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 .
Claim Status
Original claims 1-22 filed 8/18/2022 are pending.
Priority
This application filed 8/18/2022 is a 371 National stage filing of PCT/US2021/018589 filed 2/28/2021, which claims benefit to US Provisional application 62/978070 filed 2/18/2020.
Drawings
The petition for color photographs and color drawings filed under 37 CFR 1.84(a)(2) is granted.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 2/26/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claim analysis
The method of claim 1 comprises receiving a CFP image and classifying each image by extracting deep features, grading drusen and pigmentary abnormalities and then predicting risk of AMD using Cox proportional hazard model. In view of the specification and art of record, color fundus photography is a non-invasive imaging technique that provides high resolution photographs of the fundus, which includes the retina, optic nerve, and choroid. This method provides a true color representation of the eye's internal structures, which the art suggests can be used for diagnosing and documenting retinal diseases and conditions. In evaluating the photo the specification at [0045] teaches that “In some examples, the deep features may include drusen and/or pigmentary abnormalities.” and appears to provide for observable features relative to extracting and using any observed abnormality in classification of AMD status in the patient. Independent claim 11 provides more broadly any type of image of both eyes of a patient, where dependent claim 12 sets forth CFP and other known imaging processes, and more broadly ‘classifying’ and ‘grading’ but dependent claim 15 provides that Cox proportional hazard model be used. Claim 16 provides for a device that receives the images, and sets forth the same analysis steps of the method. With respect to processing and normalizing images, the specification for both the methods and device use ‘deep learning’ which the specification at [0041] teaches “Deep learning is a branch of machine learning that allows computers to learn by example; in the case of image analysis, it involves training algorithmic models on images with accompanying labels such that they can perform classification of novel images according to the same labels.” With respect to automatically providing classification, in [0043] it teaches “The prediction method delivers autonomous predictions of a higher accuracy than those from retinal specialists using two existing clinical standards. Hence, the predictions are closer to the ground truth of actual time-based progression to late AMD than when retinal specialists are grading the same bilateral CFP and entering these grades into the SSS or the online calculator. In addition, deep feature extraction may generally achieve higher accuracy than DL grading of traditional hand-crafted features.” however this is not a definition or requirement of ‘automatic’ nor is there any requirement of what standards are used in classifying and predicting broadly required of the claims. Dependent claims provide for creating or using a standard or normalized score, and considering additional information such as genotype and patient age, smoking status and AMD genotype (claims 5-7), as well as associating observed abnormalities with BA or NV (claims 2-3).
For step 1 of the 101 analysis, the claims are found to be directed to a statutory category of a process and a product.
For step 2A of the 101 analysis, the judicial exception of the claims are the steps of accessing an image of an eye for abnormalities. In review of the specification, there is no teaching of new abnormalities or unique or different image types, and appear to provide for assessing abnormalities generally used in assessing AMD, GA or NV status. Similar for predicting, scoring, automatically or using known correlative data such as age, smoking or any genotype associated with AMD, there does not appear to be any specific process of grading or predicting required by the claim as set forth in the specification. The step of receiving, classifying and predicting appear to be instructional steps of observing a photo and assessing any abnormalities that might be present. The claims set forth the use of a Cox proportional hazard model, which was known in the art broadly as a class of survival models in statistics. The judicial exception is a set of instructions for analysis of images and appear to fall into the category of Mental Processes, that is concepts performed in the human mind (including an observation, evaluation, judgment, opinion) for observing and noting abnormalities in a photo of the eye and into the category of Mathematical Concepts, that is mathematical formulas or equations to the extent that Cox statistical analysis is used to assess data.
