DETAILED ACTION
This action is in response to the claims filed on Dec. 15th, 2023 A summary of this action:
Claims 1-35 have been presented for examination.
Claims 1-35 are objected to because of informalities
Claims 10-11 and 14 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement.
Claim 10-11, 14, 20, 27 and 34 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite
Claims 1-35 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of both a mathematical concept and mental process without significantly more.
The § 102/103 rejections below in part rely on a term in the prior art has its plain meaning explained (MPEP § 2131.01) in view of the United States NIH National Cancer Institute, Dictionary of Cancer Terms, definition of “angiography”, URL: cancer(dot)gov/publications/dictionaries/cancer-terms/def/angiography, specifically: “A procedure to x-ray blood vessels. The blood vessels can be seen because of an injection of a dye that shows up in the x-ray.” - Also, another term “Inertance” in the prior art has its meaning explained in view of Southern Illinois University, Lesson 6: Mathematical Models of Fluid Flow Components, ET 438, Automatic Control Systems Technology, Aug. 2015, URL: engr(dot)siu(dot)edu/staff/spezia/Web438A/Lecture%20Notes/lesson6et438a(dot)pdf – slide 20: “Amount of pressure drop required to increase flow rate by one unit/second. Analogy-electrical inductance.”
Claim(s) 1-2, 5-6, 8, 20-32, and 35 is/are rejected under 35 U.S.C. 103 as being unpatentable over Larrabide, Ignacio, et al. "HeMoLab–Hemodynamics Modelling Laboratory: An application for modelling the human cardiovascular system." Computers in biology and medicine 42.10 (2012): 993-1004 in view of Sharma et al., US 2013/0132054 and in further view of Schrauwen, J. T. C., et al. "Geometry-based pressure drop prediction in mildly diseased human coronary arteries." Journal of biomechanics 47.8 (2014): 1810-1815.
Claim(s) 3-4, 9, 12-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Larrabide, Ignacio, et al. "HeMoLab–Hemodynamics Modelling Laboratory: An application for modelling the human cardiovascular system." Computers in biology and medicine 42.10 (2012): 993-1004 in view of Sharma et al., US 2013/0132054 and in further view of Schrauwen, J. T. C., et al. "Geometry-based pressure drop prediction in mildly diseased human coronary arteries." Journal of biomechanics 47.8 (2014): 1810-1815 in view of Zhang et al., "Quantification of coronary microvascular resistance using angiographic images for volumetric blood flow measurement: in vivo validation", 2011
Claim(s) 10-11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Larrabide, Ignacio, et al. "HeMoLab–Hemodynamics Modelling Laboratory: An application for modelling the human cardiovascular system." Computers in biology and medicine 42.10 (2012): 993-1004 in view of Sharma et al., US 2013/0132054 and in further view of Schrauwen, J. T. C., et al. "Geometry-based pressure drop prediction in mildly diseased human coronary arteries." Journal of biomechanics 47.8 (2014): 1810-1815 in view of Zhang et al., "Quantification of coronary microvascular resistance using angiographic images for volumetric blood flow measurement: in vivo validation", 2011 and in further view of Liao, Rui, et al. "3-D reconstruction of the coronary artery tree from multiple views of a rotational X-ray angiography." The international journal of cardiovascular imaging 26.7 (2010): 733-749.
Claim(s) 33 is/are rejected under 35 U.S.C. 103 as being unpatentable over Larrabide, Ignacio, et al. "HeMoLab–Hemodynamics Modelling Laboratory: An application for modelling the human cardiovascular system." Computers in biology and medicine 42.10 (2012): 993-1004 in view of Sharma et al., US 2013/0132054 and in further view of Schrauwen, J. T. C., et al. "Geometry-based pressure drop prediction in mildly diseased human coronary arteries." Journal of biomechanics 47.8 (2014): 1810-1815 in view of Zhang et al., "Quantification of coronary microvascular resistance using angiographic images for volumetric blood flow measurement: in vivo validation", 2011 and in further view of Jarisch, “Myocardial Perfusion Evaluation Using Only Six Projections”, 2012, accessed via URL: www(dot)researchgate(dot)net/publication/271842517_Myocardial_Perfusion_Evaluation_Using_Only_Six_Projections
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Larrabide, Ignacio, et al. "HeMoLab–Hemodynamics Modelling Laboratory: An application for modelling the human cardiovascular system." Computers in biology and medicine 42.10 (2012): 993-1004 in view of Sharma et al., US 2013/0132054 and in further view of Schrauwen, J. T. C., et al. "Geometry-based pressure drop prediction in mildly diseased human coronary arteries." Journal of biomechanics 47.8 (2014): 1810-1815 and in further view of Mynard et al., “Scalability and in vivo validation of a multiscale numerical model of the left coronary circulation”, 2014
Claim(s) 34 is/are rejected under 35 U.S.C. 103 as being unpatentable over Larrabide, Ignacio, et al. "HeMoLab–Hemodynamics Modelling Laboratory: An application for modelling the human cardiovascular system." Computers in biology and medicine 42.10 (2012): 993-1004 in view of Sharma et al., US 2013/0132054 and in further view of Schrauwen, J. T. C., et al. "Geometry-based pressure drop prediction in mildly diseased human coronary arteries." Journal of biomechanics 47.8 (2014): 1810-1815 and in further view of official notice.
Claims 1 and 31 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 34 of U.S. Patent No. 11983473.
Claims 1-35 are rejected on the ground of nonstatutory double patenting as being unpatentable over the claims (see table below for details on which claims) of the U.S. Patent No. 11983473 in view of Schrauwen et al., “Geometry-based pressure drop prediction in mildly diseased human coronary arteries”, 2014.
This action is non-final
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Consideration of Prior Art Cited in Parent Application
As this is a continuation of prior US application, see MPEP § 609.02(II)(A)(2): “The examiner will consider information which has been considered by the Office in a parent application (other than an international application; see subsection I., above) when examining: (A) a continuation application filed under 37 CFR 1.53(b), (B) a divisional application filed under 37 CFR 1.53(b), or (C) a continuation-in-part application filed under 37 CFR 1.53(b). A listing of the information need not be resubmitted in the continuing application unless the applicant desires the information to be printed on the patent.”
Also see MPEP § 2001.06(b): “If the application under examination is identified as a continuation, divisional, or continuation-in-part of an earlier application, the examiner will consider the prior art properly cited in the earlier application. See MPEP § 609 and MPEP § 719.05, subsection (II)(A), example J. The examiner must indicate in the first Office action whether the prior art in a related earlier application has been reviewed. Accordingly, no separate citation of the same prior art need be made in the later application, unless applicant wants a listing of the prior art printed on the face of the patent.”
See MPEP § 707.05(a): “Additionally, copies of references cited in continuation applications if they had been previously cited in the parent application are not furnished”
The prior art in the instant parent application has been reviewed for the prosecution of the instant application. Several references from the prior art are relied upon below, as well as newly cited art.
Claim Interpretation
Claim 21: “The method according to claim 1, wherein the plurality of bi-dimensional images comprises X-ray angio images taken from at least one perspective” – see page 2, last paragraph. In view of the disclosure, the BRI of “from at least one perspective” is simply “one perspective”, wherein X-ray angiography always takes images from at least one perspective/view.
To clarify, its akin to reciting in the claim that a photographer takes an camera picture from at least one perspective, because to take an picture one must always point the camera at sometime (a perspective) to take a picture of.
In other words, its non-limiting by reciting “one perspective”. As a further point of clarity, note that while page 10 discloses that “different perspectives” are used, this is not what the claim requires, but rather only “one”.
Claim Objections
Claims 1-35 are objected to because of the following informalities:
Claim 32 is objected to be the “to determine…” FFR recitation is unclear as to whether the x-ray imager or the computer is to do this determination – the Examiner interprets it’s the computer, in view of the instant disclosure conveying this is calculated the by the processor, and similar such recitations
Claim 33 does not explicitly refer back to the x-ray imaging system of claim 32 – the Examiner suggest the article “the”
Claim 34 is objected to because: “wherein the computer is embodied in a cloud or high-performance computing cluster” is potentially ambiguous as to what claim scope this is actually reciting. In view of page 17, ¶ 2, and last paragraph on page 7, the Examiner suggest amending this to “wherein the computer is a cloud computer or a computing cluster”, wherein the Examiner interprets that a computing cluster has two or more computers. See the § 112(b) below for the “high-performance” recitation, i.e. the Examiner suggests removing this for the reasons detailed below.
Claims 5-7 and 29 recite the term “standard 1D model” and the like, wherein the term “standard” is a potentially ambiguous term as to whether or not there is an objective standard for POSITA to apply in claim interpretation. In view of page 13 ¶¶ 2-3, the Examiner suggests amending to use terms such as “predefined” or “pre-determined”, rather than “standard”. To clarify, the instant disclosure does not convey that this model is a from a medical standard or the like (e.g. a well-known model with well-known values, such as one that might be in a medical textbook or the like), but rather merely just pre-defined
The claims have numerous issues with antecedent basis. The Examiner suggests amending the claims such that the first recitation of each distinct element uses articles such as “a”/”an”, later recitations referring back to the same distinct element uses articles such as “the”/”said”, to use disambiguating modifiers (e.g., first, second, etc.) when there are multiple distinct elements with the same base term, and that the use of modifiers for each distinct element is kept consistent. Below is a non-exhaustive list of examples of these issues:
Claim 2 – claim 1 already sets for “a plurality of segments” and the like, wherein claim 2 appears to set these forth again, but adding in the lumped parameter models. The Examiner suggests clarifying this claim scope to more clearly set forth what is visually depicted in fig. 6, noting further page 14: “At a certain point, the vessels are no longer modelled by the 1 D model, but are lumped, however still containing the characteristics… For the lumping of the endpoints of the vessels, often the hydraulic electrical analogue is used”, e.g. on page 15: “At the vessel ends of the coronary tree, lumped parameter models are applied.… The vessels of the coronary tree are modeled by 1 D model and the vessel endpoints are lumped by 0D model, this makes a 1 D/0D model”
Claim 3 recites “at least parts of the conduits that form the tree”, wherein this has the phrase “parts of the conduits” – this could be potentially ambiguous (i.e. is it parts of individual conduits in the tree, are a subset of the conduits?) - in view of pages 18-23, the Examiner suggests clarifying amendments and more clear antecedents, e.g. a portion/subset of the conduits
Claim 4 – “conduit narrowing or blockage” but claim 1 recites “wherein the stenotic vessel segment has a narrowing or blockage of flow;” – the Examiner suggests in view of page 20-21 incl.: “In the case of presence of collateral flow bypassing the lesion, at 3042 the 25 processor adjusts the 1 D/OD model to cope with the amount of collateral flow. In the case of collateral flow across the lesion from the same artery... In the case of collateral flow arising from other coronary arteries, at 3042…” further clarifying amendments, and interprets this as “determines…the presence of collateral flow within the tree”, noting that claim 1 already requires that there is a stenotic vessel segment in the tree
Claim 7: “the myocardium” is the first recitation but has the article “the”
Claim 8, “the myocardium microvasculature” is the first recitation of this element
Claims 10-11: “at least two bi-dimensional images”, followed by “the bi-dimensional images”, wherein claim 1 already recites a plurality of bi-dimensional images, in other words, there is a substantial lack of clear antecedent basis – the Examiner suggests clarifying on this, i.e. the at least two is of the plurality, and claim 11 is further limiting the plurality (keeping with consistent use of prior modifying terms)
Claims 12-13 have a similar problem, with the “each bi-dimensional image”, “each” implying its referring to a plurality, but claim 12 only requires “one”, etc.
Claim 12, no article on “delay” for its first recitation
Claim 13, the “each bi-dimensional” image
Claim 33: “An X-ray…” but it depends on claim 32 which already cited this element
Claim 33, “the delay” but this is not previously recited
Claim 35, wherein it recites that the location of the region of interest is within the 1D model, but the independents require the step (c) to be performed “within the 3D reconstruction” instead
Also, note that “location” is first recited here but lacks an article
Claim 35: “the flow analysis”, however the prior recitations have the modifier “quantitative” as well
Claims 16-18 – several singular elements at their first recitation lack an article, e.g. “voltage and current” instead of “a voltage and a current”
Also, the dependents lack articles of “the” for later elements that, in the context of the claim and disclosure, are intended to refer back to the first recitations
Appropriate correction is required.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 10-11, 14, 20, 27 and 34 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. The dependent claims inherit the deficiencies of the claims they depend upon.
Regarding claim 20, the phrase "such as" renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
MPEP § 2173.05(b)(IV): “A claim term that requires the exercise of subjective judgment without restriction may render the claim indefinite. In re Musgrave, 431 F.2d 882, 893, 167 USPQ 280, 289 (CCPA 1970). Claim scope cannot depend solely on the unrestrained, subjective opinion of a particular individual purported to be practicing the invention. Datamize LLC v. Plumtree Software, Inc., 417 F.3d 1342, 1350, 75 USPQ2d 1801, 1807 (Fed. Cir. 2005));”
Claim 34 recites the phrase “high-performance”, wherein the term “high-performance” is a subjective term that renders the claim indefinite because there is no standard provided in the instant disclosure (page 7 last paragraph) for POSITA to ascertain the scope of the present claims without relying on their own unrestrained, subjective opinion when practicing the invention.
Claim 7 recites “small” – this is a subjective/relative term, with no standard in the disclosure (page 11, and the Examiner notes that the Kim reference is of record, and does not use the term as well, nor use the term “dominance”)
Claim 27 recites “semi-automatically based on user input” – the term “semi-automatically” is a subjective term, as it is unclear how much the claim requires to be automated, i.e. is it simply that the user selects the region, but using a mouse on the computer, or is the computer required to provide substantial aids to the user, e.g. automatically zooming into a portion of the image where its likely to be, providing markers, etc. Pages 16-17 paragraph between the pages do not provide an objective standard for what “semi-automatically” is to require, and what it does not require.
Claim 10 recites: “that accounts minimize effects of foreshortening and superimposing” with “at least two bi-dimensional images”– this is an unlimited functional recitation that merely expresses a desired result of the blush measurement but imposes no restriction on how this result is to be achieved, i.e. any and all means and/or methods may be used to accomplish this minimizing, and the specification provides no details (page 19 ¶ 2, page 6 second to last paragraph, etc.) on what is to be done to achieve this particular desired result. See MPEP § 2173.05(g), including: “Halliburton Energy Servs., Inc. v. M-I LLC, 514 F.3d 1244, 1255, 85 USPQ2d 1654, 1663 (Fed. Cir. 2008) (noting that the Supreme Court explained that a vice of functional claiming occurs "when the inventor is painstaking when he recites what has already been seen, and then uses conveniently functional language at the exact point of novelty") (quoting General Elec. Co. v. Wabash Appliance Corp., 304 U.S. 364, 371 (1938)); see also United Carbon Co. v. Binney & Smith Co., 317 U.S. 228, 234, 55 USPQ 381 (1942)”
To clarify, it is indefinite because it is unlimited how to achieve the desired result, but requires the computer to do so.
In the state of the art, POSITA would have known that this was typically a manual process performed by the cardiologist when performing X-ray angiography, and thus without the claim expressing how this desired result is to be achieved this is nothing more than broadly automating a manual activity to achieve a desired result, with no restriction, but for the computer, on how to do it, i.e. “conveniently functional language at the exact point of novelty”.
Liao, Rui, et al. "3-D reconstruction of the coronary artery tree from multiple views of a rotational X-ray angiography." The international journal of cardiovascular imaging 26.7 (2010): 733-749. Introduction: “Traditionally, several angiographic views are taken from different angles and then are selected subjectively based on the cardiologist’s experience, to minimize foreshortening and vessel overlap” - and, page 734, col. 2, ¶ 2: “In addition, whereas typically it is preferred to have two projections orthogonal to each other, this angular distance may not be achievable in a clinical setup when foreshortening and vessel overlap need to be minimized for the whole coronary artery tree in both projections.”
Willerson, "Coronary Artery Disease", textbook, Jan. 2015, pages 91-92 ¶¶ 3-4 in section “Angiographic views”.
Schrijver, M. "Angiographic assessment of coronary stenoses: A review of the techniques." Archives of physiology and biochemistry 111.2 (2003): 77-158. Page 122, col. 2, ¶ 2: “To acquire coronary arteriographic images, it is essential to choose an appropriate projection angle such that overlap of different vessels and foreshortening are minimal. If done properly, the resulting images allow a cardiologist to qualitatively assess the geometry and patency of the coronary arteries.” And § 17.2.1 ¶ 1: “If the viewing angles of these two systems is chosen such that they are (almost) orthogonal, the combination of the resulting image sequences allows the reconstruction of the three dimensional coronary arterial tree (Barth et al., 1988; Büchi et al., 1990; Hulzebosch et al., 1990; Kitamura et al., 1988; Klein et al., 1998; Muijtjens, 1995; Parker et al., 1987, 1988b; Ruan et al., 1994; Wahle et al., 1995). By explicitly dealing with geometric distortion during the reconstruction process, the problems with non-uniform magnification and foreshortening are resolved. It also enables the selection of optimal viewing angles for subsequent (single plane) acquisitions (Dumay, 1992; Wollschläger et al., 1988).” – note, the claim is not limited to a biplane angiography (page 21, ¶ 3 of the disclosure).
Claim 13 recites “to increase the temporal resolution of the determination” – this is another desired result without restriction on how the delay is to be used to achieve this effect. Page 21, ¶ 3 and page 7 ¶ 3, which merely convey using generic information gathered generically from commercially available machines, with this desired result as expressed in the claim for using said information.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 10-11 and 14 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. The dependent claims inherit the deficiencies of the claims they depend upon.
Claims 10-11 and 14 as discussed above recited unlimited functional limitations expressing merely desired results. See the disclosure and discussion above – as the specification conveys no manner of how these are to be accomplished, there is insufficient written description for these features. E.g. MPEP § 2161.01(I): “Regents of the Univ. of Cal. v. Eli Lilly & Co., 119 F.3d 1559, 1568, 43 USPQ2d 1398, 1405-06 (Fed. Cir. 1997)("The description requirement of the patent statute requires a description of an invention, not an indication of a result that one might achieve if one made that invention.").” and “Similarly, original claims may lack written description when the claims define the invention in functional language specifying a desired result but the specification does not sufficiently describe how the function is performed or the result is achieved”
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-35 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of both a mathematical concept and mental process without significantly more.
Step 1
Claim 1 is directed towards the statutory category of a process.
Claim 31 is directed towards the statutory category of an article of manufacture.
Claims 31, and the dependents thereof, are rejected under a similar rationale as representative claim 1, and the dependents thereof.
Step 2A – Prong 1
The claims recite an abstract idea of both a mental process and mathematical concept.
As an initial matter, the Examiner notes the focus of the claimed advance. See pages 3-5, including the numerous citations to publications in the prior art, page 10 discloses the use of conventional, commercially available angiography systems for use in mere data gathering, page 11 ¶ 2 clarifies that the 1D/0D model is not the inventive concept, but rather the idea of at least one other (Kim et al); page 13 teaches using “predefined skeleton models as taught by Dodge et al.” and further note on page 15 ¶ 4, page 15 ¶ 1 clarifies that the 0D/lumped elements are known in the art and summarized by Shi et al., with the application of scaling laws as taught by Dindorf et al., page 15 second to last paragraph clarifies that making a 3D reconstruction is known in the art, and one may readily use a technique such as the one of Onuma et al., page 15 last paragraph clarifies the identifying step may “be done manually” by a user, page 16 discusses doing CFD calculations such as by Marchandise et al., wherein the paragraph between pages 16-17 clarifies its calculations known in the art, citing to a textbook, page 17 discloses the reduced order model is a fitted equation, e.g. the one of Schrauwen et al., page 18 further clarification on the mathematical nature of this invention, i.e. “calculations…” repeated multiple times in particular contexts, and steps “to improve the calculations, page 19 clarifies the use of blush calculations as known in the art, e.g. by Vogelzang et al. (i.e. its not a new measurement technique; see Mayo in MPEP § 2106.05(d); see example 45 claim 3), page 20 ¶ 1 clarifies on another use of known techniques in the art, page 20 last paragraph clarifies that the presence of collateral flow is determined by the technique of Appleby et al. (i.e. not the inventive concept)with page 22 clarifying on the use of conventional commercial machine used as a tool for the mere data gathering (in contrast, see example 45, clam 3), the adjustments to the 1D/0D elements per page 22 is doing with “using methods well-known in the art”, page 23 discusses the use of other known methods in the art (e.g. by Vasan et al), and page 23: “All calculations discussed so far are performed and measured under rest.” -also, page 24: “At 307 the processor calculates the vFFR.”, noting page 24: “Information on blood pressure can be
rendered available from a manometer connected to a catheter or by a cuff measurement on the patient’s arm.” – see Mayo in 2106.05(d), see In re Grams in MPEP § 2106.05(g): “i. Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989);”
In summary, when one reads the specification, especially if one reads it as POSITA with the background knowledge POSITA would already posses in this field (MPEP § 2111.01), and then reads the claims, the focus of this this claimed advance is simply in the math concept (in particular, limitations (d)-(e), but this is the work of Schrauwen et al., per page 17, and per a review of the noted NPL article), wherein, at most, one could consider limitation (f) for the adding step, but see Schrauwen, as of record (the “Fast and Accurate Pressure-Drop Prediction in Straightened Atherosclerotic Coronary Arteries” article) – see the introduction, then see figure 1, note that its using the reduced-order model coupled to lumped parameter models coupled to a 3D model, and note the second to last paragraph: “In a landmark study, Tsai and
Young derived an expression for the pressure-drop over an idealized stenosis as a function of velocity and geometry.34,35 This work was later used to estimate the pressure-drop in stenosed human coronary arteries.7 Previous work from our group extended those models to incorporate more patient-specific geometrical features.” – then see the section “Geometrical Reconstruction and CFD” including fig. 2, incl.: “In the IVUS images the lumen was segmented. …The geometries were meshed with GAMBIT (ANSYS, Inc., Canonsburg, PA, USA). Mesh independency studies were conducted, resulting in a surface mesh of triangular elements with an element size of 1.25 9 1022 mm and a volume mesh with approximately 106 tetrahedral elements.” – i.e. limitations (b, d-e) are the inventive concept of Schrauwen, not of the instant application, and (c) is a step readily performed “manually” (page 15 of the instant disclosure), and for (f), well see Schrauwen fig. 1, which is replacing the 1D elements of the prior art (e.g. those of Tsai and Young) with the reduced order model of Schrauwen.
