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 .
Response to Amendment
The Amendment filed January 22, 2026 has been entered. Claims 21-40 remain pending in the application.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claims 21-40 are rejected under 35 U.S.C. 103 as being unpatentable over Anderson (US 2016/0157802 A1) (“Anderson”) in view of Choi et al. (US 2015/0164453 A1) (“Choi”).
Regarding claims 21, 32 and 39, Anderson discloses A computer-implemented method/system/non-transitory computer-readable medium of processing electronic images to identify relevant flow characteristics in a patient, the method comprising (Abstract and entire document):
a data storage device storing instructions for processing electronic images to identify relevant flow characteristics in a patient; and a processor configured to execute the instructions to perform operations comprising ([0043], “In some embodiments, the computing device 172 includes a processor, random access memory, and a storage medium.”):
receiving a patient-specific representation of at least a portion of vasculature of the patient, the at least a portion of the vasculature comprising at least one lesion (FIG. 5-8 and associated paragraphs, see at least [0051], “The image-based physiologic measurements may include a dominance classification, a degree of occlusion of a lesion, which may be expressed as a percent diameter stenosis, a classification of a lesion, a degree of bending of a vessel of the vessel system, a length of a lesion, and/or a degree of calcification of a lesion.”);
determining or receiving values for one or more metrics of interest associated with one or more locations in the patient-specific representation (FIG. 5-8 and associated paragraphs, see at least [0051], “The image-based physiologic measurements may include a dominance classification, a degree of occlusion of a lesion, which may be expressed as a percent diameter stenosis, a classification of a lesion, a degree of bending of a vessel of the vessel system, a length of a lesion, and/or a degree of calcification of a lesion.” And [0052], “After obtaining the angiogram data, the data may be parsed by an image-processing component provided by the system 150 of FIG. 4 to segment the patient's vasculature and estimate certain features thereof. The parsing of the data may be performed to extract image-based physiologic measurements that may be provided to a risk calculator to generate a disease quantification score.”);
determining a diseased region in the at least a portion of the vasculature of the patient based on the values for the one or more metrics of interest (FIG. 5-8 and associated paragraphs, see at least [0051], “The image-based physiologic measurements may include a dominance classification, a degree of occlusion of a lesion, which may be expressed as a percent diameter stenosis, a classification of a lesion, a degree of bending of a vessel of the vessel system, a length of a lesion, and/or a degree of calcification of a lesion.” And [0052], “After obtaining the angiogram data, the data may be parsed by an image-processing component provided by the system 150 of FIG. 4 to segment the patient's vasculature and estimate certain features thereof. The parsing of the data may be performed to extract image-based physiologic measurements that may be provided to a risk calculator to generate a disease quantification score.”);
determining at least one first position proximal to the diseased region and at least one second position distal to the diseased region (As shown in FIG. 8A, the diseased region is 802, distal and proximal positions are marked as 836, 832, 814, 838, etc. See further FIG. 7 and [0066], discussing marking for bifurcations and branching)
generating a visualization of at least the diseased region, the visualization including markers illustrating the first position and second position (As shown in FIG. 8A, the diseased region is 802, distal and proximal positions are marked as 836, 832, 814, 838, etc. See further FIG. 7 and [0066], discussing marking for bifurcations and branching).
