DETAILED ACTION
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 .
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).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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Claims 11-13 and 15-20 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 5-7, 10, 13, and 17 of U.S. Patent No. 9,349,178. Although the claims at issue are not identical, they are not patentably distinct from each other because the claims of the current application are broader than the claims of the conflicting patent. See the correspondence table below:
Current application 18/825,275
Conflicting patent 9,349,178
11
1
12
10
13
The claims of the conflicting patent do not recite “the change comprises a change from a congenital anomaly of a coronary artery”. However, Singer (U.S. Pub. No. 2015/0112901), as cited in the IDS filed 5 September 2024, discloses in [0054]: “In addition, inflow and outflow boundary conditions may be prescribed to compensate for underlying psychological or medical conditions such as pain, anxiety, fear, anemia, hyperthyroidism, left ventricular systolic dysfunction, left ventricular hypertrophy, hypertension or arterial-venous fistula”. The conflicting patent and Singer are directed to the same field of art (a machine learning system for estimating a characteristic of an inflow/outflow tract). Therefore, the conflicting patent and Singer are combinable. Modifying the claims of the conflicting patent by adding the capability to manage “change from a congenital anomaly of a coronary artery”, as taught by Singer, would yield the expected and predictable result of wider applicability. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the conflicting patent and Singer in this way.
15
5
16
10
17
5
18
6 + 7
19
10
20
13, 17
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 11, 12, 15-17, and 19 is/are rejected under 35 U.S.C. 102(a)(1) and (a)(2) as being anticipated by Sankaran et al. (U.S. Pub. No. 2014/0249784), hereinafter “Sankaran”, as cited in the IDS filed 5 September 2024.
Regarding claim 11, Sankaran teaches:
A method for hemodynamic determination in medical imaging (See the Abstract.), the method comprising:
acquiring medical scan data representing a vessel structure of a patient (See step 100 in Fig. 2 and [0026], where the patient-specific anatomical data of the aorta and the main coronary arteries meet the claimed medical scan data of a vessel structure of a patient.);
extracting a set of features from the medical scan data (See [0029], where inflow and outflow boundary conditions such as cardiac output, blood pressure and boundary conditions such as physical boundaries of the aorta and main coronary arteries are extracted.);
modifying a first of the features of the set, the modifying representing a change to the vessel structure due to therapy (See [0031], where boundary conditions assigned in step 300 of Fig. 2 are adjusted to model treatments such as placing a coronary stent in one of the coronary arteries.);
inputting, by a processor, the features to a machine-trained classifier, the features including the first feature after the modifying (See [0042], where fractional flow reserve values are obtained by the use of machine learning in method 600, depicted in Fig. 3.); and
outputting, by the processor with application of the machine-trained classifier, an indicator of a value of a hemodynamic metric based on the application of the features to the machine-trained classifier (See [0024]: “The equations 30 may be solved using a computer 40. Based on the solved equations, the computer 40 may output one or more images or simulations indicating information relating to the blood flow in the patient's anatomy represented by the model 10.” Again see [0042], where instead of using equations/physics-based simulations, machine learning is used.).
Regarding claim 12, Sankaran teaches:
The method of claim 11 wherein the change to the vessel structure comprises change from a stent or from therapy with a drug (See [0031], where boundary conditions assigned in step 300 of Fig. 2 are adjusted to model treatments such as placing a coronary stent in one of the coronary arteries.).
Regarding claim 15, Sankaran teaches:
The method of claim 11 wherein modifying comprises modifying the first and additional features of the features of the set (See [0031]: “For example, the three-dimensional model 10 created in step 200 and/or the boundary conditions assigned in step 300 may be adjusted to model one or more treatments, e.g., placing a coronary stent in one of the coronary arteries represented in the three-dimensional model 10 or other treatment options.” Multiple boundary conditions are modified, which meets “modifying the first and additional features”.).
Regarding claim 16, Sankaran teaches:
The method of claim 11 wherein modifying comprises modifying with the therapy resulting in less flow restriction than without the modifying (See [0031]: “For example, the three-dimensional model 10 created in step 200 and/or the boundary conditions assigned in step 300 may be adjusted to model one or more treatments, e.g., placing a coronary stent in one of the coronary arteries represented in the three-dimensional model 10 or other treatment options.” Placement of a stent results in less flow restriction than without placement.).
Regarding claim 17, Sankaran teaches:
The method of claim 11 wherein acquiring comprises acquiring with the medical scan data comprising a two or three-dimensional representation of the vessel structure (See [0027]: “A three-dimensional model of the patient's anatomy may be created based on the obtained anatomical data (step 200). For example, the three-dimensional model may be the three-dimensional model 10 of the patient's anatomy described above in connection with FIG. 1.”); and wherein extracting the set of the features comprises extracting geometrical and/or functional features of the vessel structure (See [0029], where inflow and outflow boundary conditions such as cardiac output, blood pressure and boundary conditions such as physical boundaries of the aorta and main coronary arteries are extracted.).
Regarding claim 19, Sankaran teaches:
The method of claim 11 wherein modifying the first feature comprises replacing a feature value corresponding to a flow restriction with a feature value corresponding to mitigation of the flow restriction, and wherein the synthetic data models the change from the flow restriction to the stent (See [0031]: “For example, the three-dimensional model 10 created in step 200 and/or the boundary conditions assigned in step 300 may be adjusted to model one or more treatments, e.g., placing a coronary stent in one of the coronary arteries represented in the three-dimensional model 10 or other treatment options.” Placement of a stent (represented by a change in feature value) results in mitigation of the flow restriction.).