Also, with respect to (g), the Examiner notes that Schrauwen is a continuation of prior work by Schrauwen – see reference # 22: “Schrauwen, J., et al. Geometry-based pressure drop prediction in mildly diseased human coronary arteries. J. Biomech. 47(8):1810–1815, 2014.” – as discussed on page 60 ¶ 1 as well as page 61 ¶ 1. Then, see the cited prior work of Schrauwen, abstract: “Furthermore, the predicted np was used to accurately estimate FFR (r¼0.93)”, then §§ 2.3-2.5, and figure 5.
In other words, Schrauwen’s inventive concept is, in a coupled 3D-1D-0D model, to replace the 1D elements of the prior art with the fitted equation, in particular in the Schrauwen 2014 “Fast and Accurate…” article note page 60 ¶ 2: “In this study we propose a method for computing the flow dynamics in regions proximal and distal to a plaque,” and to clarify, page 66, ¶ 3: “For similar purposes, other studies coupled CFD to 1D models.3,12,30 These models are based on 1D formulations of the NS equation.1,8,9,11,14,16,19,2”
The present independent claims, for the focus of their claimed advance, is merely using the inventive concept of Schrauwen in its ordinary capacity (noting Schrauwen is doing 3D CFD simulations and fitting the equations to the results), i.e. its simply replacing, in a coupled 3D-1D-0D model, the 3D CFD simulation with the 1D model, with the only distinction being that the stenosed vessel itself (the 3D model in Schrauwen) is replaced with the fitted equation. But even this is a prior idea by Schrauwen - see Schrauwen, J., et al. Geometry-based pressure drop prediction in mildly diseased human coronary arteries. J. Biomech. 47(8):1810–1815, 2014, abstract: “The effect of the geometric features was determined and the pressure drop in mildly diseased human coronary arteries was predicted quickly based solely on geometry. This pressure drop estimation could serve as a boundary condition in CFD to model the impact of distal epicardial vessels. [i.e. two intended ways to use it, the first being replacing the CFD simulation itself for FFR calculations], the second as a boundary condition for distal vessels]” And § 2.4 (note fig. 1 for the “Stenosed”, and § 3 including fig. 5 which clarifies on this.
In summary, the focus of the claimed advance is merely how to perform the math calculations, wherein there is a great deal of conventionality in the present abstract idea (i.e. POSITA would not recognize much of an inventive concept), in a manner similar to how the original discoverer of the fitted equation intended to use the equation (i.e. no inventive concept in how the fitted equation is to be used).
The specification further discloses an array of measurements to be performed, but the specification conveys that at least a substantial portion of these measurements are known in the art (see Electric Power Group; see In re Grams; see Mayo; see PerkinElmer, Inc. v. Intema Ltd., such as in MPEP §2106.05(g and d)).
To clarify, page 4 of the disclosure: “In order to keep the computational demands on a feasible level a reduced model can be used in the calculation.” - which is what Schrauwen, “Fast and Accurate…”, introduction, ¶ 3 states: “One approach to reducing computational time is to only compute flow dynamics with CFD in the stenosed region, and use reduced-order models for epicardial arteries proximal and distal to the stenosed region”, and to clarify in ¶ 3: “This approach is illustrated in Fig. 1. A 3D reconstruction suited for CFD computations is created based on multi-planar angiography of the stenosed region. The dotted lines represent the epicardial vessels for which reduced-order models based on imaging data could be used (Right panel)” (with respect to the instant disclosure, page 4: “Furthermore, due to the fact that these methods required MR or CT imaging, they cannot be used during the intervention in which x-ray angiography is the standard imaging modality”, but Schrauwen is already doing it with x-ray angiography, with “two images” per fig. 1 of Schrauwen).
A claim to a math concept discovered by another, with no particular inventive application of how the math is integrated into a practical application (e.g. see Mayo for its discussion of Diamond v. Diehr in MPEP § 2106.04(d) ¶ 1), is not eligible subject matter under § 101.
See MPEP § 2106.04: “...In other claims, multiple abstract ideas, which may fall in the same or different groupings, or multiple laws of nature may be recited. In these cases, examiners should not parse the claim. For example, in a claim that includes a series of steps that recite mental steps as well as a mathematical calculation, an examiner should identify the claim as reciting both a mental process and a mathematical concept for Step 2A Prong One to make the analysis clear on the record.”
To clarify, see the USPTO 101 training examples, available at https://www.uspto.gov/patents/laws/examination-policy/subject-matter-eligibility.
The mathematical concept recited in claim 1 is:
A computer-implemented method for quantitative flow analysis of a tree of conduits perfusing an organ of a patient from a plurality of two bi-dimensional images of at least part of the tree obtained from different perspectives, the method comprising: - an abstract idea, but for the mere recitation to use a computer as a tool to implement the abstract idea, with an intended use of a “quantitative flow analysis” (math calculations in textual form, see below for clarification), wherein the recitation of the images is considered part of the intended use as there is no recitation later in the claim of the use of these images
a) generating a one-dimensional (1D) model that is specific to the patient, wherein the 1D model includes a plurality of segments representing conduits of at least part of the tree of the patient, wherein fluid flow through the segments of the 1D model is governed by a one-dimensional, axisymmetric form of fluid equations; - a series of mathematical relationships/equations in textual form. To clarify, this is establishing a model comprising a series of “one-dimensional, axisymmetric form of fluid equations” for each segment of the plurality of segments, and the mathematical relationships between these segments represented by the “…fluid equations” – see page 14, ¶¶ 3-5 to clarify on the BRI
Also see page 22, second to last paragraph: “A further embodiment provides for the use of patient information to improve the adjustment of the 1 D/0D model parameters to make the model more patient specific as shown at 3044 of Fig. 3E. For instance, patient height, weight, gender, age and heart type are used to calculate a correction factor for components of the 1D/0D models. This is done by the processor using methods well known in the art, for instance Clay et al, "Normal Range of human left ventricular volumes and mass using steady state free precession MRI in the radial long axis orientation", Magn Reson Mater Phy (2006) 19: 41-45.”
e) using the volumetric mesh of d) in conjunction with computational fluid dynamic simulations to generate a reduced three-dimensional (3D) model for the region of interest, wherein the reduced 3D model consists of a pressure drop equation for the region of interest; - math calculations/equations/relationships in textual form, wherein the result of the math calculations is to generate a mathematical “equation”. To clarify, pages 16-17: “CFD numerical methods and algorithms can be used to solve equations of fluid dynamics, for instance the coronary flow and pressure. These equations are based on conservation laws of classical physics (conservation of mass, momentum and energy). From these laws partial differential equations are derived and, where possible, simplified as taught by P. Wesseling, "Principles of Computational Fluid Dynamics", Springer Series in Computational Mathematics 29, 2009, p. 1-4…For these CFD simulations varying flow values can be used by the processor as a boundary condition to obtain pressure data. Optionally these calculations can be uploaded to a cloud and performed on multiple systems or uploaded to a high performance computing cluster to decrease the computation time.” And page 16, ¶ 2: “To be able to perform further CFD calculations, at 3013 a volume mesh is applied by the processor to the 30 reconstruction…” –
To clarify on the pressure drop equation, page 16-17, including: “…Instead of using the 30 reconstruction, the 30 reconstruction is replaced by an equation that represents the pressure-flow relation. This equation is then used for further calculations. The equation can be extracted by the processor by means of CFD simulations…. The outcome of this operation performed by the processor is a fitted equation for the segment of interest that calculates a pressure drop for a given flow value.”
f) adding the reduced 3D model to the 1D model of a) as a coupling condition at the position in the 1 D model identified in c) to generate a coupled model; -- mathematical equations/relationships in textual form, for use in later calculations. To clarify, page 18, ¶ 1: “At the position of the segment of interest, at 3033 the processor adds the reduced 3D model to the 1D/0D model as an extra coupling condition.”, and see the 1D model as discussed above, i.e. this, as claimed, is adding a “pressure drop equation” to a set of “one-dimensional, axisymmetric form of fluid equations”, resulting in a series of equations which are the mathematical model used for later calculations. See pages 23-24: “All calculations discussed so far are performed and measured under rest. However, for accurate vFFR calculations hyperemia is advantageously simulated…. At 305, the 1 D/0D model is adjusted by the processor to deal with the hyperemic state. All the measurements performed for the calculations are done in the rest state of the patient… At 307 the processor calculates the vFFR. The 1D/0D model [a set of equations] as described above is solved at 306 using the aortic pressure as inlet boundary condition. As a result, the vFFR value over the segment of interest is known, that is the distal pressure divided by the proximal pressure. This is known for each centerline point of the 30 reconstruction…Each stenosis can, in fact, be calculated as a reduced 3D model to be inserted in the 1 0/00 model to obtain a more accurate representation of reality.”
To further clarify, note the antecedents, i.e. the reduced 3D model consists of the equation recited above, and the 1D model is governed by equations. The coupling is merely combining mathematical relationships/equations in textual form by adding them together (e.g. forming a set of equations)
and g) performing quantitative flow analysis using the coupled model of f). – math calculations in textual form, using the equations of the coupled model. To clarify, see the above citations, also see page 20, last paragraph: “At 3042, the processor adjusts the 1 D/0D model for the presence of collateral flow. Collateral flow is an important factor for the calculations because the blood flow may bypass the coronary lesion in the main artery and supply 25 enough oxygenated blood to the tissue distal to the coronary lesion, making the stenosis less severe. There are two types of collaterals, those across lesions and those that arise from other coronary artery/arteries. In order to obtain accurate vFFR results, the calculations have to be adjusted for the presence of collateral flow.”
Then, see pages 23-24: “All calculations discussed so far are performed and measured under rest. However, for accurate vFFR calculations hyperemia is advantageously simulated…. At 305, the 1 D/0D model is adjusted by the processor to deal with the hyperemic state. All the measurements performed for the calculations are done in the rest state of the patient… At 307 the processor calculates the vFFR. The 1D/0D model as described above is solved at 306 using the aortic pressure as inlet boundary condition. As a result, the vFFR value over the segment of interest is known, that is the distal pressure divided by the proximal pressure. This is known for each centerline point of the 30 reconstruction.
Also, page 11: “At 1216, the processing module performs quantitative flow analysis. The vFFR value for each centreline point of the 3D reconstruction is, for example, calculated and shown on a display for the user”
Under the broadest reasonable interpretation, the claim recites a mathematical concept – the above limitations are steps in a mathematical concept such as mathematical relationships, mathematical formulas or equations, and mathematical calculations. If a claim, under its broadest reasonable interpretation, is directed towards a mathematical concept, then it falls within the Mathematical Concepts grouping of abstract ideas. In addition, as per MPEP § 2106.04(a)(2): “It is important to note that a mathematical concept need not be expressed in mathematical symbols, because "[w]ords used in a claim operating on data to solve a problem can serve the same purpose as a formula." In re Grams, 888 F.2d 835, 837 and n.1, 12 USPQ2d 1824, 1826 and n.1 (Fed. Cir. 1989). See, e.g., SAP America, Inc. v. InvestPic, LLC, 898 F.3d 1161, 1163, 127 USPQ2d 1597, 1599 (Fed. Cir. 2018)”
See MPEP § 2106.04(a)(2).
To clarify, see the USPTO 101 training examples, available at https://www.uspto.gov/patents/laws/examination-policy/subject-matter-eligibility.
The mental process recited in claim 1 is:
a) generating a one-dimensional (1D) model that is specific to the patient, wherein the 1D model includes a plurality of segments representing conduits of at least part of the tree of the patient, wherein fluid flow through the segments of the 1D model is governed by a one-dimensional, axisymmetric form of fluid equations; - a mental process, such as with the use of pen and paper as physical aids, to draw out a simple schematic of the coronary tree of a patient (e.g. by a cardiologist who is observing the results of routine clinical tests performed when tasked with diagnosing a patient with stenosis), e.g. drawing out a model such as the one depicted in instant fig. 6 (page 15, ¶ 3: “An example of a 1D/0D model for a subset of the coronary tree is shown in Fig. 6.”), wherein the person makes a mental judgment that the 1D segments are to be governed by 1D axi-symmetric fluid equations (e.g. equations modeling the flow of fluid through cylindrical pipes, wherein the model accounts for the length of the vessel/pipe as the one-dimension)...” – e.g. the cardiologist mentally judging the model the coronary tree/a subset of it as a series of simple pipes, wherein the equations represent the flow through the pipe
With respect to making this patient specific, this would merely be the mental process a cardiologist would be able to perform, e.g. page 18, ¶ 2: “Furthermore, the dimensions of the 1 D/0D model are adjusted to fit the actual patient specific situation…For instance at 3032 the inlet radius of the 3D reconstruction segment can be used to adjust the generalized diameters within the complete 1 D model.” – e.g. a cardiologist judging/observing dimensions of portions of the patient coronary tree, and making mental judgements to make the model more clearly reflect the patient geometry, e.g. judging to adjust the pipe diameters from a standard model (e.g. one in a textbook or other medical literature) to make the pipe model patient specific by judging to use the diameters from the patient (e.g. ones observed from clinical tests).
As a point of clarity, the equation as recited herein is readily a simple equation, e.g. one taking the form of y=mx+b, wherein a person is readily able to mentally observe data (e.g. as a chart or plot) and fit a line through the data points. Physical aids such as pen, paper, a calculator are readily able to be used to assist in the process.
c) identifying a region of interest within the 3D reconstruction which corresponds to a stenotic vessel segment belonging to the plurality of segments of the 1D model, wherein the stenotic vessel segment has a narrowing or blockage of flow; - a mental process. See pages 15-16, the paragraph split between the pages: “At 3012 in the 30 reconstruction a segment of interest is identified. This can be done manually, upon user input, or automatically or semi-automatically… Alternatively, or in combination, a user can indicate a region of interest in the 30 reconstruction or in one or both the two-dimensional images with the processor elaborating such information to determine the position of such zone in the 30 reconstruction” – e.g. a person, such as a cardiologist, making mental observations of the 3D reconstruction of the coronary tree, such as on the display of a computer or in a print-out from a computer, wherein the cardiologist or other similar medical professional makes a mental judgement of where the stenosis (by visually identifying a narrowing in the 3D reconstruction, or judging there is a blockage of flow based on the imaging and other routine clinical tests in cardiology such as stress tests performed in combination with imaging).
As a further point of clarity, the Examiner also noted dependent claim 27, wherein by § 112(d) there is a presumption (as dependent claims must further limit the independent, i.e. claim 27 conveys that this step being done “manually” per page 15 of the disclosure is an embodiment of this scope) that this step in the independent claims may be done manually such as based on user input (i.e. the person doing this step, and providing the input to a generic computer in a generic way), as claim 27 further merely limits this to being automatic or semiautomatic by broadly invoking a computer as a tool to for mere automation of this manual process.
To clarify, this limitation, when read in view of the instant disclosure pages 15-16 as cited above, is nothing more than a mental process, or simply using a computer as a tool to perform/implement the mental process, wherein neither the claims nor the disclosure describes with any particularly how this step is performed in a technological manner. MPEP § 2106.05(f): “…TLI Communications…In other words, the claims invoked the telephone unit and server merely as tools to execute the abstract idea. Thus, the court found that the additional elements did not add significantly more to the abstract idea because they were simply applying the abstract idea on a telephone network without any recitation of details of how to carry out the abstract idea…” and MPEP § 2106.05(a)(I): “ii. Accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer, FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016); iii. Mere automation of manual processes, such as using a generic computer to process an application for financing a purchase, Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 (Fed. Cir. 2017) or speeding up a loan-application process by enabling borrowers to avoid physically going to or calling each lender and filling out a loan application, LendingTree, LLC v. Zillow, Inc., 656 Fed. App'x 991, 996-97 (Fed. Cir. 2016) (non-precedential);… v. Affixing a barcode to a mail object in order to more reliably identify the sender and speed up mail processing, without any limitations specifying the technical details of the barcode or how it is generated or processed, Secured Mail Solutions, LLC v. Universal Wilde, Inc., 873 F.3d 905, 910-11, 124 USPQ2d 1502, 1505-06 (Fed. Cir. 2017);”
e) using the volumetric mesh of d) in conjunction with computational fluid dynamic simulations to generate a reduced three-dimensional (3D) model for the region of interest, wherein the reduced 3D model consists of a pressure drop equation for the region of interest; - a mental process, but for the mere instructions to use a computer as a tool in this mental process. The cardiologist would readily be able to use a computer as a tool to perform CFD simulations (see pages 16-17 of the instant disclosure, including the citation to “Principles of Computation Fluid Dynamics” reference), and then observe the results for a region of interest on the display of the computer, or as a chart printed out on pen and paper, and then mentally evaluate these results to fit an equation to the results, e.g. observe a simple data point chart showing the pressure of the vessel as compared to the length of the vessel, and then drawing a line, or a series of lines, to connect the data points, wherein they mentally judge to using a simple equation to represent the line/lines, e.g. y=mx+b (or in this case, the equivalent of Pressure = m * length +b, with m as the slope, and b as the intercept with the pressure axis), or a series of such simple equations for each set of datapoints with a linear relation, wherein they then mentally evaluate, such as with physical aids such as pen, paper, and a calculator, the lines and the equations to generate an equation that best fits the data points.
f) adding the reduced 3D model to the 1D model of a) as a coupling condition at the position in the 1 D model identified in c) to generate a coupled model; - a mental process step. E.g. the cardiologist, having obtained a reduced 3D model of a “pressure drop equation for the region of interest”, mentally judges that in their 1D model, e.g. one on pen and paper, to add this equation to represent the pressure at the position they mentally observed to have stenosis.
Pages 17-18: “First, the segment of interest as indicated earlier by the user has a certain position within the 1D/0D model. At this position, the information of the 3D reconstruction is inserted. Therefore at 3031 the processor receives an input from the user to indicate which segment(s) of the heart model (for instance the AHA model as shown in Fig. 4) is represented by the 3D reconstruction… At the position of the segment of interest, at 3033 the processor adds the reduced 3D model to the 1 D/0D model as an extra coupling condition…” – i.e. the cardiologist, having drawn a model using pen and paper, e.g. fig. 6 then adds in an equation into the model at the mentally identified, e.g. by mental observation, position in the model, e.g. by writing down in the model that for a particular node a particular equation (the pressure drop equation) is to be used for calculations.
Also see page 24, ¶ 6: “Each stenosis can, in fact, be calculated as a reduced model to be inserted in the 1D/0D model to obtain a more accurate representation of reality.” – i.e. adding another equation/math relationships into a set of equations/math relationships, wherein the new equation/math relationship of the “reduced model” is the result of math calculations
This limitation does not require any performance of the calculations, rather it is merely setting up a series of equations to be solved, which may readily be done either purely mentally or using pen and paper as an aid to draw a model, e.g. fig. 6, assign equations to each node in the model, etc.
and g) performing quantitative flow analysis using the coupled model of f) – a mental process step wherein the person, i.e. the cardiologist, solves the equations discussed above, such as by using pen and paper, and a calculator, to solve the equations. The Examiner also notes that the claim does not require that the equations are for the entire coronary tree, but rather only for a “part of the tree”, as such a simple model of only a few vessels in the tree may be used for these calculations, e.g. a model only represents 3-4 vessels (such as a subset of the vessels shown in fig. 4).
Should a more complex model be used, or should the cardiologist desire for faster calculations, then the cardiologist may apply a computer to perform the calculations, or use a computer as a tool to implement the calculations.
Under the broadest reasonable interpretation, these limitations are process steps that cover mental processes including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of physical aids but for the recitation of a generic computer component. If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the "Mental Process" grouping of abstract ideas. A person would readily be able to perform this process either mentally or with the assistance of physical aids. See MPEP § 2106.04(a)(2).
To clarify, see the USPTO 101 training examples, available at https://www.uspto.gov/patents/laws/examination-policy/subject-matter-eligibility. In particular, with respect to the physical aids, see example # 45, analysis of claim 1 under step 2A prong 1, including: “Note that even if most humans would use a physical aid (e.g., pen and paper, a slide rule, or a calculator) to help them complete the recited calculation, the use of such physical aid does not negate the mental nature of this limitation.”; also see example # 49, analysis of claim 1, under step 2A prong 1: “Moreover, the recited mathematical calculation is simple enough that it can be practically performed in the human mind. Even if most humans would use a physical aid, like a pen and paper or a calculator, to make such calculations, the use of a physical aid would not negate the mental nature of this limitation.”
As such, the claims recite an abstract idea of both a mental process and mathematical concept.
Step 2A, prong 2
The claimed invention does not recite any additional elements that integrate the judicial exception into a practical application. Refer to MPEP §2106.04(d).