Anderson fails to explicitly disclose determining at least one first position proximal to the diseased region and at least one second position distal to the diseased region at least in part by automatically determining a proximity of the diseased region to a bifurcation, a proximity of the diseased region to a non-pinnable location, and/or a proximity of the diseased region to a second diseased region
However, in the same field of endeavor, Choi teaches determining at least one first position proximal to the diseased region and at least one second position distal to the diseased region at least in part by automatically determining a proximity of the diseased region to a bifurcation, a proximity of the diseased region to a non-pinnable location, and/or a proximity of the diseased region to a second diseased region, wherein determining the at least one first position and the at least one second position includes identifying locations at which one or more anatomically relevant metrics transition from values indicative of the diseased region to values indicative of non-diseased vasculature based on the automatically determined proximity ([0082], “Characteristics of coronary lesion, e.g., minimum lumen area, minimum lumen diameter, degree of stenosis at lesion (percentage diameter/area stenosis), e.g., by determining virtual reference area profile by using Fourier smoothing or kernel regression, and/or computing percentage stenosis of lesion using the virtual reference area profile along the vessel centerline; location of stenotic lesions, such as by computing the distance (parametric arc length of centerline) from the main ostium to the start or center of the lesion; length of stenotic lesions, such as by computing the proximal and distal locations from the stenotic lesion, where cross-sectional area is recovered; and/or irregularity (or circularity) of cross-sectional lumen boundary.” See also [0091] discussing location to bifurcation. A length or area of the lesion including to a first position and second position, where it transitions from diseased to non-diseased based on automatic proximity detection to the bifurcation, calculated based at least in part on a distance to a bifurcation or other known features)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify the computer-implemented method/system/non-transitory computer-readable medium as taught by Anderson to include determining at least one first position proximal to the diseased region and at least one second position distal to the diseased region at least in part by automatically determining a proximity of the diseased region to a bifurcation, a proximity of the diseased region to a non-pinnable location, and/or a proximity of the diseased region to a second diseased region as taught by Choi to assist in guiding therapy ([0028], “The present disclosure is directed to a new approach for providing prognosis of adverse cardiac events and for guiding medical therapy based on patient-specific geometry and blood flow characteristics. Although the present disclosure is described with respect to coronary artery disease, the same system is applicable to creating a patient-specific prediction of rupture risks in other vascular systems beyond the coronary arteries, such as the carotid artery.”).
Regarding claims 22 and 33, Anderson as modified discloses The computer-implemented method of claim 21, Anderson as modified further discloses further comprising: receiving one or more observed lumen measurements of the at least a portion of the vasculature of the patient (Anderson FIG. 5-8 and associated paragraphs, see at least [0051], “The image-based physiologic measurements may include a dominance classification, a degree of occlusion of a lesion, which may be expressed as a percent diameter stenosis, a classification of a lesion, a degree of bending of a vessel of the vessel system, a length of a lesion, and/or a degree of calcification of a lesion.” And [0052], “After obtaining the angiogram data, the data may be parsed by an image-processing component provided by the system 150 of FIG. 4 to segment the patient's vasculature and estimate certain features thereof. The parsing of the data may be performed to extract image-based physiologic measurements that may be provided to a risk calculator to generate a disease quantification score.”); and
determining the diseased region in the at least a portion of the vasculature of the patient based on the one or more observed lumen measurements (Anderson FIG. 5-8 and associated paragraphs, see at least [0051], “The image-based physiologic measurements may include a dominance classification, a degree of occlusion of a lesion, which may be expressed as a percent diameter stenosis, a classification of a lesion, a degree of bending of a vessel of the vessel system, a length of a lesion, and/or a degree of calcification of a lesion.” And [0052], “After obtaining the angiogram data, the data may be parsed by an image-processing component provided by the system 150 of FIG. 4 to segment the patient's vasculature and estimate certain features thereof. The parsing of the data may be performed to extract image-based physiologic measurements that may be provided to a risk calculator to generate a disease quantification score.”).
Regarding claims 23, 34 and 40, Anderson as modified discloses The computer-implemented method of claim 22, Anderson as modified further discloses wherein determining the diseased region further comprises: predicting or receiving one or more healthy lumen measurements of the vasculature of the patient (Anderson FIG. 5-8 and associated paragraphs, see at least [0051], “The image-based physiologic measurements may include a dominance classification, a degree of occlusion of a lesion, which may be expressed as a percent diameter stenosis, a classification of a lesion, a degree of bending of a vessel of the vessel system, a length of a lesion, and/or a degree of calcification of a lesion.” And [0052], “After obtaining the angiogram data, the data may be parsed by an image-processing component provided by the system 150 of FIG. 4 to segment the patient's vasculature and estimate certain features thereof. The parsing of the data may be performed to extract image-based physiologic measurements that may be provided to a risk calculator to generate a disease quantification score.”);
generating a lumen narrowing score based on the one or more observed lumen measurements and the predicted or received one or more healthy lumen measurements of the vasculature of the patient (Anderson FIG. 5-8 and associated paragraphs, see at least [0051], “The image-based physiologic measurements may include a dominance classification, a degree of occlusion of a lesion, which may be expressed as a percent diameter stenosis, a classification of a lesion, a degree of bending of a vessel of the vessel system, a length of a lesion, and/or a degree of calcification of a lesion.” And [0052], “After obtaining the angiogram data, the data may be parsed by an image-processing component provided by the system 150 of FIG. 4 to segment the patient's vasculature and estimate certain features thereof. The parsing of the data may be performed to extract image-based physiologic measurements that may be provided to a risk calculator to generate a disease quantification score.”); and
determining a location of the diseased region based on the generated lumen narrowing score (Anderson FIG. 5-8 and associated paragraphs, see at least [0051], “The image-based physiologic measurements may include a dominance classification, a degree of occlusion of a lesion, which may be expressed as a percent diameter stenosis, a classification of a lesion, a degree of bending of a vessel of the vessel system, a length of a lesion, and/or a degree of calcification of a lesion.” And [0052], “After obtaining the angiogram data, the data may be parsed by an image-processing component provided by the system 150 of FIG. 4 to segment the patient's vasculature and estimate certain features thereof. The parsing of the data may be performed to extract image-based physiologic measurements that may be provided to a risk calculator to generate a disease quantification score.”).
