DETAILED ACTION
Claims 1, 3-12 and 14-20 are pending in this application. Claims 1 and 12 have been amended in this application, and claims 2 and 13 are canceled.
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 .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 10/20/2023 and 12/16/2024 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Response to Arguments
35 U.S.C. 103
The applicant’s arguments (see Remarks, filed 03/25/2026) have been fully considered by the examiner and are not persuasive. Applicant argues that the combination of Negasheva and Udupa fails to teach a health assessment value describing a biological age where the value is derived from image processing metrics. The examiner disagrees, Negasheva teaches on page 405 column 2 and page 406 column 1 that multiple factors of body composition such as height, weight, and chest and waist circumferences are used in determining the biological age. Further, Udupa teaches in paragraph [0032] the use of an image processing model to derive measures of body composition such as adipose, muscle and bone densities, these values are then used to output a statistical breakdown which is indicative of the patient’s overall health (see Udupa [0125]-[0127]). One of ordinary skill in the art would understand that it would be obvious to take these measures as taught in Negasheva and combine them with a system such as that of Udupa to create a system which takes body composition measures derived from an image, and generates a biological age factor output. This combination would be obvious regardless of how the body composition measures are derived, given that Negasheva teaches the use of the same measures that Udupa derives to generate this biological age output. For at least the reasons above, the examiner maintains the rejections under 35 U.S.C. 103 over Udupa in view of Negasheva.
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(Udupa, [0032])
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claims 3-5 and 14-16 rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form.
Regarding claim 3 and its dependent claims 4-5, the claims depend on claim 2, which has been canceled, therefore the claims are in improper dependent form as being dependent on a canceled claim. For examination purposes the examiner is interpreting claim 3 as being dependent from independent claim 1, and claims 4-5 having the same dependencies as written. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Regarding claim 14 and its dependent claims 15-16, the claims depend on claim 13, which has been canceled, therefore the claims are in improper dependent form as being dependent on a canceled claim. For examination purposes the examiner is interpreting claim 13 as being dependent from independent claim 12, and claims 15-16 having the same dependencies as written. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
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 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.
1. Claims 1, 6-8, 10-12, and 17-19 are rejected under 35 U.S.C. 103 as being unpatentable over Udupa US 20230129957 A1) in view of Negasheva (Negasheva et al, Express Estimation of the Biological Age by the Parameters of Body Composition in Men and Women over 50 Years, Bulletin of Experimental Biology and Medicine, 2017).
Regarding claim 1 Udupa discloses; A health screening system comprising:
a set of computerized image analysis tools receiving slice-image medical data of a patient to provide a set of different body composition measurements related to clinical risk factors (Udupa, [0022] CT scans are used to determined body composition [0032] body composition measures associated with risk of certain diseases are quantified by the model);
a model receiving the different body composition measurements to provide a health assessment value combining the different body composition measurements and indicating health of the patient (Udupa, [0032] the model takes measures of different tissues of interest, such as adipose, muscle and bone density to quantify the body composition, [0125]-[127] the system outputs a breakdown of the tissue composition values, which per [0032] are values indicative of a patient’s health)
and an output presenting the health assessment value for review (Udupa, [0032] the model takes measures of different tissues of interest, such as adipose, muscle and bone density to quantify the body composition, [0125]-[127] the system outputs a breakdown of the tissue composition values, which per [0032] are values indicative of a patient’s health, [0091] the components and values are presented as an output);
and wherein the health assessment value is an biological age value.
Regarding claim 1 Udupa fails to disclose; wherein the health assessment value is an age value.
However, in the same field of endeavor of health risk screening, Negasheva teaches; wherein the health assessment value is an age value (Negasheva, page 406 column 1 paragraph 2, multiple factors are taking into an analysis to output a biological age value (BA), page 406 column 2 paragraphs 1-4 , the Biological age (BA) values are computed associated with multiple biomarkers and body composition).