Claim Rejections - 35 USC § 103
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sankaran (U.S. Pub. No. 2014/0249784) in view of Singer (U.S. Pub. No. 2015/0112901).
Claim 13 is met by the combination of Sankaran and Singer, wherein
Sankaran discloses:
The method of claim 11 wherein
Sankaran does not explicitly disclose the following; however, Singer discloses:
the change comprises a change from a congenital anomaly of a coronary artery (See [0054]: “In addition, inflow and outflow boundary conditions may be prescribed to compensate for underlying psychological or medical conditions such as pain, anxiety, fear, anemia, hyperthyroidism, left ventricular systolic dysfunction, left ventricular hypertrophy, hypertension or arterial-venous fistula”. ).
Sankaran and Singer together disclose the limitations of claim 13. Singer is directed to a similar field of art (a machine learning system for estimating a characteristic of an inflow/outflow tract). Therefore, Sankaran and Singer are combinable. Modifying Sankaran by adding the capability to represent a change from a congenital anomaly of a coronary artery, as taught by Singer, would yield the expected and predictable result of wider applicability of the Sankaran method/system. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine Sankaran and Singer in this way.
Claim(s) 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sankaran (U.S. Pub. No. 2014/0249784) in view of Fonte et al. (U.S. Pub. No. 2014/0073976), hereinafter “Fonte”, as cited in the IDS filed 5 September 2024.
Claim 18 is met by the combination of Sankaran and Fonte, wherein
Sankaran discloses:
The method of claim 11 wherein extracting the set of the features comprises
Sankaran does not explicitly disclose the following; however, Fonte suggests:
extracting an ischemic weight and an ischemic contribution score, the ischemic contribution score being a function of the ischemic weight (See [0047]: “The data may be processed using algorithms relating the patient's anatomy and characteristics to functional estimates of ischemia and blood flow. The algorithms may employ empirically derived models, machine learning, or analytical models relating blood flow to anatomy. Estimates of ischemia (blood flow, FFR, etc) may be generated for a specific location in a vessel, as an overall estimate for the vessel, or for an entire system of vessels such as the coronary arteries.” Then see [0045]: “It will be appreciated that any combination of those features, modified by any desired weighting scheme, may be incorporated into a machine learning algorithm executed according to the disclosed embodiments.”).
Sankaran and Fonte together disclose the limitations of claim 18. Fonte is directed to a similar field of art (individual-specific blood flow characteristic estimation). Therefore, Sankaran and Fonte are combinable. Modifying the system and method of Sankaran by adding the capability of “extracting an ischemic weight and an ischemic contribution score, the ischemic contribution score being a function of the ischemic weight”, as suggested by Fonte, would yield the expected and predictable result of wider applicability of the Sankaran method/system. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine Sankaran and Fonte in this way.
Allowable Subject Matter
Claims 1-10 are allowed. The prior art of record, individually or in combination, does not disclose or suggest in claim 1: “a processor configured to modify a first feature of the features from a first state to a therapeutically corrected state, to apply the features including the first feature as modified to a machine-trained predictor trained with training data of examples of vessels in the therapeutically corrected state”. Sankaran at [0042] only states: “Thus, in one embodiment, FFR values may be obtained by training a machine learning algorithm to estimate FFR values for various points of patient geometry based on feature vectors of patient physiological parameters and measured blood flow characteristics, and then applying the machine learning algorithm to a specific patient's geometry and physiological parameters to obtain predicted FFR values.” The applicant also comments on how Sankaran falls short on pages 7-8 of the Remarks filed 17 November 2015 within the file wrapper for U.S. application number 14/804,609. Dependent claims 2-10 include the limitations of claim 1 and are indicated as being allowable for those same limitations.
Claim 14 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Claim 20 is objected to as being dependent upon a rejected base claim, but would be allowable if (1) the double patenting rejections are overcome, and if (2) rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter: the prior art of record, individually or in combination, does not disclose or suggest in
claim 14: “the machine-trained classifier was trained with training data comprising synthetic examples that account for the therapy.” Sankaran at [0042] only states: “Thus, in one embodiment, FFR values may be obtained by training a machine learning algorithm to estimate FFR values for various points of patient geometry based on feature vectors of patient physiological parameters and measured blood flow characteristics, and then applying the machine learning algorithm to a specific patient's geometry and physiological parameters to obtain predicted FFR values.”
claim 20: “(i) an in vitro model with a ground truth of the hemodynamic metric measured form the in vitro model and/or (ii) in silico model with a ground truth of the hemodynamic metric computed with computation fluid dynamics; wherein the synthetic data comprises examples generated by regular variation of the in vitro model, the in silico model, or both the in vitro and in silico models, the synthetic data not representing any particular patient with perturbing computer modeling, physical modeling, or both in a systematic pattern.” Sharma et al. (U.S. Pub. No. 2015/0112182), as cited in the IDS filed 5 September 2024, discloses within the context of fractional flow reserve estimation, training a machine learning classifier using only synthetic data not specific to any patients in [0079]. However, this reference is excluded under the 35 U.S.C. 102(b)(2)(C) exception.
Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JONATHAN S LEE whose telephone number is (571)272-1981. The examiner can normally be reached 11:30 AM - 7:30 PM.
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/Jonathan S Lee/Primary Examiner, Art Unit 2677
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