Regarding claims 24 and 35, Anderson as modified discloses The computer-implemented method of claim 23, Anderson as modified further discloses wherein predicting one or more healthy lumen measurements further comprises: forming a plurality of regressors based on one or more of the observed lumen measurements and/or the determined diseased region; determining one or more parameter values for each of the plurality of regressors; and performing a kernel regression of the plurality of regressors associated with the diseased region to predict the one or more healthy lumen measurements (Choi [0082], “Characteristics of coronary lesion, e.g., minimum lumen area, minimum lumen diameter, degree of stenosis at lesion (percentage diameter/area stenosis), e.g., by determining virtual reference area profile by using Fourier smoothing or kernel regression, and/or computing percentage stenosis of lesion using the virtual reference area profile along the vessel centerline”).
Regarding claims 25 and 36, Anderson as modified discloses The computer-implemented method of claim 21, Anderson as modified further discloses wherein the first position and the second position are set at a fixed distance from the diseased region when there is no bifurcation, non-pinnable location, or second diseased region within a set distance of the diseased region (Anderson As shown in FIG. 8A, the diseased region is 802, distal and proximal positions are marked as 836, 832, 814, 838, etc. See further FIG. 7 and [0066], discussing marking for bifurcations and branching).
Regarding claim 26, Anderson as modified discloses The computer-implemented method of claim 21, Anderson as modified further discloses further comprising: determining a lumen narrowing score; and determining an acuity of the diseased region using the lumen narrowing score (Anderson FIG. 5-8 and associated paragraphs, see at least [0051], “The image-based physiologic measurements may include a dominance classification, a degree of occlusion of a lesion, which may be expressed as a percent diameter stenosis, a classification of a lesion, a degree of bending of a vessel of the vessel system, a length of a lesion, and/or a degree of calcification of a lesion.” And [0052], “After obtaining the angiogram data, the data may be parsed by an image-processing component provided by the system 150 of FIG. 4 to segment the patient's vasculature and estimate certain features thereof. The parsing of the data may be performed to extract image-based physiologic measurements that may be provided to a risk calculator to generate a disease quantification score.”).
Regarding claim 27, Anderson as modified discloses The computer-implemented method of claim 21, Anderson as modified further discloses wherein the markers illustrating the first position and second position comprise moveable pins (Anderson [0075], “In that regard, value indicators 804 can be disposed adjacent to markers 802 to indicate the location within the patient's vasculature to which the measurement corresponds. In other embodiments, value indicators 804 are displayed further away from markers 802, but an additional visual element (e.g., an arrow, a straight line, a curved line, marker 802 and value indicator 804 are the same or similar colors, etc.) is provided to indicate the location of the measurement. In some embodiments, the value indicators 804 include only the value of the physiological measurement (e.g., “0.96”), while in other embodiments, the value indicators 804 include the value and type of physiological measurement (e.g., “0.95 FFR”). In yet other embodiments, additional information, such as the time the measurement was taken, severity of the stenosis or lesion, etc. can also be provided. For example, a user may provide a user input (e.g., a selection from a drop-down menu, toggle through the available options, etc.) selecting the types of information that should be displayed in value indicators 804. Labels 806, for each of the value indicators 804, can also be provided. Labels 806 can include alphabetical, numeric, and/or other symbolic characters. Labels 806 may assist in identifying markers 802 and/or value indicators 804 (e.g., to distinguish between different markings/value indicators and/or to facilitate discussion of the vessel depictions).”).