The following limitations are merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f), including the “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more”:
Claim 1 - computer-implemented; Claim 31 - A non-transitory computer-readable storage medium having stored thereon executable instructions that, when executed by one or more processors of a computer system, cause the computer system to;
e) using the volumetric mesh of d) in conjunction with computational fluid dynamic simulations to generate a reduced three-dimensional (3D) model for the region of interest - should this be found to not be part of the math concept as discussed above, then this would be considered as part of the mere instructions to use a computer as a tool to implement the abstract idea, when read in view of pages 16-17 the paragraph split between the pages, also see page 17 of the disclosure for Schrauwen et al., as discussed above, as this step in Schrauwen, and pointed to by the specification, is merely using commercial software tools to perform this step).
b) generating a three-dimensional (3D) reconstruction for a subset of the tree of the patient; d) using the 3D reconstruction to construct a volumetric mesh for the subset of the tree of the patient corresponding to the region of interest; - part of the mere instructions to use a computer as a tool to perform the abstract idea. See page 15, second to last paragraph: “In Fig. 3B, at 3011 the processor makes a patient specific reconstruction of a subset of interest of the coronary tree which includes the coronary lesion of interest using multiple two-dimensional images as known in the art as, for instance, taught in "A novel dedicated 3-dimensional quantitative coronary analysis methodology for bifurcation lesions", Yoshinobu Onuma,Chrysafios Girasis, Jean-Paul Aben, Giovanna Sarno, Nicolo Piazza, Coen Lokkerbol, Marie-Angel Morel, Patrick W. Serruys, Eurolntervention 2011; 6:1-00. An example is shown in Fig. 7.” And Page 16, ¶ 2: “To be able to perform further CFD calculations, at 3013 a volume mesh is applied by the processor to the 30 reconstruction. To increase accuracy and computational speed of the CFO calculations element size and shape of the volume mesh can be varied throughout the vessel as taught, for instance, by Marchandise et al, "Quality open source mesh generation for cardiovascular flow simulations", Modeling of Physiological Flows, MS&A - Modeling, Simulation and Applications, Volume 5, 2012, pp 395-414. These adjustments can depend on location in the vessel (e.g., smaller elements near vessel boundaries) and geometric properties/features like local curvature and diameter/area changes”, wherein there is no inventive concept found in these recitations as these recitations are merely using what is already at least “known in the art”, and because the technical details of the implementation of these limitations are left to the work of others in the field
Also see page 17 of the disclosure for Schrauwen et al., as discussed above, as these steps in Schrauwen, and pointed to by the specification, is merely using commercial software and other commonplace algorithms as tools to perform these acts).
and g) performing quantitative flow analysis using the coupled model of f) – should it be found that this limitation is not part of the abstract idea, then the Examiner submits this would be mere instructions to “apply it” for the abstract idea as this limitation places no restriction on how the quantitative flow analysis is performed but for the recitation of using the result of the abstract idea in a generalized manner
The following limitations are adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g):
… a tree of conduits perfusing an organ of a patient from a plurality of two bi-dimensional images of at least part of the tree obtained from different perspectives– should this be given patentable weight, even though the body of the claim makes no recitation of the usage of these images, then this limitation would be considered merely data gathering
b) generating a three-dimensional (3D) reconstruction for a subset of the tree of the patient; d) using the 3D reconstruction to construct a volumetric mesh for the subset of the tree of the patient corresponding to the region of interest; - mere data gathering for use in the later use in the abstract idea. See page 15, second to last paragraph: “In Fig. 3B, at 3011 the processor makes a patient specific reconstruction of a subset of interest of the coronary tree which includes the coronary lesion of interest using multiple two-dimensional images as known in the art as, for instance, taught in "A novel dedicated 3-dimensional quantitative coronary analysis methodology for bifurcation lesions", Yoshinobu Onuma,Chrysafios Girasis, Jean-Paul Aben, Giovanna Sarno, Nicolo Piazza, Coen Lokkerbol, Marie-Angel Morel, Patrick W. Serruys, Eurolntervention 2011; 6:1-00. An example is shown in Fig. 7.” And Page 16, ¶ 2: “To be able to perform further CFD calculations, at 3013 a volume mesh is applied by the processor to the 30 reconstruction. To increase accuracy and computational speed of the CFO calculations element size and shape of the volume mesh can be varied throughout the vessel as taught, for instance, by Marchandise et al, "Quality open source mesh generation for cardiovascular flow simulations", Modeling of Physiological Flows, MS&A - Modeling, Simulation and Applications, Volume 5, 2012, pp 395-414. These adjustments can depend on location in the vessel (e.g., smaller elements near vessel boundaries) and geometric properties/features like local curvature and diameter/area changes”, wherein there is no inventive concept found in these recitations as these recitations are merely using what is already at least “known in the art”, and because the technical details of the implementation of these limitations are left to the work of others in the field
A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception. See MPEP § 2106.04(d).
The claimed invention does not recite any additional elements that integrate the judicial exception into a practical application. Refer to MPEP §2106.04(d).
Step 2B
The claimed invention does not recite any additional elements/limitations that amount to significantly more.
The following limitations are merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f), including the “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more”:
Claim 1 - computer-implemented; Claim 31 - A non-transitory computer-readable storage medium having stored thereon executable instructions that, when executed by one or more processors of a computer system, cause the computer system to;
e) using the volumetric mesh of d) in conjunction with computational fluid dynamic simulations to generate a reduced three-dimensional (3D) model for the region of interest - should this be found to not be part of the math concept as discussed above, then this would be considered as part of the mere instructions to use a computer as a tool to implement the abstract idea, when read in view of pages 16-17 the paragraph split between the pages
b) generating a three-dimensional (3D) reconstruction for a subset of the tree of the patient; d) using the 3D reconstruction to construct a volumetric mesh for the subset of the tree of the patient corresponding to the region of interest; - part of the mere instructions to use a computer as a tool to perform the abstract idea. See page 15, second to last paragraph: “In Fig. 3B, at 3011 the processor makes a patient specific reconstruction of a subset of interest of the coronary tree which includes the coronary lesion of interest using multiple two-dimensional images as known in the art as, for instance, taught in "A novel dedicated 3-dimensional quantitative coronary analysis methodology for bifurcation lesions", Yoshinobu Onuma,Chrysafios Girasis, Jean-Paul Aben, Giovanna Sarno, Nicolo Piazza, Coen Lokkerbol, Marie-Angel Morel, Patrick W. Serruys, Eurolntervention 2011; 6:1-00. An example is shown in Fig. 7.” And Page 16, ¶ 2: “To be able to perform further CFD calculations, at 3013 a volume mesh is applied by the processor to the 30 reconstruction. To increase accuracy and computational speed of the CFO calculations element size and shape of the volume mesh can be varied throughout the vessel as taught, for instance, by Marchandise et al, "Quality open source mesh generation for cardiovascular flow simulations", Modeling of Physiological Flows, MS&A - Modeling, Simulation and Applications, Volume 5, 2012, pp 395-414. These adjustments can depend on location in the vessel (e.g., smaller elements near vessel boundaries) and geometric properties/features like local curvature and diameter/area changes”, wherein there is no inventive concept found in these recitations as these recitations are merely using what is already at least “known in the art”, and because the technical details of the implementation of these limitations are left to the work of others in the field
and g) performing quantitative flow analysis using the coupled model of f) – should it be found that this limitation is not part of the abstract idea, then the Examiner submits this would be mere instructions to “apply it” for the abstract idea as this limitation places no restriction on how the quantitative flow analysis is performed but for the recitation of using the result of the abstract idea in a generalized manner
The following limitations are adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g):
… a tree of conduits perfusing an organ of a patient from a plurality of two bi-dimensional images of at least part of the tree obtained from different perspectives– should this be given patentable weight, even though the body of the claim makes no recitation of the usage of these images, then this limitation would be considered merely data gathering
b) generating a three-dimensional (3D) reconstruction for a subset of the tree of the patient; d) using the 3D reconstruction to construct a volumetric mesh for the subset of the tree of the patient corresponding to the region of interest; - mere data gathering for use in the later use in the abstract idea. See page 15, second to last paragraph: “In Fig. 3B, at 3011 the processor makes a patient specific reconstruction of a subset of interest of the coronary tree which includes the coronary lesion of interest using multiple two-dimensional images as known in the art as, for instance, taught in "A novel dedicated 3-dimensional quantitative coronary analysis methodology for bifurcation lesions", Yoshinobu Onuma,Chrysafios Girasis, Jean-Paul Aben, Giovanna Sarno, Nicolo Piazza, Coen Lokkerbol, Marie-Angel Morel, Patrick W. Serruys, Eurolntervention 2011; 6:1-00. An example is shown in Fig. 7.” And Page 16, ¶ 2: “To be able to perform further CFD calculations, at 3013 a volume mesh is applied by the processor to the 30 reconstruction. To increase accuracy and computational speed of the CFO calculations element size and shape of the volume mesh can be varied throughout the vessel as taught, for instance, by Marchandise et al, "Quality open source mesh generation for cardiovascular flow simulations", Modeling of Physiological Flows, MS&A - Modeling, Simulation and Applications, Volume 5, 2012, pp 395-414. These adjustments can depend on location in the vessel (e.g., smaller elements near vessel boundaries) and geometric properties/features like local curvature and diameter/area changes”, wherein there is no inventive concept found in these recitations as these recitations are merely using what is already at least “known in the art”, and because the technical details of the implementation of these limitations are left to the work of others in the field
In addition, the above insignificant extra-solution activities are also considered as well-understood, routine, and conventional activities, as discussed in MPEP § 2106.05(d):
from a plurality of two bi-dimensional images of at least part of the tree obtained from different perspectives – see the below evidence, also the Examiner notes that the claim recites no particular tool required to gather the data, so also see MPEP § 2106.05(d)(II): ““iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining "shadow accounts"); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log); iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93;”
b) generating a three-dimensional (3D) reconstruction for a subset of the tree of the patient; -page 15, ¶¶ 4-5: “These geometrical features are based on common values as described in Dodge et al, "Lumen diameter of normal human coronary arteries: influence of age, sex, anatomic variation, and left ventricular hypertrophy or dilation", Circulation 1992; 86: 232-246…. In Fig. 3B, at 3011 the processor makes a patient specific reconstruction of a subset of interest of the coronary tree which includes the coronary lesion of interest using multiple two-dimensional images as known in the art as, for instance, taught in "A novel dedicated 3-dimensional quantitative coronary analysis methodology for bifurcation lesions", Yoshinobu Onuma, Chrysafios Girasis, Jean-Paul Aben, Giovanna Sarno, Nicolo Piazza, Coen Lokkerbol, Marie-Angel Morel, Patrick W. Serruys, Eurolntervention 2011; 6:1-00.”– also see the below evidence, and note the disclosure states “for instance”
d) using the 3D reconstruction to construct a volumetric mesh for the subset of the tree of the patient corresponding to the region of interest – page 17: “To be able to perform further CFO calculations, at 3013 a volume mesh is applied by the processor to the 30 reconstruction. To increase accuracy and 10 computational speed of the CFO calculations element size and shape of the volume mesh can be varied throughout the vessel as taught, for instance, by Marchandise et al, "Quality open source mesh generation for cardiovascular flow simulations", Modeling of Physiological Flows, MS&A - Modeling, Simulation and Applications, Volume 5, 2012, pp 395-414.”…” – also see the below evidence
The Examiner finds the following activities as WURC, wherein these include actitivies recited in several of the dependent claims in various forms (these findings are here for conciseness of the rejection):
Obtaining a plurality of two-dimensions images from X-rays – see the instant disclosure page 1, last paragraph: “At the moment X-ray angiography is the standard technique for anatomical assessment of the coronary arteries and the diagnosis of coronary artery disease. During X-ray angiography several different two-dimensional images (also called bi-dimensional images), also called two-dimensional projections (also called bi-dimensional projections), of the object under examination can be obtained from different views or perspectives by rotating the arm, holding the Xray source and the image intensifier, with reference to the patient.” And page 10, second to last paragraph: “For example, a bi-plane or single plane angiographic system can be used such as those manufactured, for example, by Siemens (Artis zee Biplane) or Philips (Allura Xper FD).”
Performing densitometric image analysis – see previously cited (in the parent case) Willerson et al., “Coronary Artery Disease”, preface, then see page 108, col. 2, ¶ 3: “Nearly all techniques detect the arterial edge by videodensitometric methods, usually employing a weighted average of the first and second derivatives of the density change across the artery to identify the edge [ 302 ].” Also see:
Previously cited Murata et al., “The influence of coronary collateral flow on the assessment of myocardial perfusion by videodensitometry”, 1997 - § 1: “Digital videodensitometric analysis of the kinetics of contrast coronary angiography has been used extensively to assess myocardial perfusion and coronary artery flow reserve w1–13x. This approach provides potentially useful physiologic information that complements the morphometric images provided by coronary arteriography…”
Vassali et al., “Measurement of coronary flow reserve and its role in patient care”, 1998 – see the section “Methods of measuring CFR” for the subsection “Videodensitometry and digital subtraction angiography”
Barfett, " Blood Velocity and Volumetric Flow Rate Calculated from Dynamic 4D CT Angiography using a Time of Flight Approach”, Master’s Thesis, University of Toronto, 2014 – page 16, ¶ 2: “The development of X-ray based imaging techniques and high density intravenous contrast media enabled the logical extension of indicator dilution theory into imaging science. On review of literature, the first identified such studies were performed in the 1950s and were subsequently followed by extensive academic activity (Gidlund 1957). X-ray systems were developed which permitted the time dependent assessment and tracking of contrast bolus motion in arteries and veins. Rather than using the concentration versus time data attained from repeat sampling of an artery or vein, continuous monitoring of a dense bolus was possible in regions of interest (ROIs) placed around arteries producing density versus time data. The technique was generally referred to as “video densitometry”. The resulting plots are in this manuscript referred to as time density curves (TDCs), however are also frequently described in the literature as time attenuation curves (TACs).
Zhang et al., “Quantification of coronary microvascular resistance using angiographic images for volumetric blood flow measurement: in vivo validation”, 2011, subsection “Blood flow measurement using angiographic images” on pages H2097-H2098
Berry et al., “Importance of collateral circulation in coronary heart disease”, 2007, section: “Angiographic evaluation of coronary collateral arteries”: “Coronary angiography is the standard method to identify coronary collateral arteries (Table 2). Angiography with ordinary visual detection has limited resolution. Arterioles ,100 mm are invisible to the naked eye,3 and visible collaterals typically have a diameter of 0.5 mm.4 The angiographic assessment of collateral circulation can be refined by off-line computer analyses.” – then see page 279 for “Angiographic collateral degree” and “Angiographic demonstration of coronary collateral arteries”, then see section “Non-invasive evaluation of coronary artery collateral arteries” on page 281, also see table 2
Performing blush image analysis – page 19, ¶ 1 of the instant disclosure: “The myocardial blush calculations as known in the art, as taught, for instance, by Vogelzang et al 'Computer-assisted myocardial blush quantification after percutaneous coronary angioplasty for acute myocardial infarction: a substudy from the TAPAS trial', European Heart Journal (2009) 30, 594-599” Also see
Willerson et al., “Coronary Artery Disease”, ISBN 978-1-4471-2827-4, 2015, preface, then page 117, col. 1, ¶ 3: “Recently, an angiographically-defined index of microvascular perfusion has been developed, the “TIMI myocardial perfusion grade.” Also called a myocardial blush score, it is measured by observing the myocardial washout of contrast media after coronary injection [ 365b ]. A normal response (Grade 3) is a brisk washin-washout. Persistence of contrast after coronary injection (Grade 2) and contrast staining of the myocardium (Grade 1) suggests increased microvascular permeability and obstruction. The absence of myocardial opacification indicates extensive microcirculatory obstruction, usually associated with dense infarction. Mortality after acute infarction is inversely related to the myocardial blush score, independent of TIMI coronary blood flow.”
Henriques et al., “Angiographic Assessment of Reperfusion in Acute Myocardial Infarction by Myocardial Blush Grade”, 2003, page 2115: “We previously described the myocardial blush grade (MBG) after primary angioplasty as an important predictor of infarct size and survival.8 After this study, several other authors confirmed these findings with a similar method in patients treated with primary coronary angioplasty9 and with a somewhat different method for patients after thrombolytic treatment and confirmed that myocardial blush is an independent predictor for outcome in acute myocardial infarction patients treated with reperfusion therapy.10–13
Zhang et al., “Quantification of coronary microvascular resistance using angiographic images for volumetric blood flow measurement: in vivo validation”, 2011, subsection “Blood flow measurement using angiographic images” on pages H2097-H2098
Lienard et al., “Quantitative Tool for the Assessment of Myocardial Perfusion during X-Ray Angiographic Procedures”, 2009, § 1 ¶ 1
Hofmann et al., “Quantitative assessment of myocardial blush grade in patients with coronary artery disease and in cardiac transplant recipients”, 2014, abstract and introduction, then see pages 1109-1110
Gai et al., “Calculation of Coronary Angiographic Total Blush in Patients with Coronary Artery Disease and its Prognostic Implication”, 2015, abstract and introduction
Vogelzang et al., “Computer-assisted myocardial blush quantification after percutaneous coronary angioplasty for acute myocardial infarction: a substudy from the TAPAS trial†”, 2009, abstract and introduction
The use of medical imaging modalities, including x-rays, to generate models of the coronary tree, including 0D, 1D, and 3D models, and models with meshes:
Liao, Rui, et al. "3-D reconstruction of the coronary artery tree from multiple views of a rotational X-ray angiography." The international journal of cardiovascular imaging 26.7 (2010): 733-749. Abstract, then see introduction ¶¶ 1-3 incl.: “It has been quantitatively evaluated in [3, 4] that 3-D reconstruction of coronary arteries from 2-D angiography permits accurate, reproducible and quantitative assessment of the 3-D geometric properties of coronary arteries, including diameter statistics, length, volume, angles at vascular branching points and tortuosity of vessels…3-D symbolic reconstruction of coronary arteries from angiographic images was investigated using two projections [3–5, 8, 9, 11, 18, 19], either from a fixed biplane system, or from different projections on a monoplane C-Arm.
Sinclair, Matthew D., et al. "Measurement and modeling of coronary blood flow." Wiley Interdisciplinary Reviews: Systems Biology and Medicine 7.6 (2015): 335-356. Page 336, col. 2, ¶¶ 3-4 including: “of cardiac health with, in particular, X-ray angiography applied to identify coronary artery disease (CAD) in the clinical setting for decades.20 This method employs the injection of a radio-opaque dye via invasive catheterization, which highlights the lumen of the coronary arteries visualized in real-time with X-ray fluoroscopy. The resulting images are then used to visually identify stenosed vessels in moderate-to-severe cases. More recently, noninvasive coronary computed tomography angiography (CCTA) has also increasingly been used to produce three-dimensional (3D) vessel geometries from which vessel lumen diameter can be measured.” – then see the section “MODELING APPROACHES IN THE CORONARY CIRCULATION” starting on page 340, including its subsections, including the subsection on Lumped Parameter models and 1D Flow models
Taylor, Charles A., and C. A. Figueroa. "Patient-specific modeling of cardiovascular mechanics." Annual review of biomedical engineering 11.1 (2009): 109-134. Abstract, then see introduction ¶¶ 1-2: “At every stage of the circulatory system, whether blood is swirling in the heart or streaming through the arterial tree, a range of mathematical models have been employed to quantify biomechanical conditions. These models, including lumped parameter, one-dimensional (1D) wave propagation, and three-dimensional (3D) numerical methods, can all be used with effect to describe cardiovascular mechanics… Development of image-based modeling technologies for simulating blood flow began in the late 1990s (1–3)…” then see ¶ 3; then see the section “Acquisition of Patient-Specific Anatomic and Physiologic Data” and its discussion of the use of CY images which are “pprojection X-ray images” in ¶ 2, then see the section “Image Segmentation and Image-Based Geometric Modeling” including figure 1 and its accompanying description, incl: “Typically, geometric solid-models of blood vessels have been constructed by (a) extracting a set of points (a contour) approximating the inside boundary of a vessel on a series of 2D image slices, (b) interpolating the contour with a curve, (c) lofting a surface through the interpolated curves, and (d ) joining the surfaces together to form a bounded volume.” – then, see the section “Automatic Mesh Generation” followed by the section “Patient-Specific Physiologic Models and Boundary Conditions” including fig. 2
Tu, Shengxian, et al. "Fractional flow reserve calculation from 3-dimensional quantitative coronary angiography and TIMI frame count: a fast computer model to quantify the functional significance of moderately obstructed coronary arteries." JACC: Cardiovascular Interventions 7.7 (2014): 768-777. Abstract, then see the section “Three-dimensional QCA” starting on page 769; then see the section “Computation fluid dynamics” starting on page 770, note the use of commercially available technology used
Saito, Tsuneo, et al. "Three-dimensional quantitative coronary angiography." IEEE Transactions on Biomedical Engineering 37.8 (1990): 768-777. Abstract, then see § 1 incl: “Therefore, three-dimensional (3-D) reconstruction of the coronary arterial tree structure from multiple projections and its 3-D display offer significant clinical benefits… number of earlier works for estimating the 3-D structure of coronary arteries with computer assistance have been reported [7]-[ 11]. These works are based on knowledge of the X-ray geometry of projections and on iterative identification of matching structures in a few views…” and see its discussion of the state of the art in 1990, then see § II, including subsections §§ II.A-II.B
Takarada, Shigeho, Zhang Zhang, and Sabee Molloi. "An angiographic technique for coronary fractional flow reserve measurement: in vivo validation." The international journal of cardiovascular imaging 29.3 (2013): 535-544. Pages 537-538 including figure 1 and its accompanying description
Wong, Jerry T., et al. "Quantification of fractional flow reserve based on angiographic image data." The international journal of cardiovascular imaging 28.1 (2012): 13-22. Pages 15-17 for sections on Imaging system and Angiograph based FFR
Sharma, Puneet, et al. "A framework for personalization of coronary flow computations during rest and hyperemia." 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2012. § 1 ¶ 2: “For an accurate computation of a patient’s coronary bloodflow, two key requirements for CFD-based methods are - (a) anatomical model of the coronary vessel tree and (b) the boundary conditions at the inlet and outlets. Recent advances in medical image processing have addressed the former by employing manual, semi-automatic or fully-automatic algorithms for multi-modality image segmentation and mesh generation, but there has been considerably less focus on the latter…”
The use of computer simulations to do quantitative flow analysis to obtain the FFR (fractional flow reserve)
Taylor, Charles A., Timothy A. Fonte, and James K. Min. "Computational fluid dynamics applied to cardiac computed tomography for noninvasive quantification of fractional flow reserve: scientific basis." Journal of the American College of Cardiology 61.22 (2013): 2233-2241. Page 2234, col. 1, ¶¶ 2-3, incl: “Recent advances in computational fluid dynamics enable calculation of coronary flow and pressure fields from anatomic image data (18). Applied to CTA, these technologies enable calculation of FFR without additional imaging or medications. The DISCOVER-FLOW (Diagnosis of Ischemia-Causing Stenoses Obtained Via Noninvasive Fractional Flow Reserve) trial, compared with invasive FFR, noninvasive FFR derived from CTA, or FFRCTA, demonstrated per-vessel accuracy, sensitivity, specificity” – also, see col. 2, ¶¶ 2-4, including: “Computation of FFRCTA requires construction of an anatomic model of the coronary arteries; a mathematical model of coronary physiology to derive boundary conditions representing cardiac output, aortic pressure, and microcirculatory resistance; and a numerical solution of the laws of physics governing fluid dynamics…” – also, see figure 5
Min, James K., et al. "Noninvasive fractional flow reserve derived from coronary CT angiography: clinical data and scientific principles." Cardiovascular Imaging 8.10 (2015): 1209-1222. Page 1209, ¶¶ 1-2
Sinclair, Matthew D., et al. "Measurement and modeling of coronary blood flow." Wiley Interdisciplinary Reviews: Systems Biology and Medicine 7.6 (2015): 335-356 – page 338, paragraph between the pages: "Furthermore, a modeling-based noninvasive approach to compute FFR using 3D computational fluid dynamics (CFD) simulations in the coronary arteries, FFRCT, has been shown to greatly outperform TAG for classifying stenosis severity50 (FFRCT is discussed further in the Boundary Conditions and Multiscale Modeling section).” – then see the section " MODELING APPROACHES IN THE CORONARY CIRCULATION” including its subsections, including the subsection on Lumped Parameter Modesl, 1D Flow models, and 3D Models”, then see page 346, col. 2, ¶¶ 1-2: “Another active field is the coupling of 3D models with 1D and 0D models to capture coronary hemodynamics as part of a closed-loop multiscale system…. The effects of stenosis geometry on average cross-sectional flow and pressure drop have been studied extensively.112,113,175,87,176 There has recently been a promising clinical application of patient-specific 3D CFD modeling in the coronary arteries to determine computed FFR (FFRCT) noninvasively.87,88,175,177 Coronary CT angiography is acquired at rest and used to rapidly reconstruct a patient-specific 3D vascular geometry of the epicardial arteries and root of the aorta which may include any stenoses…”
The claimed invention is directed towards an abstract idea of both a mathematical concept and a mental process without significantly more.