In view of the claim breadth and requirements of the specification, the breadth of “receiving”, “classifying”, and “predicting” encompasses non-transformative visual assessment of a image of an eye coupled with prior knowledge of the correlation of said phenotype(s) with the presence of particular genotype(s); for example, using known genotypes to be informative, or knowing that smoking status has a positive correlation with AMD. This breadth does not impose a meaningful limit on the claim scope, such that all others are not precluded from using the natural principle of observing abnormalities and using them to diagnose AMD. Although the claims encompass “automatically’, the courts have also identified limitations that did not integrate a judicial exception into a practical application; for example, merely including instructions to implement an abstract idea on a computer device, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f). As the steps of “receiving”, “classifying”, and “predicting” are very generally recited, the combination of “receiving”, “classifying”, and “predicting” is together reasonably interpreted as mere data gathering and observation of photos. Computing, constructing datasets and using statistical models was well understood, conventional, and routinely performed in the art at the time the application was filed, to the extent that a Cox model is to be applied in the assessment of AMD from the image. Furthermore, the limitation of genotyping breeding individuals at a plurality of markers or alleles does not change the steps to be performed. See MPEP § 2106.05(g) for a discussion on adding insignificant extra-solution (both pre-solution and post-solution) activity to the judicial exception. See also MPEP § 2106.05(h) for a discussion on generally linking the use of a judicial exception to a particular technological environment or field of use. The claims appear to fall into the category of Mathematical Concepts, as it applies the use of statistics and mathematical relationships in analyzing probabilities, and also into the category of mental processes, as concepts performed in the human mind (including an observation, evaluation, judgment, opinion) because there is no apparent complexity to or amount of data that is collected and analyzed as presently claimed which was not previously performed by a physician for assessing AMD.
Recent guidance from the office requires that the judicial exception be evaluated under a second prong to determine whether the judicial exception is practically applied. In the instant case, the claims do not have an additional element to which the assessment is applied and as a final step only provides a prediction based on the observation. This judicial exception requires steps recited at high level of generality and for a device/computer are only stored on a non-transitory memory, and is not found to be a practical application of the judicial exception as broadly set forth.
For step 2B of the 101 analysis, to the extent ‘receiving’ can be interpreted as a physical requirement of the claims, each of the independent claims recites additional elements and are found to be generic instruction and steps of obtaining image data. As such, the claims do not provide for any additional element to consider under step 2B. For the product or processing the method using a computer, it is noted that in explaining the Alice framework, the Court wrote that "[i]n cases involving software innovations, [the step one] inquiry often turns on whether the claims focus on the specific asserted improvement in computer capabilities or, instead, on a process that qualifies as an abstract idea for which computers are invoked merely as a tool." The Court further noted that "[s]ince Alice, we have found software inventions to be patent-eligible where they have made non-abstract improvements to existing technological processes and computer technology." Moreover, these improvements must be specific -- "[a]n improved result, without more stated in the claim, is not enough to confer eligibility to an otherwise abstract idea. [t]o be patent-eligible, the claims must recite a specific means or method that solves a problem in an existing technological process.”
As indicated in the summary of the judicial exception above and in view of the teachings of the specification, the steps are drawn to analysis of image data. While the instruction for the method can be stored on a medium and could be implemented on a computer device, together the steps do not appear to result in significantly more than a means to assess or compare images of the eye where observed abnormalities can be associated with AMD. The judicial exception of the method as claimed can be performed by hand and in light of the previous claims to a computer medium and in light of the teaching of the specification on a computer. In review of the instant specification the methods do not appear to require a special type of processor and can be performed on a general purpose computer. Further, ‘deep features’ do not appear to require any new or unique images, or any new or unique types of abnormalities, and appear to encompass features that are observable by the human eye. Based upon an analysis with respect to the claim as a whole, claims 1-22 do not recite something significantly different than a judicial exception. Dependent claims set forth additional steps which are more specifically define the considerations and steps of calculating, and comparing, and do not add additional elements which result in significantly more to the claimed method for the analysis. The Step 2 analysis is a two-part analysis, Step 2A and Step 2B, with the first part Step 2A requiring a determination of whether the claims are directed towards a judicial exception, i.e. a law of nature, natural phenomenon, or an abstract idea. In the instant case, the claims comprise steps of comparing images or observing in images and is considered the judicial exception. As such, the instant claims set forth an inventive concept that are drawn only to an abstract process that only manipulates data with respect to grading and predicting using statistical models such as Cox model. Therefore the result of Step 2A analysis is that the claims are directed towards a judicial exception, i.e. an abstract idea. The second part, Step 2B of the two step analysis is to determine whether any element or combination of elements, in the claim is sufficient to ensure that the claim as a whole amounts to significantly more than the judicial exception. No additional steps are recited in the instantly claimed invention that would amount to significantly more than the judicial exception for having an image and reporting what is observed relative to it be indicative of AMD. Furthermore, if a claim is directed essentially to a method of calculating, using a mathematical formula, even if the solution is for a specific purpose, the claimed method is non-statutory. In other words, patenting abstract idea (observing abnormalities known and associated with AMD in a photo) cannot be circumvented by attempting to limit the use to a particular technological environment or purpose and desired result.
