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 Arguments
Applicant's arguments filed 20 November 2025 have been fully considered but they are not persuasive. Regarding amended claim 1, applicant argues that the cited prior art does not disclose “identifying one or more immune cell regions or one or more interstitial fibers within myocardial tissue of the one or more EMB images”. See Arguments at 8-9. Specifically, applicant acknowledges that Nirschl uses techniques to extract features from ROIs (Id. at 8) and discloses the use of transmural tissues from the left ventricular free wall (Id. at 9), but argues that Nirschl does not “disclose any identification of immune cell regions or interstitial fibers”. Id. at 8. Further, applicant acknowledges that Peyster discloses “detect[ing] and phenotyp[ing] individual cells, such as CD3+, CD8+, CD68+, and FoxP3+ cells” but argues that “[t]he method is directed toward single-cell detection and not to the identification of one or more immune cell regions. Id. at 8-9. Applicant’s arguments are not persuasive in this regard.
Initially, regarding the citation of the Nirschl reference, it is noted that regions of interest are identified/extracted (Nirschl at 3) of the transmural tissues depict fibrosis (Nirschl at 5, 7). These identified ROIs depict interstitial fibers (Nirschl page 6, see Figure 2) and fibrosis relates to thickening/scarring of a collection of those fibers. Consequently, identifying the ROI of these fibers constitutes “identifying one or more…interstitial fibers within myocardial tissue” as recited in claim 1. Applicant attempts to distinguish this limitation from the cited regions of interstitial fibers by arguing that “these ROIs are simply uniform rectangular patches, not anatomical, morphological, or histologically meaningful “regions”. Arguments at 8. However, the claim, as presently constructed, does not require that identified regions/fibers have any anatomical, morphological, or histological meaning, just that they are of interstitial fibers (or immune cell regions). Therefore, applicant’s arguments to the contrary are not persuasive.
Regarding the citation of the Peyster reference, it is noted that the cells applicant acknowledges Peyster identifies using fluorescent markers (CD3+, CD8+, CD68+, and FoxP3+) are immune cells. Contrary to applicant’s assertion, the system does not merely identify a single immune cell, but tracks, within the tissue, a collection of immune cells with fluorescent markers within a region via that underwent quantitative analysis. See Peyster at 333. Further, even assuming arguendo that Peyster relates to identifying “individual cells”, such an identification would constitute “identifying one or more immune cell regions” as recited in claim 1. Applicant’s arguments to the contrary are, therefore, found not persuasive in this regard.
Allowable Subject Matter
Claim 5 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. Reasons for allowance will be provided in the event the application becomes in condition for allowance.
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.
Claim(s) 1, 3,4, 6, 9-12, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Nirschl (“A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue”, copy provided, see PTO-892) in view of Peyster (“In Situ Immune Profiling of Heart Transplant Biopsies Improves Diagnostic Accuracy and Rejection Risk Stratification”, copy provided, see PTO-892).
Regarding claim 1, Nirschl (“A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue”, copy provided, see PTO-892) discloses:
A non-transitory computer-readable medium storing computer- executable instructions that, when executed, cause a processor to perform operations, comprising:
obtaining one or more digitized endomyocardial biopsy (EMB) images from a patient having had a heart transplant (pages 10-11, EMB images for image analysis from heart transplant recipients)
identifying one or more immune cell regions or more interstitial fibers within myocardial tissue of the one or more digitized EMB images (see, for example, page 11, where transmural tissues from the left ventricular free wall is used));
extracting a plurality of histological features from the one or more digitized EMB images (pages 9-12, image analysis extracts features from ROIs including texture, color, etc.; histopathology is used in a CNN classifier), wherein the plurality of histological features are associated with the one or more immune cell regions or the one or more interstitial fibers (see, for example, page 11, where transmural tissues from the left ventricular free wall is used));
applying a machine learning predictive model to operate on the plurality of histological features to generate a prediction for the patient, wherein the prediction comprises a grade or a clinical trajectory associated with the patient (pages 9-10, a CNN classifier uses the features to assign a probability of heart failure)
Even assuming arguendo that Nirschl does not explicitly disclose:
extracting a plurality of histological features from the one or more digitized EMB images
Peyster et al. (“In Situ Immune Profiling of Heart Transplant Biopsies Improves Diagnostic Accuracy and Rejection Risk Stratification”, copy attached, see PTO-892) discloses:
obtaining one or more digitized endomyocardial biopsy (EMB) images from a patient having had a heart transplant (Visual Abstract, pages 328, 331, multispectral EMB tissue images are acquired)
identifying one or more immune cell regions or more interstitial fibers within myocardial tissue of the one or more digitized EMB images (see, for example, page 333 detailing the immunophenotyping on immune cells)
extracting a plurality of histological features from the one or more digitized EMB images (pages 332-333, various markers from the EMB images are determined) wherein the plurality of histological features are associated with the one or more immune cell regions or the one or more interstitial fibers (see, for example, page 333 detailing the immunophenotyping on immune cells)
applying a machine learning predictive model to operate on the plurality of histological features to generate a prediction for the patient, wherein the prediction comprises a grade or a clinical trajectory associated with the patient (pages 333-334, the histological features are used to assess whether patients will suffer rejection events in the future vs. patients who will not)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the system of Peyster et al. with the system of Nirschl such that the system would have been configured to extracting a plurality of histological features from the one or more digitized EMB images as described in Peyster. The suggestion/motivation would have been in order to implement a system capable of “improv[ing] the diagnostic and prognostic value of allograft EMB specimens” (page 334 of the Peyster reference).