Regarding the dependent claims
Claim 2 is further limiting both the mental process and mathematical concept as discussed above - see page 4, ¶¶ 2-3: “In order to keep the computational demands on a feasible level a reduced model can be used in the calculation. That is, sections of the coronary tree can be represented by a one-dimensional network or zero-dimensional (lumped) model. This multi-scale approach was adopted by Kirn et al, "Patient-specific modelling of blood flow and pressure in human coronary arteries", Annals of Biomedical Engineering 38, 3195-3209, 2010 to compute physiologically realistic pressure and flow waveforms in coronary vessels at baseline conditions. 3D CFD simulations were coupled with an analytical 1 D model of the circulation and a lumped-parameter model of the coronary resistance.”, see the above citations including fig. 6, wherein simple circuit elements are used for the lumped parameter models, i.e. a person is readily able to draw out, such as with pen and paper, a simple circuit and conduct mental evaluations of it, such as may be aided by other physical aids, wherein a person is readily able to mentally evaluate simple equations (e.g. Ohm’s Law of V=IR, or hydroelectric analogs of these) so as to perform the mental evaluation
Claim 3 is considered as an insignificant extra-solution activity of mere data gathering of the image analysis, followed by a mental process step of “update the coupled model…” using the gathered data (e.g. the cardiologist observing results from routine clinical tests, and making mental judgements to adjust/update the model to reflect the results), wherein “update the coupled model…” is also considered as math equations/relationships/calculation in textual form, wherein combination of features is akin “i. Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989);” as discussed in MPEP § 2106.05(g) - to clarify, see the instant disclosure, including page 17: “At 303, the processor can adjust the heart model using the variation between the patient specific geometrical features and the common geometrical features in the segment of the coronary tree. In order to make the constructed 1 D/0D model more accurate and to incorporate the 3D morphology of the lesion of interest, 3D information of a segment of interest of the coronary tree can be used. This information can be obtained from two-dimensional angiographic images.”, also see page 18: “…To make the calculations even more accurate, the 1D/0D model can be 15 adjusted to make it even more patient specific. Different aspects can be taken into account, for instance myocardium status, the presence of collateral flow, L V wall motion, coronary motion and patient information… The status of the myocardium microvasculature can be determined by the processor by performing myocardial blush calculations… The myocardial blush calculations as known in the art, as taught, for instance, by Vogelzang et al…” and page 20: “As an example of adjusting specific components of the heart model using myocardial status, at 3041 the processor adjusts end-resistances of the model as shown in Fig. 9. For example, an increased microvascular resistance of a specific part of the heart is measured using blush. This can be incorporated in the model 20 by adjusting the value of the end-resistance belonging to the coronary artery supplying that region of the heart with blood using a weighting factor… At 3042, the processor adjusts the 1D/0D model for the presence of collateral flow. Collateral flow is an important factor for the calculations because the blood flow may bypass the coronary lesion in the main artery and supply enough oxygenated blood to the tissue distal to the coronary lesion, making the stenosis less severe… In order to obtain accurate vFFR results, the calculations have to be adjusted for the presence of collateral flow. The possible presence of collateral flow can be determined as taught in the art by Appleby et al…” and page 21: “In the case of collateral flow across the lesion from the same artery, the 1 D model is adjusted, for example, by adding one or more elements for the collateral flow parallel to the lesion in the 1 D model as illustrated in Fig. 1 0a… For example, extra OD elements can be added simulating the collateral flow as illustrated in Fig. 10b.” – i.e. the math equations/relationships being adjusted/updated by adding in another equation/relationship/variable to the set of equations/relations, wherein the cardiologist would have also readily be able to perform such a step mentally in a similar manner to the examples discussed above for the independent claim. Also see page 22, second to last paragraph: “A further embodiment provides for the use of patient information to improve the adjustment of the 1 D/0D model parameters to make the model more patient specific as shown at 3044 of Fig. 3E. For instance, patient height, weight, 25 gender, age and heart type are used to calculate a correction factor for components of the 1 D/0D models.” – additional WURC evidence is discussed above in the independents for the types of image analysis to be performed in the disclosure, and dependent claims of this claim
Claim 4 is considered as part of the mere data gathering, wherein this is WURC in view of the evidence discussed above in the independent claims.
Claim 5 is further limiting both the mental process and the mathematical concept, to clarify this is akin to starting with a standard set of equations and standard values for some of the variables in the equations, e.g. out of a textbook, wherein some of the values are mentally judged to be adjusted, e.g. the diameters of vessels, wherein this is also part of the math concept as its merely adjusting values of variables in the set of equations/relationships, wherein the “geometric features extracted…” recitation is math calculations in textual form – see page 5, (c): “making calculations based on the 3D reconstruction to determine geometrical features of the conduits such as diameters, lengths, 30 curvatures, centrelines, or the like;” and page 11, ¶ 1: “At 1212 the data processing module 114 makes calculations based on the 3D reconstruction to determine geometrical features of the conduits such as diameters, lengths, curvatures, centrelines, or the like.” Should it be found that the “…geometric features extracted…” feature is not math calculations in textual form, then the Examiner submits this would be considered as mere data gathering for the abstract idea, wherein this is WURC in view of page 15, ¶¶ 4-5: “These geometrical features are based on common values as described in Dodge et al, "Lumen diameter of normal human coronary arteries: influence of age, sex, anatomic variation, and left ventricular hypertrophy or dilation", Circulation 1992; 86: 232-246…. In Fig. 3B, at 3011 the processor makes a patient specific reconstruction of a subset of interest of the coronary tree which includes the coronary lesion of interest using multiple two-dimensional images as known in the art as, for instance, taught…” – additional evidence is discussed above for the independent claims
Claim 6 is rejected under a similar rationale as claim 5
Claim 7 is a mental process, i.e. a person, e.g. a cardiologist, mentally selecting a model based on coronary dominance (page 15 ¶ 4) such as by a mental judgement/evaluation/opinion
Claim 8 is considered as both part of the mental process as a mental judgement such as by a cardiologist, and part of the math concept. To clarify, pages 18-20: “In order to improve the calculations, it is important to know the status of the myocardium microvasculature as indicated by operation 3041 of Fig. 3E…The status of the myocardium microvasculature can be determined by the processor by performing myocardial blush calculations…The myocardial blush calculations as known in the art…As an example of adjusting specific components of the heart model using myocardial status, at 3041 the processor adjusts end-resistances of the model as shown in Fig. 9. For example, an increased microvascular resistance of a specific part of the heart is measured using blush. This can be incorporated in the model 20 by adjusting the value of the end-resistance belonging to the coronary artery supplying that region of the heart with blood using a weighting factor…” – i.e. this is merely adjusting values of variables in the equations of the model, potentially using another mathematical relationship of a “weighting factor” as part of the adjustment
Claim 9 recites mere data gathering that is WURC in view of pages 18-19: “In order to improve the calculations, it is important to know the status of the myocardium microvasculature as indicated by operation 3041 of Fig. 3E…The status of the myocardium microvasculature can be determined by the processor by performing myocardial blush calculations…The myocardial blush calculations as known in the art…” – additional evidence of this is discussed above in the rejection of the independents
Claim 10 is rejected under a similar rationale as claim 9, also for the foreshortening and superimposing Liao et al., “3-D reconstruction of the coronary artery tree from multiple views of a rotational X-ray angiography”, 2010, as cited above, Introduction ¶ 1:”Traditionally, several angiographic views are taken from different angles and then are selected subjectively based on the cardiologist’s experience, to minimize foreshortening and vessel overlap”
Claim 11 is " a data gathering step that is limited to a particular data source (such as the Internet) or a particular type of data (such as power grid data or XML tags) could be considered to be both insignificant extra-solution activity and a field of use limitation. See, e.g., Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (limiting use of abstract idea to the Internet); Electric Power, 830 F.3d at 1354, 119 USPQ2d at 1742 (limiting application of abstract idea to power grid data); Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d 1315, 1328-29, 121 USPQ2d 1928, 1939 (Fed. Cir. 2017) (limiting use of abstract idea to use with XML tags)” as discussed in MPEP § 2106.05(h)” which is WURC in view of the evidence discussed above for the independent claims and claims 9-10, as well as page 9, ¶ 2: “The operations employ an imaging system capable of acquiring and processing two-dimensional images of a vessel organ (or portion thereof) or other object of interest. For example, a single plane 25 or bi-plane angiographic system can be used such as those manufactured, for example, by Siemens (Artis zee Biplane) or Philips (Allura Xper FD).”; then see page 19: “Another manner to minimize the effect of foreshortening and superimposing is by the use of a three-dimensional imaging modality such as from CT or MR.” and page 20: “The CT data can be registered by the processor to the two-dimensional Xray images that were used to create the 3D reconstruction as described in step 3011 of Fig. 3B. This can be done, for instance, by Markelj et al, "Robust Gradient-Based 3-D/2-D registration of CT and MR to X-ray images", IEEE Trans 5 Med Imaging 2008 27(121 ): 1704 -14.”
Claim 12 is considered as another step in both the mental process and another part of the math concept as math calculations/equations/relationships in textual form (see pages 20-21 as was discussed above to clarify, including: “At 3042, the processor adjusts the 1 D/0D model for the presence of collateral flow. Collateral flow is an important factor for the calculations because the blood flow may bypass the coronary lesion in the main artery and supply enough oxygenated blood to the tissue distal to the coronary lesion, making the stenosis less severe… In the case of collateral flow across the lesion from the same artery, the 1 D model is adjusted, for example, by adding one or more elements for the collateral flow parallel to the lesion in the 1 D model as illustrated in Fig. 10a… For example, extra OD elements can be added simulating the collateral flow as illustrated in Fig. 10b…” -e.g. a person adding a simple resistor/capacitor/inductor model, with a step of mere data gathering for use in the abstract idea, wherein the data gathering is considered WURC in view of page 21, ¶ 1: “generic velocity information based on one or multiple angiographic images by using densitometric and geometric information” – for more evidence, see:
Barfett, Joseph. Blood Velocity and Volumetric Flow Rate Calculated from Dynamic 4D CT Angiography using a Time of Flight Approach. Diss. 2014. See page 4, ¶ 2, then see § 1.5: “Delay in TOA of the bolus centroid between proximal and distal points in a pipe, vessel or other conduit can be used as a measure of average fluid velocity along the intraluminal pathlength (Shpilfoygel et al. 1999; Shpilfoygel et al. 2000) (Figure 1.6). This velocity, if multiplied by the cross sectional area of the conduit, may be used to calculate volumetric flow rate” – see figure 1.6 to clarify: “Basis of intraluminal fluid velocity calculation via the video densitometry approach. Intraluminal velocity may be measured by indicator dilution theory if we assume that the indicator is well mixed. Where a bolus is passing through a pipe, the delay in arrival of bolus centroid between proximal and distal regions in the pipe may be divided into the distance between the regions to obtain mean bulk velocity. Where recirculation effects are important, time to peak (TTP) may be used as a reasonable surrogate measure of bolus centroid. It is important that these regions be orthogonal to the pipe's central axis and that their border includes the entire pipe lumen” and page 29 ¶ 1
Willerson et al., “Coronary Artery Disease”, ISBN 978-1-4471-2827-4, 2015, see page 117, col. 1, ¶ 3
Reymond, Philippe, et al. "Validation of a patient-specific one-dimensional model of the systemic arterial tree." American Journal of Physiology-Heart and Circulatory Physiology 301.3 (2011): H1173-H1182. Page 1173, col. 2, last paragraph
Zhang et al., "Quantification of coronary microvascular resistance using angiography images for volumetric blood flow measurement: in vivo validation", 2011, page 2098, col. 1, ¶¶ 1-2
Claim 13 is further limiting the mere data gathering, and is considered WURC in view of the above discussed evidence
Claim 14 is rejected under a similar rationale as discussed above for claims 4 and 12-13, and the evidence discussed above at 2B for the independent claims and the noted dependent claims for its mere data gathering being conventional
Claim 15 is rejected under a similar rationale as above for the various “updating…” limitations (as being both part of the mental process and the math concept; see the above citations to the instant disclosure to clarify on the BRI including page 4: “In order to keep the computational demands on a feasible level a reduced model can be used in the calculation. That is, sections of the coronary tree can be represented by a one-dimensional network or zero-dimensional (lumped) model.”; page 15: “At the vessel ends of the coronary tree, lumped parameter models are applied. The initial values of these components can be determined using scaling laws as taught by Dindorf et al, "Modelling of pulsatory flows in blood vessels", 10 Acts of Bioengineering and Biomechanics, Vol. 3, No. 2, 2001…”, and pages 20-23), with an insignificant extra solution activity of mere data gathering that is WURC in view of the above discussed evidence for these elements that have been recited in similar forms
Claim 16 is further limiting both the mental process and math concept to using a circuit model for the cardiovascular network, wherein the Examiner further, to clarify on the BRI of this limitation, the 2B evidence above regarding the modeling using 0D models, i.e. it’s a routinely used manner of modelling lumped parameters, e.g. see Sinclair 2015 as discussed above, page 341: “0D models are also referred to as lumped parameter network (LPN) models, as they typically are used to represent the combined behavior of otherwise extensive vessel networks and their interaction with myocardial contraction. In the past, they have provided a valuable approach to understand the proposed mechanisms of cross talk, with LPN models representing the entire coronary tree.104–106 The commonly used Windkessel models are analogous to an electrical circuit incorporating resistive, capacitive, impedance, and inductive components which are representative of features of coronary flow…”
Claims 17-18 are rejected under a similar rationale as claim 16
Claim 19 is rejected under a similar rationale as claims 12-15, i.e. claim 19 is adding an equation to the math concept in the form of a 1D element, as well as a mental step of a mental judgement by the cardiologist, with a step of mere data gathering that is WURC in view of the above discussed evidence
Claim 20 is merely further limiting the mental process and math concept, and if not would be considered mere data gathering wherein this is WURC. Page 22 second to last paragraph: “For instance, patient height, weight, 25 gender, age and heart type are used to calculate a correction factor for components of the 1 D/0D models. This is done by the processor using methods well known in the art, for instance Clay et al, "Normal Range of human left ventricular volumes and mass using steady state free precession MRI in the radial long axis orientation", Magn Reson Mater Phy (2006) 19: 41-45.”
Claim 21 "a data gathering step that is limited to a particular data source (such as the Internet) or a particular type of data (such as power grid data or XML tags) could be considered to be both insignificant extra-solution activity and a field of use limitation. See, e.g., Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (limiting use of abstract idea to the Internet); Electric Power, 830 F.3d at 1354, 119 USPQ2d at 1742 (limiting application of abstract idea to power grid data); Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d 1315, 1328-29, 121 USPQ2d 1928, 1939 (Fed. Cir. 2017) (limiting use of abstract idea to use with XML tags)” as discussed in MPEP § 2106.05(h)” which is WURC in view of the evidence discussed above for claims 9-10, as well as page 9, ¶ 2: “The operations employ an imaging system capable of acquiring and processing two-dimensional images of a vessel organ (or portion thereof) or other object of interest. For example, a single plane 25 or bi-plane angiographic system can be used such as those manufactured, for example, by Siemens (Artis zee Biplane) or Philips (Allura Xper FD).”; - also, see the above evidence for the data gathering for the independents
Claim 22 is further limiting both the math concept and the mental process, by limiting to a “fitted equation…that calculates a pressure drop for a given flow value”, wherein this is merely limiting what equation is used in the math concept, and fitting an equation such as this is considered as a mental process akin to the example discussed above for claim 1 for the equation in claim 1 (i.e. a cardiologist using pen, paper, and a calculator, to fit a simple equation to a series of data points on a chart, such as fitting a line through the data pints)
As a point of clarity, the equation may be as simple as y=mx+b, or a form of this equation, or a linear regression which predates computers, e.g. ordinary least squares for fitting linear regressions was discovered by Carl Gauss (namesake of Gauss’s Law in electrical engineering and physics) well before the invention of digital computers and in routine use (see example 45, claim 1, prong 1, discussion of the history of the Arrhenius equation). Should evidence be required of this, the Examiner takes OFFICAL NOTICE of this historical fact.
Claim 23 is further limiting the mental process and math concept by specifying to use the “aortic pressure as an inlet boundary condition”. To clarify on the mental, in the coronary tree the aorta is the inlet for the entire tree – so in a simple model of the topmost vessels of the tree, it would have been a trivial mental task to judge to use the pressure at the aorta (i.e. the pressure of the inlet pipe of a series of pipes) as a boundary condition, and then the person would be able to solve a simple model using pen, paper, and a calculator, such as was discussed above for claim 1
Claims 24-25 are further limiting the math concept by adding another math calculation, wherein should this element be considered an additional element (for similar reasons as the limitation it further limits) it would be WURC in view of page 2, ¶¶ 3-4 including: “…Both the ESC and ACC/ AHA guidelines recommend the use of FFR…”, and additional evidence was discussed above for the independent claims
Claim 26 is further limiting the math calculation by “calculated directly”, and the “adjusting” is considered as a both a mental process step of mental judgements by a cardiologist and part of the math equations/relationships/calculations, when read in view of page 24, last paragraph: “Adjustment of the model for hyperemia can for example be done by changing the end-resistances using scaling factors”
To clarify on the BRI of hyperemia, this is a stress/non-rest state of the heart, e.g. the state of the heart to be measured during routine clinical stress tests (e.g. using a treadmill, having the patient walk/run on the treadmill, wherein the clinicians adjust the incline of the treadmill until the desired heart rate is reached; or by using “additional drug infusion (adenosine or papaverine) is required” as discussed on page 3 ¶ 1 of the instant disclosure). The act of “adjusting” in claim 26 is simply the act of adjusting values in the equations to simulate this state, wherein a cardiologist would readily be able to provide a mental judgement/opinion for this, e.g. an opinion based on their expertise as a cardiologist as to what occurs to a patient’s cardiovascular system in a hyperemia state
Claim 27 is mere instructions to use a computer to implement the abstract idea/apply the abstract idea on a computer for the “wherein the region of interest is identified automatically or semi-automatically…” – i.e. pages 15-16, paragraph split between the pages: “This can be done manually, upon user input… a user can indicate a region of interest”, wherein this is akin to “ii. Accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer, FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016); iii. Mere automation of manual processes, such as using a generic computer to process an application for financing a purchase, Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 (Fed. Cir. 2017) or speeding up a loan-application process by enabling borrowers to avoid physically going to or calling each lender and filling out a loan application, LendingTree, LLC v. Zillow, Inc., 656 Fed. App'x 991, 996-97 (Fed. Cir. 2016) (non-precedential);” as discussed in MPEP § 2106.05(a)(I); and akin to “"claiming the improved speed or efficiency inherent with applying the abstract idea on a computer" does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015).” As discussed in MPEP § 2106.05(f)
Claim 28 is further limiting the math concept of math calculations in textual form when read in view of page 5, (c): “making calculations based on the 3D reconstruction to determine geometrical features of the conduits such as diameters, lengths, 30 curvatures, centrelines, or the like;” and page 11, ¶ 1: “At 1212 the data processing module 114 makes calculations based on the 3D reconstruction to determine geometrical features of the conduits such as diameters, lengths, curvatures, centrelines, or the like.”, wherein should this be found not to be math calculations in textual form then the Examiner submits that this would be "a data gathering step that is limited to a particular data source (such as the Internet) or a particular type of data (such as power grid data or XML tags) could be considered to be both insignificant extra-solution activity and a field of use limitation. See, e.g., Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (limiting use of abstract idea to the Internet); Electric Power, 830 F.3d at 1354, 119 USPQ2d at 1742 (limiting application of abstract idea to power grid data); Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d 1315, 1328-29, 121 USPQ2d 1928, 1939 (Fed. Cir. 2017) (limiting use of abstract idea to use with XML tags)” as discussed in MPEP § 2106.05(h)” which is WURC in view of the above discussed evidence for the modeling/generating in 3D
Claim 29 is rejected under similar rationales as were discussed above for similar limitations, i.e. this is a simple mental judgment by a cardiologist to start with a textbook model/standard model, and then make mental judgments to adjust values in the model to reflect patient specific data, e.g. the diameters of vessels, based on mentally observed values (such as gathered from routine clinical tests as discussed above, and evidenced at 2B), and part of the math concept as this is adjusting values in the math equations/relationships for use in the later calculations (Page 18: “To make the calculations even more accurate, the 1D/0D model can be adjusted to make it even more patient specific”)
Claim 30 is part of the math calculations for the generation of the reduced 3D model (which is a math equation), and if not then its just mere data gathering that is WURC – see page 17, ¶¶ 3-4: “Optionally, another way for reducing more computation time is to determine the pressure-flow relation based on geometric features of the 3D reconstruction as taught by Schrauwen et al, "Fast and Accurate Pressure-Drop Prediction in Straightened Atherosclerotic Coronary Arteries", Annals of 15 Biomedical Engineering, 2014. A model can be created using features from the 3D geometry like minimum diameter, diameter changes and curvature. The outcome of this operation performed by the processor is a fitted equation for the segment of interest that calculates a pressure drop for a given flow value.” – and page 5, (c): “making calculations based on the 3D reconstruction to determine geometrical features of the conduits such as diameters, lengths, 30 curvatures, centrelines, or the like;” and page 11, ¶ 1: “At 1212 the data processing module 114 makes calculations based on the 3D reconstruction to determine geometrical features of the conduits such as diameters, lengths, curvatures, centrelines, or the like.” - see the other evidence above as well (to clarify, merely using the work of another in its ordinary capacity is not an inventive concept)
Claim 32 is considered as generally linking to a particular technological environment of an X-ray imaging system, as well as part of the mere data gathering as its merely specifying the source of the data, wherein this ss WURC (page 1, last paragraph: “At the moment X-ray angiography is the standard technique for anatomical assessment of the coronary arteries and the diagnosis of coronary artery disease. During X-ray angiography several different two-dimensional images (also called bi-dimensional images), also called two-dimensional projections (also 30 called bi-dimensional projections), of the object under examination can be obtained from different views or perspectives by rotating the arm, holding the Xray source and the image intensifier, with reference to the patient.” – also, page 9: “The operations employ an imaging system capable of acquiring and processing two-dimensional images of a vessel organ (or portion thereof) or other object of interest. For example, a single plane 25 or bi-plane angiographic system can be used such as those manufactured, for example, by Siemens (Artis zee Biplane) or Philips (Allura Xper FD).”