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(Negasheva, page 406 column 2)
The combination of Udupa and Negasheva would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. Udupa teaches a method of computing body composition of biomarkers associated with aging and risk and disease, however it does not teach computing biological age. Negasheva teaches this commutation and teaches how this compares to chronological age, as well as how the parameters used are factors in advanced biological age. The motivation for the combination of lies in that the use of biological age as a risk score or metric is reflective of multiple factors which would indicate a patient’s risk of disease at once, rather than individually assessing these factors, which would be more time consuming to assess (Negasheva, page 405, abstract, and column 1 paragraph 1 through column 2 paragraph 2).
Regarding claim 6 the combination of Udupa and Negasheva teaches; The health screening system of claim 1 wherein the output further provides relative significance of the body composition measurements in influencing the health assessment value (Udupa, [0032] the model takes measures of different tissues of interest, such as adipose, muscle and bone density to quantify the body composition, [0125]-[127] the system outputs a breakdown of the tissue composition values, which per [0032] are values indicative of a patient’s health, [0091] the components and values are presented as an output).
Regarding claim 7 the combination of Udupa and Negasheva teaches; The health screening system of claim 1 wherein the computerized analysis image tools output physical measurements (Udupa, [0032] the model takes measures of different tissues of interest, such as adipose, muscle and bone density to quantify the body composition, [0125]-[127] the system outputs a breakdown of the tissue composition values and measures).
Regarding claim 8 the combination of Udupa and Negasheva teaches; The health screening system of claim 7 wherein the output further provides images depicting the physical measurements (Udupa, [0091] the tissue component measures are output, [0032] the system outputs a segmentation (visual image/depiction) and quantification (numeric measure) of body composition).
Regarding claim 10 the combination of Udupa and Negasheva teaches; The health screening system of claim 1 wherein the slice image medical data is computed tomography data (Udupa, [0022] CT scans are used to determined body composition).
Regarding claim 11 the combination of Udupa and Negasheva teaches; The health screening system of claim 10 wherein the slice image data is abdominal image data (Udupa, [0022] CT scans are used to determined body composition, [0037]-[0038] abdominal regions are imaged).
Regarding claim 12 the combination of Udupa and Negasheva teaches; A method of assessing a biological age comprising:
(a) obtaining slice image medical data for a patient (Udupa, [0022] CT scans are used to determined body composition [0032] body composition measures associated with risk of certain diseases are quantified by the model);
(b) applying a set of computerized image analysis tools to the slice image medical data to provide a set of different body composition measurements related to clinical risk factors (Udupa, [0022] CT scans are used to determined body composition [0032] body composition measures associated with risk of certain diseases are quantified by the model);
(c) applying the set of different body composition measurements to a computerized model combining the different body composition measurements into a health assessment value (Udupa, [0032] the model takes measures of different tissues of interest, such as adipose, muscle and bone density to quantify the body composition, [0125]-[127] the system outputs a breakdown of the tissue composition values, which per [0032] are values indicative of a patient’s health);
(Udupa, [0032] the model takes measures of different tissues of interest, such as adipose, muscle and bone density to quantify the body composition, [0125]-[127] the system outputs a breakdown of the tissue composition values, which per [0032] are values indicative of a patient’s health, [0091] the components and values are presented as an output) and wherein the health assessment value is an biological age value (Negasheva, page 406 column 1 paragraph 2, multiple factors are taking into a analysis to output a biological age values (BA), page 406 column 2 paragraphs 1-4 , the Biological age (BA) values are computed associated with multiple biomarkers and body composition).
The combination of Udupa and Negasheva would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. Udupa teaches a method of computing body composition of biomarkers associated with aging and risk and disease, however it does not teach computing biological age. Negasheva teaches this commutation and teaches how this compares to chronological age, as well as how the parameters used are factors in advanced biological age. The motivation for the combination of lies in that the use of biological age as a risk score or metric is reflective of multiple factors which would indicate a patient’s risk of disease at once, rather than individually assessing these factors, which would be more time consuming to assess (Negasheva, page 405, abstract, and column 1 paragraph 1 through column 2 paragraph 2).