Regarding claim 3, the combination of Nirschl and Peyster et al. discloses the medium of the parent claim (claim 2).
Peyster additionally discloses:
wherein the one or more immune cell regions comprise one or more of lymphocytes, lymphocyte foci, and lymphocyte clusters (see, for example, page 336, CD3+, CD8+, etc.)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the system of Peyster et al. with the system of Nirschl such that the system would have been configured to identifying one or more immune cell regions, including lymphocytes, of the one or more digitized EMB images, wherein the plurality of histological features are associated with the one or more immune cell regions as described in Peyster. The suggestion/motivation would have been in order to implement a system capable of “improv[ing] the diagnostic and prognostic value of allograft EMB specimens” (page 334 of the Peyster reference).
Regarding claim 4, the combination of Nirschl and Peyster et al. discloses the medium of the parent claim (claim 1).
Peyster additionally discloses:
wherein the plurality of histological features comprise one or more of a number of lymphocytes, a spatial arrangement of lymphocytes, a shape of one or more interstitial fibers, and an orientation of one or more interstitial fibers (see, for example, page 336, Table 4, the amount of various lymphocyte markers is used as a predictor of clinical rejection)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the system of Peyster et al. with the system of Nirschl such that the system would have been such that the plurality of histological features comprised one or more of a number of lymphocytes, as described in Peyster. The suggestion/motivation would have been in order to implement a system capable of “improv[ing] the diagnostic and prognostic value of allograft EMB specimens” (page 334 of the Peyster reference).
Regarding claim 6, the combination of Nirschl and Peyster et al. discloses the medium of the parent claim (claim 1).
Peyster additionally discloses:
wherein the plurality of histological features comprise one or more of:
features quantifying a number of lymphocyte foci in different tissue compartments;
size or density statistics for lymphocyte clusters (see, for example, page 336, Table 4, the amount of various lymphocyte markers is used as a predictor of clinical rejection)
spatial or edge interactions of lymphocyte clusters or lymphocyte foci.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the system of Peyster et al. with the system of Nirschl such that the system would have been such that the plurality of histological features comprised one or more of a number of lymphocytes, as described in Peyster. The suggestion/motivation would have been in order to implement a system capable of “improv[ing] the diagnostic and prognostic value of allograft EMB specimens” (page 334 of the Peyster reference).
Regarding claim 9, Nirschl additionally discloses:
providing trajectory labels for the one or more digitized EMB images, wherein the trajectory labels describe clinical outcomes of the patient associated with one or more digitized EMB images (page 12, training images were ground truth labelled for the clinical outcome); and
utilizing the trajectory labels to validate the prediction (page 12, the classifier is evaluated based on a separate evaluation of the training dataset, grouped by patient, with images and ground truth labels)
Regarding claim 10, Nirschl additionally discloses:
wherein the plurality of histological features relate to interstitial stromal fibers (page 12, patients with heart failure have an expansion of cellular and acellular stromal tissue))
Regarding claim 11, the combination of Nirschl and Peyster et al. discloses the medium of the parent claim (claim 1).
Peyster additionally discloses:
wherein the plurality of histological features are associated with lymphocytes in a myocardial compartment and not with lymphocytes within an endocardial compartment (see, for example, page 336, Table 4, the amount of various lymphocyte markers is used as a predictor of clinical rejection; see pages 5-7, imaging of myocardium)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the system of Peyster et al. with the system of Nirschl such that the system would have been such that the plurality of histological features comprised one or more of a number of lymphocytes, as described in Peyster. The suggestion/motivation would have been in order to implement a system capable of “improv[ing] the diagnostic and prognostic value of allograft EMB specimens” (page 334 of the Peyster reference).
Regarding claim 12, the combination of Nirschl and Peyster et al. discloses the medium of the parent claim (claim 1).