The recitation of “to determine at least one fractional flow reserve…” is considered under two different claim interpretations in view of the disclosure – 1) as an insignificant extra-solution activity of mere data gathering as well as a step with a nominal/tangential link to the primary process of the claimed invention, wherein it is WURC in view of pages 3-4 including: “…Both the ESC and ACC/ AHA guidelines recommend the use of FFR…” and the evidence as discussed above– to clarify, this is under the interpretation that the FFR is determined by the measurement methodology discussed as being “used increasing over the last 10-15 years”/in the “guidelines” for the industry; and 2) as a math calculation in textual form when read in view of page 23: “vFFR calculations” and page 24: “At 307 the processor calculates the vFFR”
To further clarify, the Examiner is noting these two interpretations are both under the BRI, as the claim does not specify that the quantitative flow analysis is to determine the FFR in claim 32, thus it is not limited to doing it by calculation, but rather it may also be a mere result gathering from conventional data gathering techniques as known in the art
Claim 33 is considered as part of the mere data gathering, wherein this is WURC in view of Jarisch, "Myocardial Perfusion Evaluation Using Only Six Projections", 2012, § 1 and §§ 4.2-4.3; further see fig. 4.1, also see the evidence discussed above for claims 11-12, and as a further point of clarity see page 21 for its “Siemens (Artis zee Biplane) or Philips (Allura Xper FD),” as being examples of a biplane imaging system, as well as Liao et al., “3-D reconstruction of the coronary artery tree from multiple views of a rotational X-ray angiography”, 2010 introduction, ¶ 1: “Traditionally, several angiographic views are taken from different angles and then are selected subjectively based on the cardiologist’s experience, to minimize foreshortening and vessel overlap.”, and in ¶ 2: “In [15, 16], the 3-D symbolic reconstruction was utilized for cardiac and/or breathing motion estimation and subsequent compensation throughout the rotational sequence before tomographic reconstruction was applied.”, and page 734 last paragraph: “3-D centerline reconstruction and subsequent tomographic reconstruction of the coronary artery tree using multiple projections of a single rotational X-ray angiography was proposed in [17].”, and page 735, col. 1, ¶ 3: “A rotational X-ray sequence is acquired by rotating the C-arm with a constant source to intensifier distance, a constant cranio/caudal angle (CRAN/CAUD), and a varying left/right anterior oblique angle (LAO/RAO).” – also see
Schrijver, M. "Angiographic assessment of coronary stenoses: A review of the techniques." Archives of physiology and biochemistry 111.2 (2003): 77-158. §§ 17.2.1-17.2.2
Claim 34 is part of the mere instructions to apply a generic computer and generic computer components as a tool to perform the abstract idea, wherein these components are generically described on page 7: “The computer product can also be uploaded to a cloud or high-performance computing cluster to improve computation time.” – wherein the disclosure conveys that the benefit is merely akin to “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer" does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015).” (MPEP § 2106.05(f)) – to clarify, claim 34 is merely claiming, in a generic manner, to use a faster computer to make the calculations faster, with no recitations on any particular technological implementation of how the claimed method is applied to “a cloud or high-performance computing cluster” (i.e. these are simply being used as tools)- the Examiner also notes that the omission of any particular details of cloud computing or high performance computing clusters conveys, by the omission, that these are WURC in the field of use as a specification preferably omits what is well-known
Claim 35 is mere data gathering with generic computer components (“an input device”, page 10, ¶ 1: “The user interface module 116 can include different kinds of input and output devices, such as a display screen for visual output, a touch screen for touch input, a mouse pointer or other pointing device for input, a microphone for speech input, a speaker for audio output, a keyboard and/or keypad for input, etc.” – i.e. generic input devices) being used in their ordinary capacity for the mere data gathering , wherein this is WURC in view of “iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining "shadow accounts"); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log);… vi. A Web browser’s back and forward button functionality, Internet Patent Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015)… i. Recording a customer’s order, Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1244, 120 USPQ2d 1844, 1856 (Fed. Cir. 2016);” as discussed in MPEP § 2106.05(d)
The claimed invention is directed towards an abstract idea of both a mathematical concept and a mental process without significantly more.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-2, 5-6, 8, 20-32, and 35 is/are rejected under 35 U.S.C. 103 as being unpatentable over Larrabide, Ignacio, et al. "HeMoLab–Hemodynamics Modelling Laboratory: An application for modelling the human cardiovascular system." Computers in biology and medicine 42.10 (2012): 993-1004 in view of Sharma et al., US 2013/0132054 and in further view of Schrauwen, J. T. C., et al. "Geometry-based pressure drop prediction in mildly diseased human coronary arteries." Journal of biomechanics 47.8 (2014): 1810-1815.
The rejections below in part rely on a term in the prior art has its plain meaning explained (MPEP § 2131.01) in view of the United States NIH National Cancer Institute, Dictionary of Cancer Terms, definition of “angiography”, URL: cancer(dot)gov/publications/dictionaries/cancer-terms/def/angiography, specifically: “A procedure to x-ray blood vessels. The blood vessels can be seen because of an injection of a dye that shows up in the x-ray.”, accessed Nov. 2025.
Also, another term “Inertance” has its meaning explained in view of Southern Illinois University, Lesson 6: Mathematical Models of Fluid Flow Components, ET 438, Automatic Control Systems Technology, Aug. 2015, URL: engr(dot)siu(dot)edu/staff/spezia/Web438A/Lecture%20Notes/lesson6et438a(dot)pdf – slide 20: “Amount of pressure drop required to increase flow rate by one unit/second. Analogy-electrical inductance.”
Regarding Claim 1
Larrabide teaches:
A computer-implemented method for quantitative flow analysis of a tree of conduits perfusing an organ of a patient from a plurality of two bi-dimensional images of at least part of the tree obtained from different perspectives, the method comprising: (Larrabide, abstract, and see fig. 5 and §§ 4.2-4.3 as discussed in detail below, including figures 4-5 which show a plurality (fig. 4, there are at least 3 images, as each plane is a bi-dimensional image) of 2d images (fig. 5 a-c)
a) generating a one-dimensional (1D) model that is specific to the patient, wherein the 1D model includes a plurality of segments representing conduits of at least part of the tree of the patient, wherein fluid flow through the segments of the 1D model is governed by a one-dimensional, ….fluid equations; (Larrabide, abstract, then see § 1 last two paragraphs, then see § 2.1 and figure 1(a) which discusses a “1-D model of the arterial tree”, incl: “The propagation of the cardiac pulse in the arterial network can be accurately represented through 1D–0D mathematical models which describe the behavior of the flow rate, mean pressure and lumen area and as a function of time throughout the systemic network (see references cited in Section 1)…” -and see the equations
then see § 3: “1D–0D tree creation/edition/visualization: edition and creation of a 1D model of the arterial tree, including changes in its geometrical and topological definition as well as the definition of the material properties corresponding to the wall tissue, and incorporating 0D terminal elements for modeling outflow boundary conditions.”, e.g. see figure 3 for an example of steps in the editing of an existing 1D model wherein this creates a “new 1D model” after having first generated an initial 1D model by reading in the files and generating it (the “1D model” depicted after the model reader); also see figure 2 as well, and § 4.1 including: “This pre-processing encompasses the configuration of a 1D arterial tree (or a sub-system of it) by creating and editing 1D arterial segments, setting the mechanical and geometrical parameters associated to each segment. It also allows setting the parameters related to the peripheral beds modeled as 0D elements.” As well as the accompanying descriptions of figures 2-3
b) generating a three-dimensional (3D) reconstruction for a subset of the tree of the patient; c) identifying a region of interest …d) using the 3D reconstruction to construct a volumetric mesh for the subset of the tree of the patient corresponding to the region of interest; (Larrabide, § 2.2, including: “To capture all the complexity of blood flow in a given arterial vessel it is necessary to perform a numerical approximation of the 3D Navier–Stokes equations (see references cited in Section 1). Such models are capable of retrieving all the complexity of blood flow in the 3D Euclidian space …In order to perform a 3D simulation we need to define the Euclidian space of our concern. Either this space is obtained from combination of basic geometrical entities or defined from the identification of anatomical structures in medical images, it is required to deal with a very large amount of data that defines completely a tetrahedralization [meshing into tetrahederal volume elements] of this spatial domain. The manipulation of this tetrahedralization and the entire data structure is one of the most expensive pre-processing stages when modeling the HCVS. The number of parameters that describe a mesh may reach up to 107… Moreover, in the case this spatial domain is obtained from medical images, we have an additional cost that is the image processing stage” – and see figure 1(b): “In (b) a schematic representation of coupling between a 1D model of the arterial tree and a 3D model of the iliac bifurcation with a fusiform aortic aneurism [example of a diseased vessel having been identified] is presented.”
Then see § 3 including: “Medical image processing: enhancement and segmentation of medical images in order to extract patient-specific geometrical models, together with visualization and geometry definition for the posterior simulation… 3D geometry edition/visualization/mesh generation: edition of 3D surfaces represented by triangular meshes and construction of tetrahedral meshes (volume filling), setting of boundary conditions and modification of geometry for the simulation of surgical procedures or pathological situations…”
To further clarify, see figure 4 as discussed in § 4.2 wherein fig. 4 shows “Illustrative sequence of the process of image segmentation and geometry acquisition from medical images” and in § 4.2 see the entire section, including: “With this in mind, the hmImageProcessing was developed to provide tools for processing medical images. This module is closely related to the hm3DModule module since it provides the input surface to build 3D models (see Section 4.3).” – then see figures 6-7, and their accompanying descriptions within §§ 4.2-4.3 – in particular note that it’s a 3D re-construction (fig. 5 from 2D images (shown in a-c) and in figure 4 the final step is generating and processing the surfaces with “Gemesis3D”
See § 4.3 to further clarify: “Modelling in detail the blood flow behavior implies dealing with complex arterial geometries (e.g., obtained from medical images). An initial surface is the starting point for this module in which we have two main steps: (i) the mesh generation and optimization of the initial surface/volume meshes (see Section 4.5) and (ii) the setting of appropriate boundary conditions…”
See § 4.5 to clarify on the mesh generation of including of “3D volume meshes”
also in § 5.3 note in ¶ 4: “The evaluation method used in the course was based on a series of reports based on numerical simulations in which the students had to perform modifications in the model and simulate different situations that may occur, such as the effects of aging, vasodilation, vasoconstriction, at-rest and exercise [hyperemia] regimes, influence of constitutive models (elastin and collagen composition) of the arterial walls, calculation of the characteristic impedance of the arterial network, among others”
e) using the volumetric mesh of d) in conjunction with computational fluid dynamic simulations to generate a …three-dimensional (3D) model for the region of interest; f) adding the … 3D model to the 1D model of a) as a coupling condition at the position in the 1 D model identified in c) to generate a coupled model; and g) performing quantitative flow analysis using the coupled model of f). (Larrabide, as discussed above, including §§ 4.1-3, then see § 4.4 and fig. 8-9, along with this accompanying descriptions, which describe the coupling of the existing 3D-1D-0D models, following by simulations using the coupled models, followed by a “Visualization” of the results, and § 4.6 clarifies on the numerical solver, and § 4.7 discusses figure 10 and visualizations from the results of the quantitive flow analysis
for more clarification, see figure 11 right-hand side as discussed in § 5
The subsections of § 5 provide further clarity, e.g. § 5.1 discusses modeling a “kidney transplantation” operation by altering the 1D-0D model, § 5.2 discusses an example with a coupled 3D-1D-0D model from MRI images as shown in fig. 14, also in § 5.3 note in ¶ 4: “The evaluation method used in the course was based on a series of reports based on numerical simulations in which the students had to perform modifications in the model and simulate different situations that may occur, such as the effects of aging, vasodilation, vasoconstriction, at-rest and exercise regimes, influence of constitutive models (elastin and collagen composition) of the arterial walls, calculation of the characteristic impedance of the arterial network, among others”
While Larrabide does not explicitly teach the following, Larrabide in view of Sharma teaches:
…axisymmetric form of… (Sharma, abstract and fig. 3, including its accompanying description, including ¶ 38: “The ID models 304-320 use a series of simplifying assumptions in order to convert a 3D domain into a ID domain along the length of the longitudinal axes. Such 1D models can be described by a system of quasilinear first order partial differential equations….Hence, when blood vessel anatomy is regular (e.g., cylindrical [example of axi-symmetrical shape, see page 4 ¶ 3 to clarify on the BRI]) and there is no need for computing local values like wall shear stress or oscillatory shear index, such 1D models can be used in order to reduce the computational time but also to study the wave propagation phenomena. These ID models are used both before and after the stenotic segments, thus allowing a detailed spatial pressure and flow rate distribution in the whole coronary arterial tree to be determined. Further, the 1D models (which contain non-linear terms) can be linearized and exact analytic solutions can be obtained in the frequency domain
within the 3D reconstruction which corresponds to a stenotic vessel segment belonging to the plurality of segments of the 1D model, wherein the stenotic vessel segment has a narrowing or blockage of flow; (Larrabide, as cited above for the 3D reconstruction and identifying steps, wherein Larrabide performed the identification during the generation of the 3D reconstruction, and only reconstructed the part of the tree identified
in view of Sharma, ¶ 27: “At step 204, a patient-specific anatomical model of the coronary arteries and the heart is generated from the medical image data. In an advantageous implementation, the patient-specific anatomical model includes a 4D (3D +time) a geometric model of the coronary arteries generated using the 4D medical image data. In order to generate the patient specific anatomical model of the coronary arteries, the coronary arteries are segmented in each frame of the 4D image data. The coronary arteries can be segmented in each frame of the medical image data using any coronary artery segmentation method. For example, the coronary arteries can be segmented in a CT volume using the method described United States Published Patent Application No. 2010/0067760, which is incorporated herein by reference. A geometric surface model is then generated for the segmented coronary arteries of interest in each frame.” – see ¶ 28 to further clarify
then see ¶¶ 29-30, including: “Accordingly, in an advantageous embodiment of the present invention, only local regions of interest inside the coronary arterial tree, e.g., segments which contain narrowing plaque deposits are segmented using full 3D models, while the rest of the circulation is represented through reduced-order models (1D models for the large arteries and lumped models for the small arteries and micro vasculature).” – to clarify, ¶ 54: “In order to extract the coronary anatomy from the medical images, embodiments of the present invention can utilize existing coronary segmentation and centerline extraction algorithms. Such algorithms readily provide the coronary vessel centerline tree, together with a surface representation including the stenosis narrowing, which is then used for extracting the required anatomical data for the 3D and 1D computations. For example, the percent blockage of a stenosis can be detected and used to construct the 3D model of the stenosis region.” And ¶ 55, further see fig. 8 – in other words, this does a 3D reconstruction of the coronary arteries, and then automatically identifies where the stenosis is for the region of interest to be simulated with the 3D CFD model
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings from Larrabide on a system for simulating arterial trees including with a 3D-1D-0D model with the teachings from Sharma on a similar such system, but “for multi-scale anatomical and functional modeling of coronary circulation is disclosed” The motivation to combine would have been that “The functional importance of coronary artery disease cannot be determined merely by observing the narrowing of the blood vessels and is related to different blood flow properties like flow rate and pressure. Current clinical practice involves invasive measurements for the proper evaluation of these quantities. In advantageous embodiments of the present invention, the risks associated with these interventions can be avoided by first acquiring detailed information on the geometry of coronary arterial trees through different imaging techniques and then by performing blood flow computations on models representing the patient-specific geometry. Further these models not only allow one to avoid invasive measurements, but also to improve treatment plans by simulating different scenarios (angioplasty, stenting, bypass procedures) and hence to improve patient outcome” (Sharma, ¶ 20)
Additional motivations to combine include: “In an advantageous embodiment, the patient-specific anatomical model also includes a patient-specific 4D anatomical model of the heart that is generated from the 4D image data. The 4D anatomical heart model is a multi-component model having multiple cardiac components, including as the chambers (left ventricle, left atrium, right ventricle, and right atrium), the heart valves (aortic valve, mitral valve, tricuspid valve, and pulmonary valve), and the aorta. Such a comprehensive model of the heart is used to capture a large variety of morphological, functional, and pathological variations. A modular and hierarchical approach can be used to reduce anatomical complexity and facilitate an effective and flexible estimation of individual anatomies.” (Sharma, ¶ 28) and ¶ 30: “Reduced-order models produce reliable results in terms of pressure and flow rate waveforms (1D models), correctly take into account the effect of distal vessels and of the microvasculature (lumped models), and lead to execution times which are more than two orders of magnitude smaller than the corresponding 3D computations”, also see ¶ 38: “An advantageous aspect of these models is the fact they take into consideration the compliance of the vessels, which allows for the description of wave phenomena which appear in the cardiovascular system… 1D models can for example be used to study the effect of geometric tapering or local stiffening of an artery on the propagation of flow rate and pressure waves. ID models are very useful when determining the characteristics of the flow rate and pressure waves inside the cardio-vascular system. These waves are generated by the interaction between the blood flow and the vessel walls, which have certain compliance, and depend on the elastic characteristics of the vessels… ID models can be used in order to reduce the computational time but also to study the wave propagation phenomena… Further, the ID models (which contain non-linear terms) can be linearized and exact analytic solutions can be obtained in the frequency domain. This way a structured tree model 321 can be obtained for the distal part of the arterial tree, which can be then lumped into impedance and applied as boundary condition at the outlet of the non-linear ID model….”
While Larrabide in view of Sharma does not explicitly teach the following, Larrabide in view of Sharma and further view of Schrauwen teaches:
reduced, wherein the reduced 3D model consists of a pressure drop equation for the region of interest (Larrabide, as discussed above, including for the coupled model with a full-order 3D CFD simulation, in view of Schrauwen, abstract, then see § 2 including §§ 2.1-2.3, then see § 2.4 which discusses modeling the “pressure drop” by “fitting” to the “CFD result[s]” – see the section in full for more details, including the equations for the pressure drop
for relevancy see § 2.5 last paragraph for its discussion of “FFR”, and fig. 5
to further clarify, see the abstract: “The effect of the geometric features was determined and the pressure drop in mildly diseased human coronary arteries was predicted quickly based solely on geometry. This pressure drop estimation could serve as a boundary condition in CFD to model the impact of distal epicardial vessels”, then see § 1 ¶ 2: “To reduce the computational time CFD can be restricted to a 3D region of interest, e.g. a coronary bifurcation containing an atherosclerotic plaque. Appropriate boundary conditions should be defined to replace the proximal and distal regions… To reduce the computational time CFD can be restricted to a 3D region of interest, e.g. a coronary bifurcation containing an atherosclerotic plaque. Appropriate boundary conditions should be defined to replace the proximal and distal regions.” And page 1811 col. 1, ¶¶ 2- 4: “…With an image based estimate of the pressure drop in a stenosed vessel it is also possible to calculate the FFR instead of measuring it…The image based pressure drop was primarily investigated as a potential boundary condition in CFD, but is in this study it was also applied to predict FFR.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings from Larrabide on a system for simulating arterial trees including with a 3D-1D-0D model with the teachings from Schrauwen on using 3D CFD simulations to fit a reduced 3D model in the form of a pressure drop equation. The motivation to combine would have been that “A high correlation was found between FFRCFD and FFRestimation. Despite the observed discrepancy between computed and estimated pressure drop the relatively high arterial pressure leads to a very good FFR prediction… Whether or not a simpler and faster approach to estimate FFR on imaging data alone can also give valuable results, depends on how well the pressure drop predictions perform in more stenosed segments with lower FFR values. In future studies the clinical relevance of the current findings should be assessed by including more heavily diseased coronary arteries, as well as comparing the predicted FFR to in vivo measurements.” Schrauwen, § 4 second to last paragraph as well as “On average the predicted pressure drop shows good agreement with the computed pressure drop. The image-based pressure drop estimation can be used for quick determination of boundary conditions, paving the way to assess WSS in a clinical setting.” (last page, last paragraph), also see the abstract: “The effect of the geometric features was determined and the pressure drop in mildly diseased human coronary arteries was predicted quickly based solely on geometry. This pressure drop estimation could serve as a boundary condition in CFD to model the impact of distal epicardial vessels.” – also, page 1811, col. 2, ¶¶ 2-4: “Real time image based pressure drop estimation in stenosed epicardial vessels can also be useful to determine the fractional flow reserve (FFR). FFR is an important indicator for the hemodynamic significance of a coronary stenosis (Pijls et al., 1996). It is defined as the pressure drop over the stenosis for minimal myocardial resistance. Treatment of the stenosis is warranted if the FFR is below 0.8 (Tonino et al., 2010). During an intervention the FFR is measured with a pressure catheter. With an image based estimate of the pressure drop in a stenosed vessel it is also possible to calculate the FFR instead of measuring it… The image based pressure drop was primarily investigated as a potential boundary condition in CFD, but is in this study it was also applied to predict FFR.”