Regarding claim 28, Anderson as modified discloses The computer-implemented method of claim 27, Anderson as modified further discloses further comprising: providing interactive options to change in display features, range, magnification, or angle of the visualization of the diseased region (Anderson [0075], “In that regard, value indicators 804 can be disposed adjacent to markers 802 to indicate the location within the patient's vasculature to which the measurement corresponds. In other embodiments, value indicators 804 are displayed further away from markers 802, but an additional visual element (e.g., an arrow, a straight line, a curved line, marker 802 and value indicator 804 are the same or similar colors, etc.) is provided to indicate the location of the measurement. In some embodiments, the value indicators 804 include only the value of the physiological measurement (e.g., “0.96”), while in other embodiments, the value indicators 804 include the value and type of physiological measurement (e.g., “0.95 FFR”). In yet other embodiments, additional information, such as the time the measurement was taken, severity of the stenosis or lesion, etc. can also be provided. For example, a user may provide a user input (e.g., a selection from a drop-down menu, toggle through the available options, etc.) selecting the types of information that should be displayed in value indicators 804. Labels 806, for each of the value indicators 804, can also be provided. Labels 806 can include alphabetical, numeric, and/or other symbolic characters. Labels 806 may assist in identifying markers 802 and/or value indicators 804 (e.g., to distinguish between different markings/value indicators and/or to facilitate discussion of the vessel depictions).”).
Regarding claim 29, Anderson as modified discloses The computer-implemented method of claim 21, Anderson as modified further discloses further comprising: enabling an assessment of treatment options for the diseased region (Anderson [0062], “By comparing the calculated pressure differential to a threshold or predetermined value, a physician or other treating medical personnel can determine what, if any, treatment should be administered. In that regard, in some instances, a calculated pressure differential above a threshold value (e.g., 0.80 on a scale of 0.00 to 1.00) is indicative of a first treatment mode (e.g., no treatment, drug therapy, etc.), while a calculated pressure differential below the threshold value is indicative of a second, more invasive treatment mode).
Regarding claim 30, Anderson as modified discloses The computer-implemented method of claim 21, Anderson as modified further discloses wherein the metrics of interest comprise one or more of: a function of fractional flow reserve (FFR), including FFR, distal point of FFR recovery, or a delta or change in FFR; an instant wave free ratio (iFR); a coronary flow reserve (CFR); an anatomical characteristic including one or more of a vessel size or vessel thickness; a plaque characteristic including one or more of a local calcium score, local low intensity plaque score, a measure of spotty calcification, a remodeling index, and/or an indicia of plaque signs; a radiodensity; and/or a blood flow characteristic including one or more of a blood flow rate or velocity, or a blood pressure (Anderson [0041], “FFR”, “ifr”, [0049], “CFR”).
Regarding claim 31, Anderson as modified discloses The computer-implemented method of claim 22, Anderson as modified further discloses wherein lumen measurements of the vasculature of the patient comprise one or more of a radius, a diameter, an area, a circumference, a length, one or both elliptical radii, a torsion of the lumen, or a minima or maxima of the above (Anderson FIG. 5-8 and associated paragraphs, see at least [0051], “The image-based physiologic measurements may include a dominance classification, a degree of occlusion of a lesion, which may be expressed as a percent diameter stenosis, a classification of a lesion, a degree of bending of a vessel of the vessel system, a length of a lesion, and/or a degree of calcification of a lesion.”).
Regarding claim 37, Anderson as modified discloses The system of claim 32, Anderson as modified further discloses wherein the visualization of the diseased region comprises: displaying the values of one or more metrics of interest associated with one or more locations in the location of the diseased region, and at the first position and second position; and enabling the visualization of the one or more metrics of interest in one or more of a table, graph, histogram, or movable visual pin (Anderson FIG. 5-8 and [0075], “In that regard, value indicators 804 can be disposed adjacent to markers 802 to indicate the location within the patient's vasculature to which the measurement corresponds. In other embodiments, value indicators 804 are displayed further away from markers 802, but an additional visual element (e.g., an arrow, a straight line, a curved line, marker 802 and value indicator 804 are the same or similar colors, etc.) is provided to indicate the location of the measurement. In some embodiments, the value indicators 804 include only the value of the physiological measurement (e.g., “0.96”), while in other embodiments, the value indicators 804 include the value and type of physiological measurement (e.g., “0.95 FFR”). In yet other embodiments, additional information, such as the time the measurement was taken, severity of the stenosis or lesion, etc. can also be provided. For example, a user may provide a user input (e.g., a selection from a drop-down menu, toggle through the available options, etc.) selecting the types of information that should be displayed in value indicators 804. Labels 806, for each of the value indicators 804, can also be provided. Labels 806 can include alphabetical, numeric, and/or other symbolic characters. Labels 806 may assist in identifying markers 802 and/or value indicators 804 (e.g., to distinguish between different markings/value indicators and/or to facilitate discussion of the vessel depictions).”).