Regarding claim 17 the combination of Udupa and Negasheva teaches; The method of claim 12 wherein the output further provides relative significance of the body composition measurements in influencing the health assessment value (Udupa, [0032] the model takes measures of different tissues of interest, such as adipose, muscle and bone density to quantify the body composition, [0125]-[127] the system outputs a breakdown of the tissue composition values, which per [0032] are values indicative of a patient’s health, [0091] the components and values are presented as an output)
Regarding claim 18 the combination of Udupa and Negasheva teaches; The method of claim 12 wherein the computerized analysis image tools output physical measurements (Udupa, [0032] the model takes measures of different tissues of interest, such as adipose, muscle and bone density to quantify the body composition, [0125]-[127] the system outputs a breakdown of the tissue composition values and measures).
Regarding claim 19 the combination of Udupa and Negasheva teaches; The method of claim 18 wherein the output further provides images depicting the physical measurements (Udupa, [0091] the tissue component measures are output, [0032] the system outputs a segmentation (visual image/depiction) and quantification (numeric measure) of body composition).
Claims 3-4 and claims 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Udupa US 20230129957 A1) in view of Negasheva (Negasheva et al, Express Estimation of the Biological Age by the Parameters of Body Composition in Men and Women over 50 Years, Bulletin of Experimental Biology and Medicine, 2017) and in further view of Hospers (Hospers et al, Relation between blood pressure and mortality risk in an older population: role of chronological and biological age, Journal of Internal Medicine, doi: 10.1111/joim.12284 (Year: 2014)).
Regarding claim 3 the combination of Udupa and Negasheva fails to teach; The health screening system of claim 2 wherein the model provides an empirically derived survival probability
and wherein the age value matches the survival probability obtained from the model to a second distinct model relating survival probability to chronological age.
However, in the same field of endeavor Hospers teaches; The health screening system of claim 2 wherein the model provides an empirically derived survival probability (Hospers, pages 489-490 Data Analysis section, the BMI, cholesterol, smoking, Blood pressure and computed biological age were used to determine mortality risks using a model, survival curves were generated for each variable relating the factors to survival)
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(Hospers, Data Analysis)
and wherein the age value matches the survival probability obtained from the model to a second distinct model relating survival probability to chronological age (Hospers, pages 489-490 Data Analysis section, the BMI, cholesterol, smoking, Blood pressure and computed biological age were used to determine mortality risks using a model, survival curves were generated for each variable relating the factors to survival, where in one of the factors was chronical age and biological age. Since both had survival curves, both would have empirical relation to survival).
The combination of Udupa, Negasheva, and Hospers would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. The combination of Udupa and Negasheva teach a model using CT scans to compute biological age based upon body composition, however they do not teach the relation of this measure to survival prediction computations. Hospers teaches this deficiency, teaching that mortality risk and survival probability may be correlated with chronological and biological ages using survival curves and multiple models. The addition of this feature to the systems and methods taught by Udupa and Negasheva would be advantageous in assessing risk factors and reducing mortality risk in high-risk individuals (Hospers, Introduction, page 488).
Regarding claim 4 the combination of Udupa, Negasheva, and Hospers teaches; The health screening system of claim 3 wherein the second model models input parameters independent of body composition information derived from slice image medical data (Negasheva, Page 406 column 1, multiple different health parameters are analyzed, not including CT values).
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(Negasheva, page 406, column 1)
The combination of Udupa, Negasheva, and Hospers would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. Udupa teaches a model using CT scans to assess body composition and health risks, but that use of a separate model to take in the non-CT health parameters. Negasheva teaches this deficiency, teaching the use of other parameters being considered by the model in computing age and risk factors. The motivation for this combination is that the using multiple factors in computing the biological age may help better estimate it (Negasheva, Page 405 columns 1 and 2).