Regarding Claim 2
The above relied upon prior art teaches:
The method according to claim 1, wherein the coupled model comprises multiple segments identifying the conduits forming the tree, such segments being associated to 1 D segments in the coupled model with end parts connected with lumped parameter models to take into account boundary conditions. (Larrabide, as cited above, as taken in view of Sharma for the 1D, including Larrabide §§ 2.1-2.2 in view of Sharma, fig. 3, as cited above)
Regarding Claim 5
The above relied upon prior art teaches:
The method according to claim 1, wherein the 1D model of a) is based on a standard 1D model that is adjusted based on geometric features extracted from the 3D reconstruction. (Larrabide, § 4.1, ¶¶ 1-2, and fig. 3, as were discussed above, wherein this is “by creating and editing…” and the editing is calibrating the model, i.e. “setting the mechanical and geometrical parameters associated to each segment. It also allows setting the parameters related to the peripheral beds modeled as 0D elements.” – fig. 3, the “new 1D model” was based on the standard “1D model” from the “files”, but also calibrated/edited by having its “mechanic and geometric properties” adjusted
Then see § 5.2 scenario 3: “In this case, the 3D arterial geometry is processed using modules hmImageProcessing and hm3DModule, and then the hm1DModule is employed to set up the 1D arterial network in which the 3D model will be embedded. Then, both data sets are combined using the hmCoupling module and the simulation is carried out.”; and see § 5.2 ¶ 2: “The 3D model is embedded in a 1D–0D model, as seen in Fig. 14(b) which gives a schematic representation of the problem. The calibration of this [i.e. the coupled] model is done such that is reproduces physiological results.”
As taken in view of Sharma, ¶¶ 27-28 as cited above, wherein the reconstruction was for the entire heart coronary tree, instead of just the vessel of interest
POSITA would have been suggested, in such a combination, to have edited/adjusted the geometrical parameters corresponding to each segment (Larrabide, as cited above) with the 3D geometrical properties extracted from the 3D/4D ”geometric model” of Sharma (¶¶ 27-28 of Sharma) as “This results in an anatomical model of the coronary arteries that shows the anatomy of the coronary arteries changing over time…. Such a comprehensive model of the heart is used to capture a large variety of morphological, functional, and pathological variations. A modular and hierarchical approach can be used to reduce anatomical complexity and facilitate an effective and flexible estimation of individual anatomies”, or
Or they would have at least found it obvious to do so because Larrabide already suggests at least § 5.1 ¶ 3: “Certainly, more accurate calibrations of the arterial tree using information provided by complementary measurements [e.g. Sharma ¶¶ 27-28] would help to improve the quality of the results” and in § 2.3: “Thus, it can be seen that due to the heterogeneous nature of the models involved in the 3D–1D–0D setting, it is necessary to handle quite heterogeneous data, that is data associated to the arterial tree (the whole set of vessels and terminals) and to the specific vessels (eventually incorporating patient-specific information from medical images).” – then see Sharma ¶ 20: “The functional importance of coronary artery disease cannot be determined merely by observing the narrowing of the blood vessels and is related to different blood flow properties like flow rate and pressure. Current clinical practice involves invasive measurements for the proper evaluation of these quantities. In advantageous embodiments of the present invention, the risks associated with these interventions can be avoided by first acquiring detailed information on the geometry of coronary arterial trees through different imaging techniques and then by performing blood flow computations on models representing the patient-specific geometry. Further these models not only allow one to avoid invasive measurements, but also to improve treatment plans by simulating different scenarios (angioplasty, stenting, bypass procedures) and hence to improve patient outcome”
Regarding Claim 6
The above relied upon prior art teaches:
The method according to claim 1, wherein the 1 D model of a) is based on a standard 1D model that is adjusted based on patient-specific data available from an imaging modality, wherein the patient-specific data comprises at least one feature selected from the group consisting of skeleton, diameters, vessel length, vessel curvature, and bifurcation angles. (See the above discussion for claim 5, this claim is rejected under a similar rationale, see Larrabide, § 3 to further clarify: “edition and creation of a 1D model of the arterial tree, including changes in its geometrical and topological [skeleton] definition as well as the definition of the material properties corresponding to the wall tissue, and incorporating 0D terminal elements for modeling outflow boundary conditions.” - and note, in the figure 2(a-b), it is visually depicted that the tree was initially created from the standard model, and edited, including adding new vessels with this associated geometry, including as visually depicted bifurcation angles
In view of Sharma, ¶ 38 to further clarify, including: “The ID models 304-320 use a series of simplifying assumptions in order to convert a 3D domain into a ID domain along the length of the longitudinal axes… There are various approach possibilities regarding these models. In the simplest case, the mechanical properties of the blood vessel are described by an algebraic relation between average pressure and the radius of the vessel… In an advantageous embodiment of the present invention, the relationship between pressure and vessel radius is given by a differential equation” – radius is an example of diameter
Regarding Claim 8
The above relied upon prior art teaches:
The method according to claim 1, further comprising updating the coupled model to take into account status of the myocardium microvasculature. (Larrabide in view of Sharma, as discussed above for claims 1, 5-6, including Larrabide § 3 and fig. 2 as discussed above for editing the skeleton/topology of the tree after the initial creation from the files
Taken in further view of Sharma for the vessel of interest being a stenosis portion of the coronary tree of the heart, and ¶ 44 of Sharma “…An important aspect which influences the coronary flow in general and the autoregulation phenomenon in particular is the presence of collateral flow. These vessels, also called anastomotic channels, develop in the heart as an adaption to ischemia. They serve as conduit segments which bridge severe stenoses or connect a territory supplied by one epicardial coronary artery with that of another. Hence, collateral vessels represent an alternative source of blood supply to a certain part of the myocardium which is affected by coronary artery disease, and they can help to preserve myocardial function…” – and see fig. 3 for “Collaterial Flow” # 336 in ¶ 32: “One further aspect which is very important in the coronary circulation, and which contributes to the large discordance between morphological and functional importance of a stenosis is the presence of collateral flow which can render a morphologically important stenosis into a functionally insignificant one. Depending on the patient specific vessel morphology, the collateral flow 336 can be modeled both through anastomotic large vessels (with 1D models) or through microvascular vessels which supply the affected region with blood (modeled through lumped elements as in FIG. 3).”
To clarify on the BRI, see pages 20-21 of the instant disclosure
POSITA would have been motivated for similar reasons as discussed above, and because collateral flow is such of an “important aspect” for evaluating stenosis as discussed by Sharma as cited above
Regarding Claim 20.
The above relied upon prior art teaches:
The method according to claim 1, further comprising using at least one further parameter to update the coupled model, wherein the at least one further parameter is selected from the group consisting of: wall motion of the left ventricle, coronary motion, information on the patient such as height, weight, gender, age, blood pressure. (Larrabide in view of Sharma, as discussed above for claims 1, 5-6, including Larrabide § 3 and fig. 2 for the updating,
In view of Sharma, ¶ 27: “At step 204, a patient-specific anatomical model of the coronary arteries and the heart is generated from the medical image data. In an advantageous implementation, the patient-specific anatomical model includes a 4D (3D +time) a geometric model of the coronary arteries generated using the 4D medical image data…A geometric surface model is then generated for the segmented coronary arteries of interest in each frame…This results in an anatomical model of the coronary arteries that shows the anatomy of the coronary arteries changing over time.” – POSITA would have inferred the patient was alive and had a beating/moving heart for such imaging
for a second example see Sharma¶ 50: “Recent developments in real-time full volume echocardiography create the opportunity to recover full 3D myocardial motion as well as volumetric color Doppler information. Dense myocardial motion provides critical information
for personalization of the heart model, as well as in the study of moving coronary vessels. Multiple information sources, such as speckle patterns, image gradients, boundary detection, and motion prediction can be fused to achieve a fast and robust detection and dense tracking of the heart anatomy on 3D+t ultrasound data. Such echo-based estimated motion and mechanical parameters of the myocardium are sufficiently close to ground truth values. In an advantageous implementation, the availability of volumetric color Doppler velocity enables fast and non-invasive recovery of patient specific blood flow information, which can be used as boundary conditions for subsequent CFD computations” – POSITA would have been motivated in view of ¶ 50 of Sharma: “Dense myocardial motion provides critical information
for personalization of the heart model”
also, see Sharma, ¶ 49: “In an advantageous embodiment of the present invention, reduced-order heart models are extracted from full-order anatomical and hemodynamic models of the heart, and efficiently coupled them with the coronary circulation
models... In particular, patient-specific advanced models of the heart morphology, dynamics, and hemodynamics generated from the received medical image data can be integrated…The models are highly modular and can be customized depending on the application, and include anatomy and dynamics of the left and right ventricles, left and right atria, aorta, aortic valve, mitral valve, tricuspid valve, pulmonary valve and trunk, pulmonary veins, and superior/inferior vena cava. Advanced morphological and dynamical parameters are readily available and can be used to study the coupled function of the heart”
Regarding Claim 21.
Larrabide, in view of Schrauwen and Sharma, teaches:
The method according to claim 1, wherein the plurality of bi-dimensional images comprises X-ray angio-images taken from at least one perspective. (Larrabide, as cited above, wherein the one example imaging technique in § 5.2 explicitly discussed was “MRI” and fig. 4 for the “Medical image reader” as clarified on in § 4.2
As taken in view of Sharma, ¶ 26: “For example, the medical image data can include, computed tomography (CT), Dyna CT, magnetic resonance (MR), Angiography, Ultrasound, Single Photon Emission computed Tomography (SPECT), and any other type of medical imaging modality. The medical image data can be 2D, 3D or 4D (3D+time) medical image data. The medical image data can be received directly from one or more image acquisition devices, such as a CT scanner, MR scanner, Angiography scanner, Ultrasound device, etc., or the medical
image data may be received by loading previously stored medical image data for a patient” - wherein, per the definition noted above, angiography is an x-ray imaging technique
POSITA would have been further motivated (see the motivations above for the combination) to do this combination, because Sharma’s imaging technique, in combination with Sharma’s reconstruction technique (¶¶ 27-28 relied upon above), would have improved the variety of different imaging modalities that may be used in this system, allowing doctors to use the imaging device they have easiest access to (or the one that insurance most readily pays for/tells the doctor to use first).
Regarding Claim 22.
The above relied upon prior art teaches:
The method according to claim 1, wherein the pressure drop equation of the reduced 3D model is a fitted equation for the region of interest that calculates a pressure drop for a given flow value. (Larrabide, as was taken in view of Schrauwen as cited above for claim 1 for this feature)
Regarding Claim 23.
The above relied upon prior art teaches:
The method according to claim 1, wherein the quantitative flow analysis of g) solves the coupled model using aortic pressure as an inlet boundary condition. (Larrabide, in view of Sharma, as discussed above for claim 1, wherein Sharma ¶ 36: “No-slip boundary conditions are enforced at the vessel walls and the inflow and outflow boundary conditions are determined by an explicit/implicit coupling with the proximal and distal ID segments.”
then Sharma, ¶ 56: “The computations for the ID models (e.g., for the coronary arteries and the aorta) compute the bulk flow rate going through the particular coronary branch (or aorta).” And ¶ 31: “The aorta and the large arteries (e.g., the left coronary artery (LCA), right coronary artery (RCA), etc.) are represented as ID blood flow models 304,306,308,310,312,314, 316,318, and 320 since these ID blood flow models 304-318 produce reliable results in terms of pressure and flow rate values and take into account wave propagation phenomena.”
Then, see ¶ 41: “There are various possibilities which can be used to assure a proper coupling of the models: the so-called "do-nothing" approach (typically used for pressure boundary conditions) and the "Lagrange multiplier" approach (typically used for velocity flow rate boundary conditions). By coupling the models, the global and the local behavior of blood can be determined, as well as the reciprocal influence between the local and global model.”
POSITA would have found this limitation suggested, or at least obvious in view of what is suggested in the above citations, specifically, ¶ 36 specifies that there are inflow/outflow boundary conditions for the 3D model (the region with stenosis), ¶ 41 clarifies that these include “pressure boundary conditions” between the 1D/3D models, and ¶¶ 31 and 56 clarify that the aorta is a 1D model
Then, see fig. 3, noting where the stenosis is, specifically the coronary tree starts at the “Aorta”, then bifurcates to the LCA and RCA branches, then bifurcates again, wherein, in the example of Sharma fig. 3, the vessel # 334 has stenosis, therefore for the 3D model of fig. 3, at 334, this includes having a pressure boundary condition at the LCA coupling
POSITA would have readily known that stenosis may occur in numerous places in the coronary tree, including the LCA, so when the system of the combination of prior art discussed above was made patient-specific (abstract of Sharma, § 2.3 ¶ 2 of Larrabide, etc.) to a patient with stenosis of the LCA, then there would have been an aortic pressure inlet boundary condition for the LCA 3D model for the stenosis in the LCA, wherein this was simply the result of what patient (mainly, where the stenosis is in the patient) the system is applied to
Furthermore, in a similar vein, the Examiner notes that this would have been prima facie obvious because this would have required nothing more than a simple re-arrangement of parts (MPEP § 2144.04), i.e. swap the 3D model from being in vessel 312 fig. 3 to 308 in fig. 3 (by merely swapping which vessel was stenosed), and one arrives at this claimed invention, where, as discussed above, POSITA would have been motivated to do so because this would have enabled the system to model and assess stenoses in the LCA (e.g. because a new patient has stenosis in the LCA)
Regarding Claim 24.
The above relied upon prior art teaches:
The method according to claim 1, wherein the quantitative flow analysis of g) calculates a parameter related to pressure difference across the region of interest. (Larrabide, as was taken in view of Schrauwen as cited above for claim 1 for this feature, in particular for the FFR)
Regarding Claim 25.
The above relied upon prior art teaches:
The method according to claim 24, wherein the parameter represents a fractional flow reserve value for the region of interest. (Larrabide, as was taken in view of Schrauwen as cited above for claim 1 for this feature, in particular for the FFR
Should further clarification be required, see Sharma abstract, and then see ¶ 61, including its discussion of the advantages of FFA for additional motivations to calculate the FFR)
Regarding Claim 26.
The above relied upon prior art teaches:
The method according to claim 25, wherein the fractional flow reserve value is calculated directly or by adjusting the coupled model to simulate hyperemia state. (Larrabide, as was cited above for claim 1 in § 5.3 ¶ 4: “The evaluation method used in the course was based on a series of reports based on numerical simulations in which the students had to perform modifications in the model and simulate different situations that may occur, such as the effects of aging, vasodilation, vasoconstriction, at-rest and exercise regimes [example of a hyperemia state],…”; in view of Schrawuen § 2.5 last paragraph as noted above: “The FFR is defined as the ratio between the distal pressure Pd and the aortic pressure Pa under hyperemia”
Should further clarification be required, see Sharma abstract, and then see ¶ 61, including its discussion of the advantages of FFR for additional motivations to calculate the FFR, including: “The functional aspects are related to the blood flow rate through a stenosis, during rest and hyperemic state… FFR is calculated by dividing the pressure distal to the stenosis to the pressure proximal to a stenosis. Since venous pressure can be generally taken as equal to zero without introducing a significant error, and the microvascular resistance is minimal and constant during hyperemic state for both a normal and stenotic vessel, the fraction of the pressures also represents the fraction of the normal maximum hyperemic flow that can still be supplied in the presence of the stenosis.” – also, Sharma, ¶ 43: “Coronary autoregulation plays a major role in the adaptation of the coronary tree to arterosclerotic segments in the epicardial vessels. Autoregulation refers to the change in the microvascular resistance as a reaction to a change in the perfusion pressure and its role is to maintain a constant flow rate through the capillaries. This aspect refers to the normal or rest state of the body. Another type of regulation takes place at exercise or drug-induced hyperemia, when the microvascular resistance decreases to a minimum in order to allow a three to five-fold increase of the flow rate. Both of these aspects have to be taken into account inside a multi-scale model of the coronary tree.”
Regarding Claim 27.
The above relied upon prior art teaches:
The method according to claim 1, wherein the region of interest is identified automatically or semi-automatically based on user input. (Larrabide, as cited above, for the identifying, teaches a user does the identifying (fig. 4-5; § 4.2 incl. ¶ 1) semi-automatically, and Sharma, as cited above and as was taken in combination for further modifying this, teaches the automatically as discussed above;
also see MPEP § 2144.04 for In re Venner for broadly automating a manual activity is prima facie obvious, e.g. by simply reciting “automatically” is exemplary of broadly automating
Regarding Claim 28.
The above relied upon prior art teaches:
The method according to claim 5, wherein the geometric features extracted from the 3D reconstruction comprise at least one feature of the conduits of the tree selected from the group consisting of diameter, length, curvature, and centerline. (Larrabide, in view of Sharma, as discussed above for claims 5-6 teaches this; for the centerline see Sharma, ¶ 54: “In order to extract the coronary anatomy from the medical images, embodiments of the present invention can utilize existing coronary segmentation and centerline extraction algorithms. Such algorithms readily provide the coronary vessel centerline tree, together with a surface representation including the stenosis narrowing, which is then used for extracting the required anatomical data for the 3D and ID computations.””
Regarding Claim 29.
The above relied upon prior art teaches:
The method according to claim 1, wherein the 1D model of a) is based on a standard 1 D model that is adjusted by patient specific data. (Larrabide, as discussed above for claims 5-6, also 28, and similar such claims)
Regarding Claim 30.
The above relied upon prior art teaches:
The method according to claim 1, wherein the reduced 3D model for the region of interest is generated from geometric features of the 3D reconstruction of b). (Larrabide, as was taken in view of Schrauwen as cited above teaches this, i.e. run several 3D CFD simulations for the region of interest, and fit the pressure drop equations to the results (Schrauwen, § 2.4 as noted above, note that length and radius are terms in said equations)), wherein in this combination the 3D CFD model would have been the one from Larrabide as was modified by Sharma as discussed above, wherein Larrabide fig. 6 visually shows that the 3D model recreates the geometry from the geometric features of the input 3D reconstruction)
Regarding Claim 31.
This is rejected under a similar rationale as claim 1 as discussed above, wherein:
A non-transitory computer-readable storage medium having stored thereon executable instructions that, when executed by one or more processors of a computer system, cause the computer system to perform quantitative flow analysis of a tree of conduits perfusing an organ of a patient from at least two bi- dimensional images of at least part of the tree obtained from different perspectives, by: (Larrabide, as cited above for claim 1 preamble )
Regarding Claim 32.
Larrabide, in view of Schrauwen and Sharma, teaches:
An X-ray imaging system comprising an imaging device for acquiring the plurality of bi-dimensional images that is operably coupled to a computer configured to perform the method of claim 1 to determine at least one fractional flow reserve value of a conduit of the at least part of the tree of the patient. (See rejection of claim 21 above, noting Sharma, ¶ 26 discussing that the medical image data is received from the device “directly”, i.e. it was transmitted so as to be received, thus they were coupled, and see Larrabide, in view of Schrauwen as well as Sharma as discussed above for the FFR (detailed discussion in claims 1, and 24-26)
To further clarify, Sharma, ¶ 68: “An image acquisition device 1020, such as a CT scanning device, MR scanning device, Ultrasound device, etc., can be connected to the computer 1002 to input image data to the computer 1002. It is possible to implement the image acquisition device 1020 and the computer 1002 as one device. It is also possible that the image acquisition device 1020 and the computer 1002 communicate wirelessly through a network. ” – and ¶ 26 clarifies that an “Angiography scanner” is one the listed acquisition devices, wherein, per the definition noted above, angiography is an x-ray imaging technique, i.e. its an x-ray imaging system
POSITA would have been further motivated (see the motivations above for the combination) to do this combination, because Sharma’s imaging technique, in combination with Sharma’s reconstruction technique (¶¶ 27-28 relied upon above), would have improved the variety of different imaging modalities that may be used in this system, allowing doctors to use the imaging device they have easiest access to (or the one that insurance most readily pays for/tells the doctor to use first).
Regarding Claim 35.