Nirschl additionally discloses:
obtaining an additional digitized EMB image of an additional patient; (pages 10-11, EMB images for image analysis from heart transplant recipients; the recitation of “additional” merely amounts to using the disclosed functions an additional time)
segmenting the additional digitized EMB image to identify one or more additional immune cell regions or one or more additional interstitial fibers (see, for example, page 9 regarding the segmenting of relevant biological structures; the recitation of “additional” merely amounts to using the disclosed functions an additional time)
extracting a plurality of additional histological features from the one or more additional immune cell regions or the one or more additional interstitial fibers (pages 9-12, image analysis extracts features from ROIs including texture, color, etc.; histopathology is used in a CNN classifier; page 12, patients with heart failure have an expansion of cellular and acellular stromal tissue; the recitation of “additional” merely amounts to using the disclosed functions an additional time); and
applying the machine learning predictive model to the plurality of additional histological features to determine an additional prediction of the additional patient (pages 9-10, a CNN classifier uses the features to assign a probability of heart failure; the recitation of “additional” merely amounts to using the disclosed functions an additional time)
Even assuming arguendo that Nirschl does not explicitly disclose:
extracting a plurality of histological features from the one or more digitized EMB images
Peyster et al. additionally discloses:
obtaining an additional digitized EMB image of an additional patient (Visual Abstract, pages 328, 331, multispectral EMB tissue images are acquired; the recitation of “additional” merely amounts to using the disclosed functions an additional time)
segmenting the additional digitized EMB image to identify one or more additional immune cell regions (see page 332 regarding cell segmentation)
extracting a plurality of additional histological features from the one or more additional immune cell regions (pages 332-333, various markers from the EMB images are determined; see, for example, page 333 detailing the immunophenotyping on immune cells; the recitation of “additional” merely amounts to using the disclosed functions an additional time)
applying a machine learning predictive model to operate on the plurality of histological features to generate a prediction for the patient, wherein the prediction comprises a grade or a clinical trajectory associated with the patient (pages 333-334, the histological features are used to assess whether patients will suffer rejection events in the future vs. patients who will not; the recitation of “additional” merely amounts to using the disclosed functions an additional time)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the system of Peyster et al. with the system of Nirschl such that the system would have been configured to extracting a plurality of histological features from the one or more digitized EMB images as described in Peyster. The suggestion/motivation would have been in order to implement a system capable of “improv[ing] the diagnostic and prognostic value of allograft EMB specimens” (page 334 of the Peyster reference).
Regarding claim 21, the combination of Nirschl and Peyster et al. discloses the medium of the parent claim (claim 1).
Peyster et al. additionally discloses:
wherein the prediction comprises the grade associated with the patient, wherein the grade comprising a binary classification indicative of a rejection of the heart transplant of the patient (page 330, the EMB is assigned a binary label as either “future rejection” or “never rejection”)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the system of Peyster et al. with the system of Nirschl such that the system would have been configured to have a prediction comprising the grade associated with the patient, wherein the grade comprising a binary classification indicative of a rejection of the heart transplant of the patient as described in Peyster. The suggestion/motivation would have been in order to implement a system capable of “improv[ing] the diagnostic and prognostic value of allograft EMB specimens” (page 334 of the Peyster reference).
Claim(s) 7 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Nirschl in view of Peyster, further in view of Madabhushi et al. (U.S.P.G. Pub. No. 2019/0279359).
Regarding claim 7, the combination of Nirschl and Peyster discloses the medium of the parent claim (claim 1).
The combination of Nirschl and Peyster does not explicitly disclose:
wherein the machine learning predictive model is configured to use a support vector machine (SVM) classification method.
Madabhushi et al. discloses:
wherein the machine learning predictive model is configured to use a support vector machine (SVM) classification method (paragraph [0051], for example, the classifier can be a support vector machine classifier)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the system of Madabhushi et al. with the combination of Nirschl and Peyster such that the system would have been configured to use a support vector machine (SVM) classification method as described in Madabhushi. The suggestion/motivation would have been in order to implement a system capable of “automatically identify[ing] and analyzing…images in a reproducible more accurate, non-tissue-destructive way using a machine vision approach” (paragraph [0018] of the Madabhushi reference).
Regarding claim 8, the combination of Nirschl and Peyster discloses the medium of the parent claim (claim 1).
The combination of Nirschl and Peyster does not explicitly disclose:
wherein the machine learning predictive model comprises a quadratic discriminant analysis model.
Madabhushi et al. discloses:
wherein the machine learning predictive model comprises a quadratic discriminant analysis model (SVM) (paragraph [0051], for example, the classifier can be a quadratic discriminant classifier)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the system of Madabhushi et al. with the combination of Nirschl and Peyster such that the system would have been configured to use a quadratic discriminant classification method as described in Madabhushi. The suggestion/motivation would have been in order to implement a system capable of “automatically identify[ing] and analyzing…images in a reproducible more accurate, non-tissue-destructive way using a machine vision approach” (paragraph [0018] of the Madabhushi reference).
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 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 JOHN R WALLACE whose telephone number is (571)270-1577. The examiner can normally be reached Monday-Friday from 8:30-5 PM.
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/JOHN R WALLACE/ Primary Examiner, Art Unit 2682