Regarding claim 38, Anderson as modified discloses The system of claim 37, Anderson as modified further discloses the operations further comprising: enabling a toggling of the display of one or more metrics of interest; enabling a change in a range, magnification, or angle of the vasculature to be displayed; and modifying the display of the values of the one or more metrics of interest, as a result of the enabled change (Anderson FIG. 5-8 and [0075], “In that regard, value indicators 804 can be disposed adjacent to markers 802 to indicate the location within the patient's vasculature to which the measurement corresponds. In other embodiments, value indicators 804 are displayed further away from markers 802, but an additional visual element (e.g., an arrow, a straight line, a curved line, marker 802 and value indicator 804 are the same or similar colors, etc.) is provided to indicate the location of the measurement. In some embodiments, the value indicators 804 include only the value of the physiological measurement (e.g., “0.96”), while in other embodiments, the value indicators 804 include the value and type of physiological measurement (e.g., “0.95 FFR”). In yet other embodiments, additional information, such as the time the measurement was taken, severity of the stenosis or lesion, etc. can also be provided. For example, a user may provide a user input (e.g., a selection from a drop-down menu, toggle through the available options, etc.) selecting the types of information that should be displayed in value indicators 804. Labels 806, for each of the value indicators 804, can also be provided. Labels 806 can include alphabetical, numeric, and/or other symbolic characters. Labels 806 may assist in identifying markers 802 and/or value indicators 804 (e.g., to distinguish between different markings/value indicators and/or to facilitate discussion of the vessel depictions).”).
Response to Arguments
Applicant's arguments filed January 22, 2026 have been fully considered but they are not persuasive. With respect to the arguments regarding the 103 rejections, the arguments are not persuasive.
As an initial matter, the arguments state the amendments are made to claims 21, 32 and 39, however they are not made to independent claims 32 and 39. Thus, the arguments regarding claims 32 and 39 are moot.
With respect to the arguments regarding the 103 rejections of claim 21 and Anderson in view of Choi, the arguments are not persuasive. The arguments state that Choi fails to disclose “determining at least one first position proximal to the diseased region and at least one second position distal to the diseased region at least in part by automatically determining a proximity of the diseased region to a bifurcation, a proximity of the diseased region to a non-pinnable location, and/or a proximity of the diseased region to a second diseased region, wherein determining the at least one first position and the at least one second position includes identifying locations at which one or more anatomically relevant metrics transition from values indicative of the diseased region to values indicative of non-diseased vasculature based on the automatically determined proximity”.
However, Choi discloses [0082], “Characteristics of coronary lesion, e.g., minimum lumen area, minimum lumen diameter, degree of stenosis at lesion (percentage diameter/area stenosis), e.g., by determining virtual reference area profile by using Fourier smoothing or kernel regression, and/or computing percentage stenosis of lesion using the virtual reference area profile along the vessel centerline; location of stenotic lesions, such as by computing the distance (parametric arc length of centerline) from the main ostium to the start or center of the lesion; length of stenotic lesions, such as by computing the proximal and distal locations from the stenotic lesion, where cross-sectional area is recovered; and/or irregularity (or circularity) of cross-sectional lumen boundary.” See also [0091] discussing location to bifurcation. A length or area of the lesion including to a first position and second position, where it transitions from diseased to non-diseased based on automatic proximity detection to the bifurcation, calculated based at least in part on a distance to a bifurcation or other known features. Applicant however argues that Choi fails to disclose the markers at the first and second locations. However, Anderson discloses the markers.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). Anderson, as shown in FIG. 8A, the diseased region is 802, distal and proximal positions are marked as 836, 832, 814, 838, etc. See further FIG. 7 and [0066], discussing marking for bifurcations and branching. Choi teaches the automatic identification at least partially based on a location to a bifurcation, assisting in the location markers of Anderson as a combination teaching. Thus, the arguments are not persuasive.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOSEPH A TOMBERS whose telephone number is (571)272-6851. The examiner can normally be reached on M-TH 7:00-16:00, F 7:00-11:00(Eastern).
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/J.A.T./Examiner, Art Unit 3791
/TSE W CHEN/ Supervisory Patent Examiner, Art Unit 3791
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