Larrabide, in view of Schrauwen and Sharma, teaches:
The X-ray imaging system according to claim 32, further comprising an input device configured to receive user input, wherein the user input selects a predetermined 1 D model to be used in the flow analysis or specifies location of the region of interest within the 1 D model (See the above discussion for claim 1, 5-6, wherein the Examiner notes Larrabide § 4.2 and figures 4-5 show the UI and discuss the steps including the region identification of the object of interest from the user,
also Larrabide figure 3 shows that its to “read SolverGP files” for an initial 1D model generation before it is later edited (also, see fig. 2 for the GUIs involved), wherein further note the “1D model writer” in fig. 3, i.e. Larrabide’s system opens a selected model, reads the file, user does edits to the 1D/0D model, saves the file, etc.,
to clarify, fig. 2(a) – specifically note that there is a “Selection Window” and below that a box for “Parameters”, wherein in this portion of the GUI, below the row of three buttons with a green “Accept” button, there is a “Filename”, followed by an entry text box with what appears to be tpyicaly text for a file path with “/” characters separating folders, and to the right of this is a “Browse” button, thus POSITA would have inferred that by clicking said button a new pre-determined (e.g. a previously determined one that was saved, such as by another user) model may be selected
Claim(s) 3-4, 9, 12-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Larrabide, Ignacio, et al. "HeMoLab–Hemodynamics Modelling Laboratory: An application for modelling the human cardiovascular system." Computers in biology and medicine 42.10 (2012): 993-1004 in view of Sharma et al., US 2013/0132054 and in further view of Schrauwen, J. T. C., et al. "Geometry-based pressure drop prediction in mildly diseased human coronary arteries." Journal of biomechanics 47.8 (2014): 1810-1815 in view of Zhang et al., "Quantification of coronary microvascular resistance using angiographic images for volumetric blood flow measurement: in vivo validation", 2011
Regarding Claim 3
While Larrabide, in view of Schrauwen and Zhang, do not explicitly teach the following feature, these would have been obvious when said combination was taken in further view of Zhang:
The method according to claim 1, further comprising, before g), performing quantitative image analysis to update the coupled model to take into account status of at least parts of the conduits that form the tree. (Larrabide in view of Sharma, as was cited above for claims 1, 5-6 and 8 (specifically see 8 first), wherein this does not explicitly teach a quantitative image analysis to determine if collateral flow is present
As taken in further view of Zhang, abstract: “Quantification of coronary microvascular resistance using angiographic images for volumetric blood flow measurement…” and Zhang, page 2096, col. 2, ¶¶ 1-3: “Therefore, measurements of coronary MR play a pivotal role in diagnosing and monitoring the effects of therapeutic interventions… Resistance is determined by dividing the pressure gradient by flow. In the case of the heart, true microcirculatory resistance (1, 12, 26) is theoretically defined as the mean aortic to coronary back pressure (vide infra) gradient divided by absolute coronary blood flow (in mmHg·ml1·min1) at hyperemia. Myocardial perfusion pressure is easy to measure invasively with a catheter or a coronary pressure wire. Therefore, the challenge for calculating MR is to measure the absolute coronary blood flow… The studies demonstrated the feasibility and potential utility of the FPA algorithm in conjunction with digital subtraction angiography for measuring volumetric coronary blood flow. When compared with other blood flow measurement techniques, the current angiographic method is simple to implement. It can be done in conjunction with routine coronary angiography, which can be accomplished during diagnostic cardiac catheterization. Furthermore, MR can be easily calculated using angiographic volumetric blood flow. The purpose of the current study is to validate the MR measurement technique in vivo using the FPA technique.”, i.e. “This new method is accurate, quantitative, and easy to perform, requiring only angiographic images” (Zhang, page 2102, col. 2, ¶ 3))
Then see Zhang, pages 2097-2098, section “Blood flow measurement using angiographic images” which teaches: “…This technique combines the densitometric analysis of spatial and temporal aspects concerning the contrast propagation through the myocardium. Flow measurements are made by summing up the pixel values in the regions of interest (ROIs) using temporal subtraction images. Coronary blood flow was determined from the change in volume during one cardiac cycle. An ROI for flow measurement was drawn around the LAD vascular bed that encompassed both the visible arteries and the microcirculatory blush (43, 60) (Fig. 3 [see fig. 3, this shows it is of a part of the tree]) Power injection of contrast material was assumed to momentarily replace blood with contrast material. The known iodine concentration in the contrast material and a linear regression analysis between the measured integrated gray levels in the calibration phantom were used to convert the gray level to volume. Therefore, the difference of densitometric signal in the vascular bed can be converted to the volume of contrast bolus entering the vascular bed between successive images [at least two images] using system iodine calibration. The time period of the cardiac cycle was calculated from the image acquisition rate (30 frames/s).” – a skilled person would have inferred that this included measuring the contrast propagation velocity because the “contrast propagation” was analyzed by “summing up the pixel values in the regions of interest” for “successive images” at “30 frames/s”, i.e. as the “contrast bolus” enters in successive images its position is measured by the “pixel values” in each image, with a fixed “time period” between each image of 1/30 seconds, as such the “difference of densitometric signal in the vascular bed…between successive images” [including the change in position of the bolus] over the given the time period would have been an example of a contrast propagation velocity measurement
Wherein Zhang, page 2102, col. 1, last paragraph clarifies: “Myocardial perfusion flow is a combination of coronary and collateral flow, so calculations using it tend to overestimate MR if they neglect collateral flow (53, 58) . In our current angiographic flow measurement, the ROI was drawn large enough to ensure that the LAD vascular bed will be within the ROI (35). As a consequence, this technique ensured that any visible potential collateral flow perfusion will be included in the angiographic NMR measurement. However, in cases of severe stenosis, coronary angiography still has only limited sensitivity for quantifying collateral circulation capacity (45, 53).” And see the conclusion: “This study demonstrated that the angiographic flow measurement based on the FPA technique can be used to assess the severity of microvascular disruption even in the presence of intermediate severity epicardial stenosis (75% area stenosis).” – i.e. the measurement was on a part of the tree with “stenosis”; wherein this characterized the “collateral flow”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings from Larrabide, in view of Sharma and Schrauwen as cited above, on a system for coupled modelling of a coronary tree, wherein Larrabide suggests using more measurements for better calibration/updating of the models involved, and Sharma teaches using imaging techniques, including angiography, to avoid invasive measurements in current clinical practice (Sharma ¶¶ 20, 26-28, etc.), including the addition of 1D/0D model elements if there is a presence of collateral flow (Sharma ¶ 32 and other portions noted above) with the teachings on Zhang of a “Quantification of coronary microvascular resistance using angiographic images for volumetric blood flow measurement”(Zhang, abstract).
The motivations to combine would have been that: 1) “This study provides a method to measure NMR without using a velocity wire, which can potentially be used to evaluate microvascular conditions during coronary arteriography.” (Zhang, abstract), 2) “When compared with other blood flow measurement techniques, the current angiographic method is simple to implement. It can be done in conjunction with routine coronary angiography, which can be accomplished during diagnostic cardiac catheterization. Furthermore, MR can be easily calculated using angiographic volumetric blood flow.” (Zhang, page 2096, col. 2, ¶ 3), 3) “This new method is accurate, quantitative, and easy to perform, requiring only angiographic images.” (Zhang, conclusion), and 4) “Myocardial perfusion flow is a combination of coronary and collateral flow, so calculations using it tend to overestimate MR if they neglect collateral flow (53, 58) . In our current angiographic flow measurement, the ROI was drawn large enough to ensure that the LAD vascular bed will be within the ROI (35). As a consequence, this technique ensured that any visible potential collateral flow perfusion will be included in the angiographic NMR measurement” (Zhang, page 2102, col. 1, ¶ 5).
Regarding Claim 4
The combination relied upon in claim 3 teaches:
The method according to claim 3, wherein the quantitative image analysis involves densitometric image analysis that determines at least one of the status of the organ and the presence of collateral flow within the tree due to conduit narrowing or blockage. (See the detailed citation and discussion for claim 3 above, including page 2097-2098 as discussed above, including noting “densitometric analysis” and the “densitometric signal” as part of Zhang’s technique)
Rationale to combine is the same.
Regarding Claim 9
The combination relied upon in claim 3 teaches:
The method according to claim 8, wherein the status of the myocardium microvasculature is determined through blush image analysis. (See the detailed citation and discussion for claim 3 above, including page 2097-2098 as discussed above, include noting that this flow measurement includes “the microcirculatory blush”)
Rationale to combine is the same.
Regarding Claim 12.
The combination relied upon in claim 3 teaches:
The method according to claim 1, further comprising updating the coupled model to take into account presence of collateral flow in the coronary tree,. (Larrabide in view of Sharma, as discussed above for claims 1, 5-6, including Larrabide § 3 and fig. 2 as discussed above for editing the skeleton/topology of the tree after the initial creation from the files
Taken in further view of Sharma for the vessel of interest being a stenosis portion of the coronary tree of the heart, and ¶ 44 of Sharma “…An important aspect which influences the coronary flow in general and the autoregulation phenomenon in particular is the presence of collateral flow. These vessels, also called anastomotic channels, develop in the heart as an adaption to ischemia. They serve as conduit segments which bridge severe stenoses or connect a territory supplied by one epicardial coronary artery with that of another. Hence, collateral vessels represent an alternative source of blood supply to a certain part of the myocardium which is affected by coronary artery disease, and they can help to preserve myocardial function…” – and see fig. 3 for “Collaterial Flow” # 336 in ¶ 32: “One further aspect which is very important in the coronary circulation, and which contributes to the large discordance between morphological and functional importance of a stenosis is the presence of collateral flow which can render a morphologically important stenosis into a functionally insignificant one. Depending on the patient specific vessel morphology, the collateral flow 336 can be modeled both through anastomotic large vessels (with 1D models) or through microvascular vessels which supply the affected region with blood (modeled through lumped elements as in FIG. 3).”
To clarify on the BRI, see pages 20-21 of the instant disclosure
POSITA would have been motivated for similar reasons as discussed above, and because collateral flow is such of an “important aspect” for evaluating stenosis as discussed by Sharma as cited above, also Sharma, ¶ 61: “collateral blood flow can increase flow and attenuate the effect of the stenosis”
wherein the presence of collateral flow in the coronary tree is determined through velocity measurements based on at least one bi-dimensional image (See the rejection above for claim 3, including Zhang pages 2097-2098, in particular note that Zhang is measuring the velocity of the contrast – in particular, “This technique combines the densitometric analysis of spatial and temporal aspects concerning the contrast propagation through the myocardium… Coronary blood flow was determined from the change in volume during one cardiac cycle… Power injection of contrast material was assumed to momentarily replace blood with contrast material…Therefore, the difference of densitometric signal in the vascular bed can be converted to the volume of contrast bolus entering the vascular bed between successive images using system iodine calibration. The time period of the cardiac cycle was calculated from the image acquisition rate (30 frames/s). The ratio of the measured volume change to the time period of the cardiac cycle yields volumetric coronary blood flow.” – i.e. its measuring the temporal contrast volume, which is an example of contrast velocity (volume per time period of a cardic cycle), i.e. “The ratio of the measured volume change to the time period of the cardiac cycle yields volumetric coronary blood flow.” – i.e. see fig. 6(a), note “Flow” units are “mL/min”, i.e. milliliters of contrast per each minute
for further clarify, see the abstract: “However, an assessment of microvascular resistance (MR) requires a velocity wire… In conclusion, a technique based on angiographic image data for quantifying NMR was validated using a swine model. This study provides a method to measure NMR without using a velocity wire, which can potentially be used to evaluate microvascular conditions during coronary arteriography” – i.e. a benefit of Zhang is to avoid using a velocity wire but to still obtain a similar result without the wire – and see equation 3 of Zhang and its accompanying description; as further clarified on page 2101, col. 2, ¶ 1: “The angiographic NMR based on FPA technique has important advantages compared with the previously reported methods for NMR measurement. The angiographic NMR measurement requires no wires and reduces the cost and procedure time associated with these techniques”
Regarding Claim 13.
The combination relied upon in claim 3 and 12 teaches:
The method according to claim 12, wherein the determination of presence of collateral flow in the coronary tree uses delay between each bi-dimensional image to increase the temporal resolution of the determination. (See the above discussed combination, noting Zhang page 2097-2098 for: “Therefore, the difference of densitometric signal in the vascular bed can be converted to the volume of contrast bolus entering the vascular bed between successive images using system iodine calibration. The time period of the cardiac cycle was calculated from the image acquisition rate (30 frames/s). The ratio of the measured volume change to the time period of the cardiac cycle yields volumetric coronary blood flow.” – i.e. this increased the temporal resolution because it calculated the time period of the cardiac cycle directly from the rate of image acquisition (i.e. 30 frames per second, so approximately 1 frame per 33.3 milliseconds (1second/30 frames), in combination with a measurement between successive images
Regarding Claim 14.
The combination relied upon in claim 3 teaches:
The method according to claim 1, further comprising updating the coupled model to take into account type of collateral flow in the coronary tree, wherein the type of collateral flow in the coronary tree is determined using densitometric image analysis and geometric information. (See the above combination as discussed extensively above, i.e. in short for the calibration of the model by Larabide, wherein Sharma teaches adding a 1D/0D element into the model for collateral flow (¶ 32) at the location of the collateral flow (fig. 3), wherein Zhang was relied upon for teaching a densitometric image analysis technique that “ensured that any
visible potential collateral flow perfusion will be included in the angiographic NMR measurement” (Zhang, 2102) – see the above citations and discussion for further details
Rationale to combine is the same.
Regarding Claim 15.
The combination relied upon in claim 3, and similar such claims as noted above, including 14) teaches:
The method according to claim 1, further comprising updating at least one lumped parameter of the coupled model based on at least one of densitometric measurements and blush measurements. (See above for claims 3 and 14, including Sharma ¶ 32, and the like)
Regarding Claim 16.
The combination relied upon in claim 3, and similar such claims as noted above, including 14 teaches:
The method according to claim 15, wherein the lumped parameter is based on a hydraulic-electrical analogue where blood pressure and flow rate is represented by voltage and current, respectively, and effects of friction in blood flow is represented by resistance. (See above, including that its “Windkessel lumped Models” (p. 994 of Larrabide) with “R” and “C”, then see Sharma, ¶ 34, including: “The lumped or OD models 322-330 of the microvasculature
are based on the analogy between electricity and hydraulics and eliminate the spatial dependency of the independent variables by concentrating the physiological properties
of the small vessels into lumped elements: resistance [resistance to blood flow], compliance [capacitors in fig. 3] and inertance [the inductors in fig. 3, note the above discussed definition of this term, note the root term here is “inertia” as well]… Three different mechanisms can be used to explain the observed flow rate waveform inside the coronary tree: varying elasticity, shortening- induced intracellular pressure and cavity induced extracellular pressure… In the multi-scale perspective, regular 3-element Windkessel models can be used at the termination sites of vessels which do not belong to the coronary tree” – and fig. 3, which shows inductors and capacitor elements as POSITA would have readily recognized
as a point of clarity on the BRI, see in Larrabide p. 994 col. 2, ¶ 2 that “R1, R2
and C are the lumped parameters that characterize the peripheral beds” – POSITA would recognize R as resistance, and C as capacitance, given the context that these are Windkessel lumped models, then, see figure 5 of the instant disclosure as described on page 9: “Fig. 5 shows the RC Windkessel model of the cardiovascular system;” including its use of “R” and “C”, and see page 15 ¶ 1 for its citation to Shi et al. for a summary on RC Windkessel models in another reference, i.e. this is a well-known analogy to POSITA, and for more evidence this is well-known, ¶ 34: “In the multi-scale perspective, regular 3-element Windkessel models can be used at the termination sites of vessels which do not belong to the coronary tree. The values of the resistances and compliances are determined by taking the average pressure and flow rate values and by adapting the resistance values in order to avoid non-physiological reflections.” – furthermore, its named Windkessel for, presumably, a person by the name of Windkessel developed this lumped model
Regarding Claim 17.
The combination relied upon in claim 3, and similar such claims as noted above, including 14 teaches:
The method according to claim 16, wherein the hydraulic-electrical analogue further includes capacitance that represents effects of inertia in blood flow. (See rejection of claim 16 above)
Regarding Claim 18.
The combination relied upon in claim 3, and similar such claims as noted above, including 14 teaches:
The method according to claim 16, wherein the hydraulic-electrical analogue further includes inductance that represents effects of vessel elasticity. (See rejection of claim 16 above)
Regarding Claim 19.
The combination relied upon in claim 3, and similar such claims as noted above, including 14 teaches:
The method according to claim 1, further comprising using at least one of densitometric measurements and blush measurements to add at least one 1D element to the coupled model. (See rejection of claim 3 above, and its dependents, noting Sharma ¶ 32 as was discussed above, i.e. the measurements (that are both of the blush and densitometric) of Zhang, with adding in 1D elements per Sharma 32, as part of the model calibrations of Larrabide for the reasons discussed above)
Claim(s) 10-11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Larrabide, Ignacio, et al. "HeMoLab–Hemodynamics Modelling Laboratory: An application for modelling the human cardiovascular system." Computers in biology and medicine 42.10 (2012): 993-1004 in view of Sharma et al., US 2013/0132054 and in further view of Schrauwen, J. T. C., et al. "Geometry-based pressure drop prediction in mildly diseased human coronary arteries." Journal of biomechanics 47.8 (2014): 1810-1815 in view of Zhang et al., "Quantification of coronary microvascular resistance using angiographic images for volumetric blood flow measurement: in vivo validation", 2011 and in further view of Liao, Rui, et al. "3-D reconstruction of the coronary artery tree from multiple views of a rotational X-ray angiography." The international journal of cardiovascular imaging 26.7 (2010): 733-749.
Regarding Claim 10.
While the above noted combination relied upon for claim 9 does not explicitly teach the following, it would have been obvious when said combination was taken in further view of Liao:
The method according to claim 9, wherein the blush image analysis involves a blush measurement in at least two bi-dimensional images that accounts minimizes effects of foreshortening and superimposing. (See the detailed citation and discussion for claim 9
Taken in view of Liao, abstract: “To present an efficient and robust method for 3-D reconstruction of the coronary artery tree from multiple ECG-gated views of an X-ray angiography. 2-D coronary artery centerlines are extracted automatically from X-ray projection images using an enhanced multi-scale analysis. For the difficult data with low vessel contrast, a semi-automatic tool based on fast marching method is implemented to allow manual correction of automatically-extracted 2-D centerlines. First, we formulate the 3-D symbolic
reconstruction of coronary arteries from multiple views as an energy minimization problem incorporating a soft epipolar line constraint and a smoothness term evaluated in 3-D. The proposed formulation results in the robustness of the reconstruction to the imperfectness in 2-D centerline extraction, as well as the reconstructed coronary artery tree being inherently smooth in 3-D”
then page 735, col. 1, last two paragraphs, then see the dsicussions section ¶ 1: “Incorporating multiple projections for efficient and robust 3-D coronary reconstruction is particularly important when a complex coronary artery tree needs to be generated because it may be difficult to find two views with good angular distance that both have sufficient contrast injection and minimal vessel overlap/ foreshortening for the complete coronary artery tree. The requirement on user interaction for correspondence matching also presents a major limitation for its clinical applications. The advantage of utilizing more than two views for automatic, accurate and robust reconstruction is quantitatively demonstrated in this work using a software coronary phantom.” – POSITA would have inferred that this would have resulted in minimized vessel overlap and foreshortening as well, as it is using more than two view and “accurate and robust”, wherein additional views may be taken by the cardiologist to further improve on this – page 735, col. 2, ¶ 2: “The most straightforward application of our method in a clinical setup would be to provide the reconstructed 3-D coronary model to the interventional cardiologists at the beginning of the PCI procedures. The 3-D model visualization will help the clinicians choose optimal angiographic views to minimize vessel foreshortening, select proper stent type and size, and properly plan the stent placement 3-D locations.” – in view of the introduction ¶ 1 as discussed below
for relevancy to the obviousness of this desired result to POSITA, see the introduction, ¶ 1: “Traditionally, several angiographic views are taken from different angles and then are selected subjectively based on the cardiologist’s experience, to minimize foreshortening and vessel overlap [superimposing].” And page 734, col. 2, ¶ 2: “In addition, whereas typically it is preferred to have two projections orthogonal to each other, this angular distance may not be achievable in a clinical setup when foreshortening and vessel overlap need to be minimized for the whole coronary artery tree in both projections.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings from the system as discussed above of Larrabide, as modified above, which including generating 3D reconstruction from angiography and other such measurements in angiography with the teachings from Liao on “an efficient and robust method for 3-D model generation of the coronary artery tree using all the projections of a rotational X-ray sequence that correspond to the same cardiac phase.” (Liao, page 735, col. 1, ¶¶ 2-3) The motivation to combine would have been that its “an efficient and robust method for 3-D model generation” – additional motivations to combine are on page 735, col. 1, ¶¶ 2-3.
Regarding Claim 11.
Combination relied upon above for claim 10 teaches:
The method according to claim 10, wherein a three-dimensional imaging modality is used to register the bi-dimensional images used for the blush image analysis. (In the combination above for claims 8-10, see Liao, page 735, col. 1, ¶ 3: “The goal of this paper is to describe an efficient and robust method for 3-D model generation of the coronary artery tree using all the projections of a rotational X-ray sequence that correspond to the same cardiac phase. A rotational X-ray sequence is acquired by rotating the C-arm with a constant source to intensifier distance, a constant cranio/caudal angle (CRAN/CAUD), and a varying left/right anterior oblique angle (LAO/RAO).” – i.e. it’s a 3D imaging modality as the C-arm is moving it in 3D around the patient, registering 2D images (fig. 1-2, see fig. (5) as well)
Rationale to combine is the same as discussed above.
Claim(s) 33 is/are rejected under 35 U.S.C. 103 as being unpatentable over Larrabide, Ignacio, et al. "HeMoLab–Hemodynamics Modelling Laboratory: An application for modelling the human cardiovascular system." Computers in biology and medicine 42.10 (2012): 993-1004 in view of Sharma et al., US 2013/0132054 and in further view of Schrauwen, J. T. C., et al. "Geometry-based pressure drop prediction in mildly diseased human coronary arteries." Journal of biomechanics 47.8 (2014): 1810-1815 in view of Zhang et al., "Quantification of coronary microvascular resistance using angiographic images for volumetric blood flow measurement: in vivo validation", 2011 and in further view of Jarisch, “Myocardial Perfusion Evaluation Using Only Six Projections”, 2012, accessed via URL: www(dot)researchgate(dot)net/publication/271842517_Myocardial_Perfusion_Evaluation_Using_Only_Six_Projections
Regarding Claim 33.
While the relied upon combination of Larrabide, in view of Sharma, Schrauwen, and Zhang, does not explicitly teach the following feature, it is taught when said combination is taken in further view of Jarisch:
An X-ray imaging system according to claim 32, wherein the computer is further configured to read information on rotational and angulation position of the imaging device for use in blush and densitometric measurements, wherein said information includes information on the delay between acquired image frames with respect to frontal and lateral X-ray source of the imaging device. (See claim 3 as discussed above for the blush and densitometric measurements using X-ray angiography, wherein Zhang’s technique relies upon the delay between each frame (page 2098, col. 1, ¶ 2 as discussed above, along with surrounding paragraphs)
As taken in further view of Jarisch, § 1: “…The purpose here is to add 3-D reconstruction of myocardial blush using the small number of projections available in angiographic procedures” wherein § 3 teaches “The method incorporates parameters for automated alignment of projections and corrections of possible 3D motion artifacts”, see § 4.3 clarifies “The new High Efficiency CT (HECT) was applied to sets of the set projection directions [the rotational and angulation positions] for each experimental condition. Progressive resolution made automated mutual alignment of projections very efficient)” to further clarify see § 4.2: “For any given projection direction [including frontal and lateral, as this is “any given…direction”] the first four phase points within an R-R interval, free of any blush image defects (e.g. due to late manual injection), were selected for DSA (Fig. 4.3)” wherein the caption of fig. 4.3 clarifies “Myocardial blush in two consecutive beats” – to clarify, each “beat” is represented by “four phase points”/images over the time of the beat; as such a skilled person would have inferred this included information on the delay between the “four phase points”, and delay between the “beats”
To clarify on the frontal/lateral: see fig. 4.1, which shows the “Angiographic setup” which shows the “CT” (§ 4.3) [example of an x-ray system] wherein § 4.1 teaches “…this acquisition procedure was repeated six times at 30 [degree] increments” – as such, a skilled person would have inferred that this includes the x-ray source being in the front (such as pictured in fig. 4.1), and the later “increments” would have moved this source to be in a lateral position (i.e., the source moves down the arm shown in the figure in 30 degree increments).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings from the combination above on a system for cardiovascular modelling that includes the “Quantification of coronary microvascular resistance using angiographic images for volumetric blood flow measurement” (Zhang, abstract) with the teachings from Jarisch on a system to evaluate the “myocardial blush” from “angiographic procedures” (Jarisch, § 1) The motivation to combine would have been that “...The value of the present technique lies in versatility and efficiency: (i) it may be added to angiographic procedures; and (ii) it may reduce X-ray exposure or MRI measurement times [5] many-fold for traditional 3D tomographic needs” (Jarisch, § 5 ¶ 2).
