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 .
Applicant filed a Reply on 01 June 2026 that:
Included replacement Fig. 10 that overcome the drawing objection;
Amended the claims to add a re-parameterizing step that, when considered in light of the persuasive arguments, overcomes the 35 USC 101 rejection;
Amended claim 1 to focus on fractional flow reserve (FFR) and second order estimates of FFR, which when considered in light of the arguments made in the 01 June 2026 Reply overcome the rejections under 35 USC 112(a) and (b) except for the 112(b) rejection of claim 10 which persists.
Response to Arguments
Applicant’s arguments with respect to claims 1 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. The arguments focus on M’hiri’s alleged lack of plural, independent processing pipelines applying analysis algorithms independently to respective 2D images and as further amended in the 01 June 2026 Reply. In response, see the newly applied art below the application which was necessitated by the amendments.
In regards to clarity of claim 10, Applicant argues that the specification provides ample context for the “deformation fields”, “views”, and “timestamps” such that one of ordinary skill in the art would understand these limitations. In response, the rejection at issue is 112(a) not 112(b). It is the claims that lack context, not the specification. Moreover, details of the specification will not be read into the claims.
Claim Rejections - 35 USC § 112
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 is 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.
Claim 10 recites “wherein the at least one similarity measure comprises a position-based similarity measure, wherein the position-based similarity measure is determined in accordance with deformation fields between at least one of views or timestamps associated with respective pairs of the images”. The recited use of the “deformation fields” is unclear and thus indefinite due in part to the lack of detailed context for the ”views” and “timestamps”. In other words, claim 10 lacks necessary context such as to which image features the “position-based similarity measure is determined”. The deformation fields also lack context and it is not clear if the deformation fields are between the views or between the timestamps themselves. It is also unclear if the deformation fields or the timestamps are associated with respective pairs of the images.
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.
Claims 1, 3-6, 8, 9, and 14-18 are rejected under 35 U.S.C. 103 as being unpatentable over M’hiri {M’hiri, Faten, et al. "Automatic evaluation of vessel diameter variation from 2D X-ray angiography." International Journal of Computer Assisted Radiology and Surgery 12.11 (2017): 1867-1876)} and Itu (US 20180310888 A1).
Claim 1
In regards to claim 1, M’hiri discloses a computer-implemented method {references are repeatedly made to “automatic methods” processing data-rich, complex 2D X-ray sequences such that that method is considered to be “computer implemented”}, comprising:
obtaining multiple two-dimensional images of an angiographic X-ray examination of a coronary system, for each one of the multiple two-dimensional images
{see abstract discussing monoplane 2D X-ray sequences for coronary arteries and Fig. 1, pg. 1869 Imaging Data}:
for each one of the multiple two-dimensional images: one or more analysis algorithms processing result, and computing a respective first-order estimate
{See generic computer/CPU used by M’hiri’s automatic method of vessel segmentation in Segmentation and Tracking of Artery section pgs. 1868-1869.
The automatic method of evaluating variation of vessel diameter from 2D X-ray angiographic image sequences as per pg. 1869, Measuring a Vessel’s Diameter, Fig. 4 includes vessel (artery lumen) segmentation which corresponds to the instant disclosure’s analysis algorithm that obtains a first order estimate (vessel segmentation) as per [0010] of the instant specification}, and
determining at least one second-order estimate
{the segmented vessels (first order estimates) from a temporal image sequence (thus, plural first order estimates) are consolidated by determining a mean vessel diameter over the whole image sequence by temporally averaging the diameters determined from the segmentation (first order estimate) for each image in the sequence and thus determines a second order estimate (means vessel diameter) from a consolidation (temporal averaging) of the first order estimates. Pg. 1868, 1869, 1870, Tables 1 and 2}; and
Itu is an analogous reference from the same field of analyzing 2D angiograms to performs various estimates and predictions. See abstract and cites below.
Itu also teaches
for each one of the multiple two-dimensional images: in a respective processing pipeline, applying one or more analysis algorithms independently to the respective one of the multiple two-dimensional images to extract at least one intermediate processing result, and computing a respective first-order estimate of a fractional flow reserve of the coronary system based on the at least one processing result
{See Fig. 8 (copied below) illustrating the application of conventional parallel processing pipeline architecture and processing to processing 2D angiographic X-ray images including extracting intermediate processing results to compute first order estimates of FFR (fractional flow reserve). See Figs. 1, 2, 3, 4, 6, 7 including extract features 120, 235-245, 410, 420, 730 from angiography, OCT, IVUS and extract features from hemodynamic measures of interest 745, and estimating FFR 125, 250, 420, [0036]-[0040] ML algorithms to estimate FFR in which the ML algorithms may be used in a cascaded or parallel workflow, [0063]-[0068]. Further as to respective processing pipelines see Fig. 8 parallel processing including multiple threads, [0022], [0070]-[0081] for- extracting features including coronary geometry, coronary artery trees, ACS related features, hemodynamic features such as FFS}
PNG
media_image1.png
562
778
media_image1.png
Greyscale
determining at least one second-order estimate of the fractional flow reserve from a consolidation of the first-order estimates of the fraction flow reserves obtained for each one of the multiple two-dimensional images {various second order estimates are determined such as the graph of FFS that consolidates the FFR first-order estimates over time that are obtained for each of the 2D angiograms, [0058]-[0059]. See also the predictions, risk of future events, and/or confidence interval that “consolidates” first-order estimates of the FFR, [0061], Fig. 7, [0064]-[0059]}
re-parameterizing the one or more analysis algorithms based on the determined at least one second-order estimate of the fractional flow reserve to improve an accuracy of the one or more analysis algorithms
{see Figs. 4 including adapting (re-parameterizing) the machine learning model [0055]-[0062], based on the estimates of FFR. See also Figs. 2, 3, 6, Offline Training which improves the accuracy of th7]e online prediction of the ML model, [0019], [0033]-[0034], [0040], [0050]-[0053], [0072] including patient-specific training and parallelized training of deep neural networks including consolidation and training in which multiple kernels execute to simulate different configurations simultaneously such as different viewpoints, lighting, textures, materials and effects}.