One way to overcome a rejection for non-patent-eligible subject matter is to persuasively argue that the claimed subject matter is not directed to a judicial exception. Another way for the applicants to overcome the rejection is to persuasively argue that the claims contain elements in addition to the judicial exception that either individually or as an ordered combination are not well understood, routine, or conventional. Another way for the applicants to overcome the rejection is to persuasively argue that the claims as a whole result in an improvement to a technology. Persuasive evidence for an improvement to a technology could be a comparison of results of the claimed subject matter with results of the prior art, or arguments based on scientific reasoning that the claimed subject matter inherently results an improvement over the prior art. The applicants should show why the claims require the improvement in all embodiments.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-22 are rejected under 35 U.S.C. 103 as being unpatentable over Phan et al. (2016), Sleiman et al. (2017) and Zhu et al. (2019).
Claim 1 comprises receiving a CFP image and classifying each image by extracting deep features, grading drusen and pigmentary abnormalities and then predicting risk of AMD using Cox proportional hazard model. Independent claim 11 provides more broadly any type of image of the eyes of a patient, where dependent claim 12 sets forth CFP and other known imaging processes, and more broadly ‘classifying’ and ‘grading’ but dependent claim 15 provides that Cox proportional hazard model be used consistent with claim 1. Claim 16 provides for a device that receives the images, and sets forth the same analysis steps of the method. Dependent claims provide for creating or using a standard or normalized score, and considering additional information such as genotype and patient age, smoking status and AMD genotype (claims 5-7), as well as associating observed abnormalities with BA or NV (claims 2-3).
Analyzing and assessing CFP images for abnormalities, in particular grading drusen and pigmentary abnormalities for an indication of AMD were known. For example, Phan et al. teach Automatic Screening and Grading of Age-Related Macular Degeneration from Texture Analysis of Fundus Images. Similarly, Sleiman et al. teach Optical Coherence Tomography Predictors of Risk for Progression to Non-Neovascular Atrophic Age-Related Macular Degeneration. Each provide analysis steps and guidance for consideration in assessing, confirming and predicting AMD in a patient’s eye. However neither specifically state to use Cox proportional hazard model, but Zhu et al. who teach Association of Age-Related Macular Degeneration With Risk of All-Cause and Specific-Cause Mortality provide the use of Cox modeling in the analysis and associate the analysis. Each provide that other conditions are used in the assessment such as age or genetic predisposition. Given the detailed guidance on assessing and using CFP images to determine AMD and provide an assessment of the severity, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was made to provide the art as a whole in assessing CFP for diagnosis AMD. One having ordinary skill in the art would have been motivated to combine the various teachings because each provide details of AMD diagnosis and a more complete ability to assess the state and progression of AMD. Given the successful results of each, there would have been a reasonable expectation of success of evaluating CFP images and staging AMD based on druen grading and pigmentary abnormalities that could be observed.
Thus, the claimed invention as a whole was clearly prima facie obvious.
Conclusion
No claim is allowed.
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/Joseph Woitach/Primary Examiner, Art Unit 1687