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Larrabide, Ignacio, et al. "HeMoLab–Hemodynamics Modelling Laboratory: An application for modelling the human cardiovascular system." Computers in biology and medicine 42.10 (2012): 993-1004 in view of Sharma et al., US 2013/0132054 and in further view of Schrauwen, J. T. C., et al. "Geometry-based pressure drop prediction in mildly diseased human coronary arteries." Journal of biomechanics 47.8 (2014): 1810-1815 and in further view of Mynard et al., “Scalability and in vivo validation of a multiscale numerical model of the left coronary circulation”, 2014
Regarding Claim 7
While Larrabide, in view of Sharma and Schrauwen do not teach the following ordered combination in full, it is taught when this combination is taken in further view of Myard:
The method according to claim 1, wherein the tree is a coronary tree, the organ is the myocardium of the heart, and the 1D model of a) is based on a standard 1D model selected from a number of predetermined models comprising a left dominant, a right dominant, and a balanced or small right/left dominant model of the coronary tree.
(Larrabide, in view of Sharma, as cited and discussed above for claims 5-6, Larrabide figure 3 shows that its to “read SolverGP files” for an initial 1D model generation before it is later edited (also, see fig. 2 for the GUIs involved), wherein further note the “1D model writer” in fig. 3, i.e. Larrabide’s system opens a selected model, reads the file, user does edits to the 1D/0D model, saves the file, etc.
to clarify, fig. 2(a) – specifically note that there is a “Selection Window” and below that a box for “Parameters”, wherein in this portion of the GUI, below the row of three buttons with a green “Accept” button, there is a “Filename”, followed by an entry text box with what appears to be typically text for a file path with “/” characters separating folders, and to the right of this is a “Browse” button, thus POSITA would have inferred that by clicking said button a new pre-determined (e.g. a previously determined one that was saved, such as by another user) model may be selected
Taken in view of Sharma for the vessel of interest being a stenosis portion of the coronary tree of the heart, and ¶ 44 of Sharma “…Hence, collateral vessels represent an alternative source of blood supply to a certain part of the myocardium which is affected by coronary artery disease, and they can help to preserve myocardial function…” – i.e. the vessels perfuse the myocardium
Taken in further view of Mynard, abstract, teaches: “We therefore validated a multiscale model of the left coronary circulation using high-fidelity data from nine adult sheep and nine newborn lambs and investigated whether wave propagation effects are more prominent in adults, whose body size (and hence wave transit distance) is greater. The model consisted of a one-dimensional (1D) network of the major conduit arteries and a lumped parameter model of microvascular beds. Intramyocardial pressure was considered to arise via contraction-related myocyte thickening and transmission of ventricular cavity pressure into the heart wall. 1D network geometry from published human anatomical data was scaled using myocardial weights, while subject-specific aortic pressure/flow and ventricular pressure formed model inputs.”, as clarified on page 518, col. 1, ¶ 1: “1D model of conduit coronary arteries. Most sheep (8, 20) display a left dominant coronary anatomy in which the Cx supplies the posterior portion of the ventricular septum. Based on the gross similarity between left dominant anatomies in humans and sheep (20), the 1D conduit artery model shown in Fig. 1 was adapted from measurements in humans by Dodge et al. (16).”; to clarify, page 526, col. 2, ¶ 2: “The geometry of the 1D conduit arterial network was based on human data (16) with similar gross coronary anatomy to sheep (20), and we therefore did not account for any anatomical differences between species or subjects.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings from Larrabide on a system which used a 1D anatomical model with the teachings from Mynard on a “1D conduit artery model” that is “left dominant”. The motivation to combine would have been that “Excellent agreement was obtained between simulated and measured CxQ waveforms in most cases. Detailed flow waveform analysis did not clearly reveal a greater prominence of wave propagation effects in adults compared with newborns. This multiscale model is likely to be useful for investigating wave phenomena and phasic aspects of coronary flow in adults and during development.” – to clarify, page 525, col. 1, ¶¶ 2-3: “The model described herein, along with our recent study of congenital coronary abnormalities (44), represents the first modeling effort in relation to the newborn coronary circulation. In the absence of subject-specific vascular geometry, this was made possible by using allometric scaling, a powerful technique for predicting physiological parameters over a wide range of body sizes across species (22) or during maturation (56)….”
Claim(s) 34 is/are rejected under 35 U.S.C. 103 as being unpatentable over Larrabide, Ignacio, et al. "HeMoLab–Hemodynamics Modelling Laboratory: An application for modelling the human cardiovascular system." Computers in biology and medicine 42.10 (2012): 993-1004 in view of Sharma et al., US 2013/0132054 and in further view of Schrauwen, J. T. C., et al. "Geometry-based pressure drop prediction in mildly diseased human coronary arteries." Journal of biomechanics 47.8 (2014): 1810-1815 and in further view of official notice.
Regarding Claim 34.
Larrabide teaches:
The X-ray imaging system according to claim 32, wherein the computer is embodied in a cloud or high-performance computing cluster. (Larrabide, § 4.6, last paragraph: “In addition, SolverGP is a parallel code which makes use of MPI communication, and uses the PETSc library [37] for solving systems of linear equations.” And § 4: “HeMoLab’s graphical user interface has been developed on top of ParaView [31], a visualization software whose development is based on VTK – The Visualization Toolkit [32]. This software is an application originally developed for scientific visualization of large data sets in scientific computing.”
Taken in view of Official Notice, wherein the Examiner takes official notice that cloud computing and high-performance computing clusters are well-known, takes further Official Notice that MPI is a commonly used and well-known messaging protocol in such technologies for distributing complex computations across numerous processing devices for parallel processing, and therefore POSITA would have found it obvious to have used such a system in such an environment to improve the speed of the calculations, wherein POSITA would have recognized this was predictable as the solver code is already a parallel code making use of MPI communications (for distributing across multiple compute nodes, e.g. in a cloud environment or high performance computing clusters)
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
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Claims 1 and 31 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 34 of U.S. Patent No. 11983473. Although the claims at issue are not identical, they are not patentably distinct from each other because:
The instant claimed invention is merely a broader claim then what is set forth in claims 1 and 34 of the ‘473 (i.e. the ‘473 anticipates, or at least renders obvious as an obvious variant, the instant claimed invention). Claim 31 is an obvious variant due to its change in statutory category.
Claims 1-35 are rejected on the ground of nonstatutory double patenting as being unpatentable over the claims (see table below for details on which claims) of the U.S. Patent No. 11983473 in view of Schrauwen et al., “Geometry-based pressure drop prediction in mildly diseased human coronary arteries”, 2014.
The features recited in the instant independent claims that are missing in the ‘473 independent claims are:
First, the use of the volumetric mesh and CFD simulations in generating the reduced order model (rather, this feature is found in dependent claim 34 of the ‘473, hence two grounds of rejection).
Second, the determination of FFR in instant claims 32-34, when compared to the claim tree of independent claim 22 in the ‘473 patent.
However, these features would have been obvious when taken in view of Schrauwen, abstract, then see § 2.3 for its CFD discussion, then see § 2.4 for the fitted equation for pressure drop and its generation by fitting CFD results, then see § 2.5 last paragraph for the FFR calculation using both the CFD simulation, as well as a second FFR calculation by the reduced-order model (see fig. 5 and its accompanying description to clarify).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings from the ‘473 claimed invention with the teachings from Schrauwen discussed above. The motivation to combine would have been that “Our results show that the additional pressure drop in the tapered model can be estimated very accurately in the linear regime based on Eq. (2.4) and adequately in the non-linear regime… Despite that our pressure drop prediction shows deviations on a vessel to vessel basis, we did incorporate key geometrical features that determine the pressure drop into the model. This leads us to belief that our model is more suitable for quick pressure drop predictions in mildly diseased regions than predictions based on the models originating from Young and Tsai, since these models were developed for high degrees of stenoses… A high correlation was found between FFRCFD and FFRestimation. Despite the observed discrepancy between computed and estimated pressure drop the relatively high arterial pressure leads to a very good FFR prediction… In this study we derived an expression for the pressure drop in mildly diseased coronary arteries based solely on imaging data. On average the predicted pressure drop shows good agreement with the computed pressure drop. The image based pressure drop estimation can be used for quick determination of boundary conditions, paving the way to assess WSS in a clinical setting” (Schrauwen, § 4)
Instant Application # 18541709
US Patent 11983473
Regarding Claim 1
A computer-implemented method for quantitative flow analysis of a tree of conduits perfusing an organ of a patient from a plurality of two bi-dimensional images of at least part of the tree obtained from different perspectives, the method comprising:
a) generating a one-dimensional (1D) model that is specific to the patient, wherein the 1D model includes a plurality of segments representing conduits of at least part of the tree of the patient, wherein fluid flow through the segments of the 1D model is governed by a one-dimensional, axisymmetric form of fluid equations;
b) generating a three-dimensional (3D) reconstruction for a subset of the tree of the patient;
c) identifying a region of interest within the 3D reconstruction which corresponds to a stenotic vessel segment belonging to the plurality of segments of the 1D model, wherein the stenotic vessel segment has a narrowing or blockage of flow;
d) using the 3D reconstruction to construct a volumetric mesh for the subset of the tree of the patient corresponding to the region of interest;
e) using the volumetric mesh of d) in conjunction with computational fluid dynamic simulations to generate a reduced three-dimensional (3D) model for the region of interest, wherein the reduced 3D model consists of a pressure drop equation for the region of interest;
f) adding the reduced 3D model to the 1D model of a) as a coupling condition at the position in the 1 D model identified in c) to generate a coupled model;
and g) performing quantitative flow analysis using the coupled model of f).
Regarding Claim 1
A computer-implemented method for quantitative flow analysis of a coronary tree perfusing a myocardium of a heart of a patient from bi- dimensional images of at least part of the coronary tree, the method comprising:
a) generating a three-dimensional (3D) reconstruction for a subset of the coronary tree of the patient from bi-dimensional images of at least part of the coronary tree obtained from different perspectives;
b) identifying a region of interest within the 3D reconstruction which has a narrowing or blockage of flow;
c) generating a reduced 3D model for the region of interest from the 3D reconstruction of a), wherein the reduced 3D model for the region of interest comprises a pressure drop equation for the region of interest;
d) generating a one-dimensional (1lD) model that is specific to the patient, wherein the 1D model includes a plurality of segments representing conduits of at least part of the coronary tree of the patient, such segments including 1 D segments with end parts connected with lumped parameter zero-dimensional models to take into account boundary conditions, wherein fluid flow through the segments of the 1D model is governed by a one-dimensional, axisymmetric form of fluid equations, and wherein the 1D model is based on at least one geometrical feature extracted from the 3D reconstruction of a), wherein the at least one geometrical feature is selected from a group consisting of diameter, vessel length, vessel curvature, and centerline;
e) generating a coupled model by adding the reduced 3D model of c) to the 1D model of d) as a coupling condition at a position in the 1D model corresponding to the region of interest;
f) updating the coupled model of e), wherein the updating is based on image analysis performed on a plurality of bi-dimensional images of at least part of the coronary tree, wherein the image analysis involves measurements of contrast propagation velocity along the coronary tree performed on at least two bi-dimensional images of the plurality of bi-dimensional images together with densiometric measurements performed on at least two bi-dimensional images of the plurality of bi-dimensional images for part of the coronary tree which has a narrowing or blockage of flow and around that part, wherein results of the measurements of contrast propagation velocity and the densiometric measurements characterize collateral flow within the coronary tree of the patient due to the narrowing or blockage of flow, and wherein results of the measurements of contrast propagation velocity and the densiometric measurements are used to adjust the coupled model of e) such that the coupled model characterizes the collateral flow within the coronary tree by adding one or more elements representing collateral flow parallel to a lesion or by adding one or more elements representing collateral flow from another coronary artery;
and g) performing quantitative flow analysis using the coupled model updated in f).
Regarding Claim 2
The method according to claim 1, wherein the coupled model comprises multiple segments identifying the conduits forming the tree, such segments being associated to 1 D segments in the coupled model with end parts connected with lumped parameter models to take into account boundary conditions.
See claim 1, limitation (d-e) as taken in ordered combination above.
Regarding Claim 3
The method according to claim 1, further comprising, before g), performing quantitative image analysis to update the coupled model to take into account status of at least parts of the conduits that form the tree.
See claim 1, limitation (f) as taken in ordered combination above.
Regarding Claim 4
The method according to claim 3, wherein the quantitative image analysis involves densitometric image analysis that determines at least one of the status of the organ and the presence of collateral flow within the tree due to conduit narrowing or blockage.
See claim 1, limitation (f) as taken in ordered combination above.
Regarding Claim 5
The method according to claim 1, wherein the 1D model of a) is based on a standard 1D model that is adjusted based on geometric features extracted from the 3D reconstruction.
Regarding Claim 5
The method according to claim 1, wherein the 1D model of d) is based on a standard 1D model including information on generalized diameter, length, and spatial orientation of a skeleton of segments that form the coronary tree that is adjusted based on the at least one geometrical feature extracted from the 3D reconstruction.
Regarding Claim 6
The method according to claim 1, wherein the 1 D model of a) is based on a standard 1D model that is adjusted based on patient-specific data available from an imaging modality, wherein the patient-specific data comprises at least one feature selected from the group consisting of skeleton, diameters, vessel length, vessel curvature, and bifurcation angles.
Regarding Claim 5
The method according to claim 1, wherein the 1D model of d) is based on a standard 1D model including information on generalized diameter, length, and spatial orientation of a skeleton of segments that form the coronary tree that is adjusted based on the at least one geometrical feature extracted from the 3D reconstruction.
As taken in ordered combination with claim 1 above, including limitation (a)
Regarding Claim 7
The method according to claim 1, wherein the tree is a coronary tree, the organ is the myocardium of the heart, and the 1D model of a) is based on a standard 1D model selected from a number of predetermined models comprising a left dominant, a right dominant, and a balanced or small right/left dominant model of the coronary tree.
See claim 1 above, including the preamble, and then:
Regarding Claim 7
The method according to claim 1, wherein the 1D model of d) is based on a predetermined 1D model of the coronary tree selected from a left dominant model, a right dominant model, a balanced model or small right/left dominant model.
Regarding Claim 8
The method according to claim 1, further comprising updating the coupled model to take into account status of the myocardium microvasculature.
Claim 1, incl. seeing (f)
Regarding Claim 9
The method according to claim 8, wherein the status of the myocardium microvasculature is determined through blush image analysis.
Claim 1, incl. seeing (f)
Regarding Claim 10.
The method according to claim 9, wherein the blush image analysis involves a blush measurement in at least two bi-dimensional images that accounts minimizes effects of foreshortening and superimposing.
Claim 1, incl. seeing (f), wherein instant claim 10 is an obvious variant by merely specifying a desired result with no restriction on how that result is to be accomplished, thereby encompassing any and all means to accomplish said result, thereby its an obvious variant given that the evidence of record as noted extensively above shows that traditionally, the cardiologist conventionally achieves this desired result by a manual process with their subjective opinion exercised during the operation of the angiography machine
Regarding Claim 11.
The method according to claim 10, wherein a three-dimensional imaging modality is used to register the bi-dimensional images used for the blush image analysis.
Regarding Claim 11.
The method according to claim 43, wherein a three- dimensional imaging modality is used to register the at least two bi-dimensional images used for the blush measurements.
Regarding Claim 12.
The method according to claim 1, further comprising updating the coupled model to take into account presence of collateral flow in the coronary tree, wherein the presence of collateral flow in the coronary tree is determined through velocity measurements based on at least one bi-dimensional image.
Claim 1, incl. (f)
Regarding Claim 13.
The method according to claim 12, wherein the determination of presence of collateral flow in the coronary tree uses delay between each bi-dimensional image to increase the temporal resolution of the determination.
Claim 1, incl. (f), then see claim 14, wherein the Examiner notes the increase merely specifies a desired result, but claim 14 recites use of the delay, and thereby recites the step the provides the result. MPEP § 2111.04(I), see the discussion of the “wherein” clause for an intended/desired result.
Regarding Claim 14.
The method according to claim 1, wherein the measurements of contrast propagation velocity are based on a delay between bi-dimensional images.
Regarding Claim 14.
The method according to claim 1, further comprising updating the coupled model to take into account type of collateral flow in the coronary tree, wherein the type of collateral flow in the coronary tree is determined using densitometric image analysis and geometric information.
Claim 1, limitation (f)
Regarding Claim 15.
The method according to claim 1, further comprising updating at least one lumped parameter of the coupled model based on at least one of densitometric measurements and blush measurements.
Claim 1, limitation (f)
Then, see dependent claims 36-38
Regarding Claim 16.
The method according to claim 15, wherein the lumped parameter is based on a hydraulic-electrical analogue where blood pressure and flow rate is represented by voltage and current, respectively, and effects of friction in blood flow is represented by resistance.
Claim 1, limitation (f)
Then, see dependent claims 36-38
Regarding Claim 17.
The method according to claim 16, wherein the hydraulic-electrical analogue further includes capacitance that represents effects of inertia in blood flow.
Claim 1, limitation (f)
Then, see dependent claims 36-38
Regarding Claim 18.
The method according to claim 16, wherein the hydraulic-electrical analogue further includes inductance that represents effects of vessel elasticity.
Claim 1, limitation (f)
Then, see dependent claims 36-38
Regarding Claim 19.
The method according to claim 1, further comprising using at least one of densitometric measurements and blush measurements to add at least one 1D element to the coupled model.
Claim 1, limitation (f)
Regarding Claim 20.
The method according to claim 1, further comprising using at least one further parameter to update the coupled model, wherein the at least one further parameter is selected from the group consisting of:
wall motion of the left ventricle, coronary motion, information on the patient such as height, weight, gender, age, blood pressure.
Claim 1, limitation (f) then:
Regarding Claim 17.
The method according to claim 1, wherein the updating of the coupled model in f) is based on at least one further parameter selected from a second group consisting of:
wall motion of the left ventricle, coronary motion, patient information.
Regarding Claim 21.
The method according to claim 1, wherein the plurality of bi-dimensional images comprises X-ray angio-images taken from at least one perspective.
Regarding Claim 19.
The method according to claim 1, wherein the plurality of bi- dimensional images comprise X-ray angio images.
Regarding Claim 22.
The method according to claim 1, wherein the pressure drop equation of the reduced 3D model is a fitted equation for the region of interest that calculates a pressure drop for a given flow value.
Regarding Claim 24.
The method according to claim 1, wherein the equation of the reduced 3D model is a fitted equation for the region of interest that calculates the pressure drop for a given flow value.
Regarding Claim 23.
The method according to claim 1, wherein the quantitative flow analysis of g) solves the coupled model using aortic pressure as an inlet boundary condition.
Regarding Claim 25.
The method according to claim 1, wherein the quantitative flow analysis of g) solves the coupled model using aortic pressure as an inlet boundary condition.
Regarding Claim 23.
The X-ray imaging system according to claim 22, wherein the computer is further configured to read information on a rotational and angulation position of the imaging device for use in blush and densitometric measurements, wherein said information includes information on a delay between acquired bi-dimensional image frames with respect to frontal and lateral X-ray source of the imaging device.
Regarding Claim 24.
The method according to claim 1, wherein the quantitative flow analysis of g) calculates a parameter related to pressure difference across the region of interest.
Claim 1, then see claims 26-28
Regarding Claim 25.
The method according to claim 24, wherein the parameter represents a fractional flow reserve value for the region of interest.
Claim 1, then see claims 26-28
Regarding Claim 26.
The method according to claim 25, wherein the fractional flow reserve value is calculated directly or by adjusting the coupled model to simulate hyperemia state.
Claim 1, then see claims 26-28
Regarding Claim 27.
The method according to claim 1, wherein the region of interest is identified automatically or semi-automatically based on user input.
See claim 29
Regarding Claim 28.
The method according to claim 5, wherein the geometric features extracted from the 3D reconstruction comprise at least one feature of the conduits of the tree selected from the group consisting of diameter, length, curvature, and centerline.
Claim 1, limitation (d)
Regarding Claim 29.
The method according to claim 1, wherein the 1D model of a) is based on a standard 1 D model that is adjusted by patient specific data.
Claim 5
Regarding Claim 30.
The method according to claim 1, wherein the reduced 3D model for the region of interest is generated from geometric features of the 3D reconstruction of b).
Claim 1, limitations (a-c)
Regarding Claim 31.
A non-transitory computer-readable storage medium having stored thereon executable instructions that, when executed by one or more processors of a computer system, cause the computer system to perform quantitative flow analysis of a tree of conduits perfusing an organ of a patient from at least two bi- dimensional images of at least part of the tree obtained from different perspectives, by:
a) generating a one-dimensional (1D) model that is specific to the patient, wherein the 1D model includes a plurality of segments representing conduits of at least part of the tree of the patient, wherein fluid flow through the segments of the 1D model is governed by a one-dimensional, axisymmetric form of fluid equations;
b) generating a three-dimensional (3D) reconstruction for a subset of the tree of the patient;
c) identifying a region of interest within the 3D reconstruction which corresponds to a stenotic vessel segment belonging to the plurality of segments of the 1 D model, wherein the stenotic vessel segment has a narrowing or blockage of flow;
d) using the 3D reconstruction to construct a volumetric mesh for the subset of the tree of the patient corresponding to the region of interest;
e) using the volumetric mesh of d) in conjunction with computational fluid dynamic simulations to generate a reduced three-dimensional (3D) model for the region of interest, wherein the reduced 3D model consists of a pressure drop equation for the region of interest;
f) adding the reduced 3D model to the 1D model of a) as a coupling condition at the position in the 1 D model identified in c) to generate a coupled model;
and g) performing quantitative flow analysis using the coupled model of f).
Claim 20, with similar rationale as claim 1 above
Regarding Claim 32.
An X-ray imaging system comprising an imaging device for acquiring the plurality of bi-dimensional images that is operably coupled to a computer configured to perform the method of claim 1 to determine at least one fractional flow reserve value of a conduit of the at least part of the tree of the patient.
Claim 22
Regarding Claim 33.
An X-ray imaging system according to claim 32, wherein the computer is further configured to read information on rotational and angulation position of the imaging device for use in blush and densitometric measurements, wherein said information includes information on the delay between acquired image frames with respect to frontal and lateral X-ray source of the imaging device.
Claim 23
Regarding Claim 34.
The X-ray imaging system according to claim 32, wherein the computer is embodied in a cloud or high-performance computing cluster.
Claim 32
Regarding Claim 35.
The X-ray imaging system according to claim 32, further comprising an input device configured to receive user input, wherein the user input selects a predetermined 1 D model to be used in the flow analysis or specifies location of the region of interest within the 1 D model.
Claim 33
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
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/David A Hopkins/ Primary Examiner, Art Unit 2188