It 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 to have modified M’hiri which already discloses
for each one of the multiple two-dimensional images: applying one or more analysis algorithms to the respective one of the multiple two-dimensional images to extract at least one intermediate processing result, and computing a respective first-order estimate of the coronary system based on the at least one processing result
determining at least one second-order estimate from a consolidation of the first-order estimates obtained for each one of the multiple two-dimensional images;
such that the method/system employs conventional parallel processing techniques such that the analysis algorithms are independently applied in a respective processing pipeline as taught by Ito because such parallel processing is faster than serial processing and such that first-order estimate is a fractional flow reserve of the coronary system and the second order estimate is determined from a consolidation of first order estimates of the FFR as also taught by Itu and such that the system also re-parameterizing the one or more analysis algorithms based on the determined at least one second-order estimate of the fractional flow reserve to improve an accuracy of the one or more analysis algorithms as further taught by Itu because FFR is a highly conventional and indeed “gold standard for determining functional severity of a lesion” as motivated by Itu in [0005], because there is a reasonable expectation of success and/or because doing so merely combines prior art elements according to known methods to yield predictable results.
Claim 3
In regards to claim 3, M’hiri discloses wherein said consolidating is based on one or more comparative metrics that compare one or more data structures of the processing pipelines associated the multiple two-dimensional images
{the BRI (Broadest Reasonable Interpretation) of “comparative metric” includes a statistical analysis performed based on the results of first order estimates such as a median or mean value as per [0041], [0064]-[0070] of the instant specification as published. M’hiri consolidates the vessel diameters based on such a mean value “comparative metric” Pg. 1868, 1869, 1870, Tables 1 and 2. See also the identification of local deformations and distensibilities within the vessel, pg. 1868-9, that compares the local vessel diameter with the mean diameters of the relevant vessel segment.}.
Claim 4
In regards to claim 4, M’hiri discloses wherein the one or more data structures comprise the multiple two-dimensional images {see abstract discussing monoplane 2D X-ray sequences for coronary arteries and Fig. 1}.
Claim 5
In regards to claim 5, M’hiri discloses wherein the one or more data structures comprise at least one intermediate processing result of the one or more analysis algorithms
{see tracking an artery segment to assess vessel diameter changes over time to detect blood vessel anomalies, pg. 1869-70 in which the vessel diameter is an intermediate result that is tracked/compared over time to produce a consolidated second-order estimate. See also Materials and Methods including Segmentation and Tracking of a Section of Artery as different times (t), (t-1), etc. and Results in which diameter changes are tracked during systole and diastole cycles}.
Claim 6
In regards to claim 6, M’hiri discloses wherein the one or more data structures comprise the first-order estimates of the hemodynamic property
{the BRI (Broadest Reasonable Interpretation) of “comparative metric” includes a statistical analysis performed based on the results of first order estimates (data structures) such as a median or mean value as per [0041], [0064]-[0070] of the instant specification as published. M’hiri consolidates the vessel diameters based on such a mean value “comparative metric” Pg. 1868, 1869, 1870, Tables 1 and 2. See also the identification of local deformations and distensibilities within the vessel, pg. 1868-9, that compares the local vessel diameter with the mean diameters of the relevant vessel segment.}.
Claim 8
In regards to claim 8, M’hiri discloses wherein the one or more comparative metrics comprise a statistical analysis of a distribution of the first-order estimates of the hemodynamic property
{the BRI (Broadest Reasonable Interpretation) of “comparative metric” includes a statistical analysis performed based on the results of first order estimates (data structures) such as a median or mean value as per [0041], [0064]-[0070] of the instant specification as published. Moreover, a mean value is a statistical analysis of a distribution that calculates the mean value of the distribution. M’hiri consolidates the vessel diameters based on such a mean value “comparative metric” Pg. 1868, 1869, 1870, Tables 1 and 2}. See also the identification of local deformations within the vessel, pg. 1869, that compares the local vessel diameter with the mean diameters of the relevant vessel segment.}.
Claim 9
In regards to claim 9, M’hiri discloses wherein the one or more comparative metrics comprise at least one similarity measure between at least one of pairs of the first-order estimates of the hemodynamic properties or pairs of intermediate processing results of the one or more analysis algorithms.
{See also the identification of local deformations and distensibilities within the vessel which involve similarity measures between pairs of first order estimates (vessel diameters at various different locations), pg. 1868-9}.
Claim 14 and 16
In regards to claims 14 and 16, M’hiri discloses wherein the one or more analysis algorithms are single frame metrics that operate based on individual ones of the multiple two-dimensional images {M’hiri’s automatic method of evaluating vessel diameter variation from 2D X-ray angiographic image sequences as per pg. 1869, Measuring a Vessel’s Diameter, Fig. 4 operates on individual ones of plural 2D images}.
Claim 15 and 17
In regards to claims 15 and 17, M’hiri discloses
wherein the multiple two-dimensional images are associated with multiple views of the coronary system {see abstract discussing monoplane 2D X-ray sequences for coronary arteries and Fig. 1, pg. 1869 Imaging Data wherein multiple view of the coronary arteries are taken at different times (time-sequence of images).
Claims 2 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over M’hiri and Itu as applied to claim 1 above, and further in view of This (US 20240407656 A1).
Claim 2
In regards to claim 2, M’hiri is not relied upon to disclose wherein an intermediate processing result of the one or more analysis algorithms comprises a length of a vessel of the coronary system, wherein the length of the vessel is compensated with respect to a perspective foreshortening associated with a respective view of the respective two-dimensional image.
This is an analogous reference from the same field of analyzing angiographic x-ray images of a coronary system including vessel segmentation and calculating first and second order estimates. See abstract, [0001]-[0022] and cites below.
This also teaches wherein an intermediate processing result of the one or more analysis algorithms comprises a length of a vessel of the coronary system, wherein the length of the vessel is compensated with respect to a perspective foreshortening associated with a respective view of the respective two-dimensional image.
{See Figs. 15, 16, [0162]-[0166] including equation 13 that compensates the vessel segment length for foreshortening}.
It 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 to have modified M’hiri which already discloses various intermediate processing results such that wherein an intermediate processing result of the one or more analysis algorithms comprises a length of a vessel of the coronary system, wherein the length of the vessel is compensated with respect to a perspective foreshortening associated with a respective view of the respective two-dimensional image as taught by This because doing so increases the accuracy of vessel segment length as motivated by This in [0166], because there is a reasonable expectation of success and/or because doing so merely combines prior art elements according to known methods to yield predictable results.
Claim 18
In regards to claim 18, M’hiri discloses wherein said consolidating is based on one or more comparative metrics that compare one or more data structures of the processing pipelines associated the multiple two-dimensional images.
{M’hiri consolidates the vessel diameters based on such a mean value “comparative metric” Pg. 1868, 1869, 1870, Tables 1 and 2. See also the identification of local deformations and distensibilities within the vessel, pg. 1868-9, that compares the local vessel diameter with the mean diameters of the relevant vessel segment. See also the 112(b) rejection above}.
Claims 7 is rejected under 35 U.S.C. 103 as being unpatentable over M’hiri and Itu as applied to claim 3 above, and further in view of Schwemmer, C., et al. "CoroEval: a multi-platform, multi-modality tool for the evaluation of 3D coronary vessel reconstructions." Physics in medicine & biology 59.17 (2014): 5163.
Claim 7
In regards to claim 8, M’hiri discloses wherein the one or more comparative metrics comprise a statistical analysis of a distribution of the of the first-order estimates of the hemodynamic property, wherein the at least one second-order estimate of the hemodynamic property is determined based on
Schwemmer is an analogous reference from the same field of analyzing angiographic x-ray images of a coronary system including vessel segmentation and determining vessel sharpness and diameter (first order estimates). See abstract and Introduction.
Schwemmer also teaches wherein the one or more comparative metrics comprise a statistical analysis of a distribution of the of the first-order estimates of the hemodynamic property, wherein the at least one second-order estimate of the hemodynamic property is determined based on a most probable value of the distribution {see section 2.2 Segmentation, 3.1.4 Vessel diameter, and 3.2 discussing most probable vessel center calculation (second order estimate) using a statistical distribution of the first-order estimates}.
It 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 to have modified M’hiri which already discloses wherein the one or more comparative metrics comprise a statistical analysis of a distribution of the of the first-order estimates of the hemodynamic property, such that wherein the at least one second-order estimate of the hemodynamic property is determined based on a most probable value of the distribution as taught by Scwemmer because doing so increases the accuracy of centerline extraction and vessel segmentation as motivated by Schwemmer, because there is a reasonable expectation of success and/or because doing so merely combines prior art elements according to known methods to yield predictable results.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Frangi A, Niessen W, Vincken K, Viergever M (1998) Multiscale vessel enhancement filtering. In: Medical image computing and computer-assisted intervention MICCAI98, p 130.
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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Michael R Cammarata whose telephone number is (571)272-0113. The examiner can normally be reached M-Th 7am-5pm EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Bella can be reached at 571-272-7778. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MICHAEL ROBERT CAMMARATA/ Primary Examiner, Art Unit 2667
Prosecution Insights