Regarding claim 14 the combination of Udupa, Negasheva, and Hospers teaches; The method of claim 13 wherein the model provides an empirically derived survival probability (Hospers, pages 489-490 Data Analysis section, the BMI, cholesterol, smoking, Blood pressure and computed biological age were used to determine mortality risks using a model, survival curves were generated for each variable relating the factors to survival) and wherein the age value matches the survival probability obtained from the model to a second distinct model relating survival probability to chronological age(Hospers, pages 489-490 Data Analysis section, the BMI, cholesterol, smoking, Blood pressure and computed biological age were used to determine mortality risks using a model, survival curves were generated for each variable relating the factors to survival, where in one of the factors was chronical age and biological age. Since both had survival curves, both would have empirical relation to survival).
The combination of Udupa, Negasheva, and Hospers would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. The combination of Udupa and Negasheva teach a model using CT scans to compute biological age based upon body composition, however they do not teach the relation of this measure to survival prediction computations. Hospers teaches this deficiency, teaching that mortality risk and survival probability may be correlated with chronological and biological ages using survival curves and multiple models. The addition of this feature to the systems and methods taught by Udupa and Negasheva would be advantageous in assessing risk factors and reducing mortality risk in high-risk individuals (Hospers, Introduction, page 488).
Regarding claim 15 the combination of Udupa, Negasheva, and Hospers teaches; The method of claim 14 wherein the second model models input parameters independent of body composition information derived from slice image imaging (Negasheva, Page 406 column 1, multiple different health parameters are analyzed, not including CT values).
The combination of Udupa, Negasheva, and Hospers would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. Udupa teaches a model using CT scans to assess body composition and health risks, but that use of a separate model to take in the non-CT health parameters. Negasheva teaches this deficiency, teaching the use of other parameters being considered by the model in computing age and risk factors. The motivation for this combination is that the using multiple factors in computing the biological age may help better estimate it (Negasheva, Page 405 columns 1 and 2).
Claims 5 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Udupa US 20230129957 A1) in view of Negasheva (Negasheva et al, Express Estimation of the Biological Age by the Parameters of Body Composition in Men and Women over 50 Years, Bulletin of Experimental Biology and Medicine, 2017) and in further view of Hospers (Hospers et al, Relation between blood pressure and mortality risk in an older population: role of chronological and biological age, Journal of Internal Medicine, doi: 10.1111/joim.12284 (Year: 2014)) and in further view of Min (US 20230147995 A1).
Regarding claim 5 the combination of Udupa, Negasheva, and Hospers fails to teach; The health screening system of claim 4 wherein the input parameters of the second model include characteristics of the patient selected from the group of sex, race, and smoking history.
However, in the same field of endeavor, Min teaches; The health screening system of claim 4 wherein the input parameters of the second model include characteristics of the patient selected from the group of sex, race, and smoking history (Min, [1008] the risk estimate includes, age, race, sex and smoking history).
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The combination of Udupa, Negasheva, Hospers and Min would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. The combination of Udupa, Negasheva, and Hospers teaches a system using multiple patient demographics and CT data to estimate biological age and risk, but does not teach race or ethnicity as a factor in this. Min teaches this deficiency, the motivation for the addition of the factors of race, sex and smoking as taught by Min is that it would improve the combined system of Udupa, Negasheva and Hospers by taking the full scope of patient demographics into account in the computation. (Min [1008])
Regarding claim 16, the combination of Udupa, Negasheva, Hospers and Min teaches; The method of claim 15 wherein the input parameters of the second model include characteristics of the patient selected from the group of sex, race, and smoking history (Min, [1008] the risk estimate includes, age, race, sex and smoking history).
The combination of Udupa, Negasheva, Hospers and Min would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. The combination of Udupa, Negasheva, and Hospers teaches a system using multiple patient demographics and CT data to estimate biological age and risk, but does not teach race or ethnicity as a factor in this. Min teaches this deficiency, the motivation for the addition of the factors of race, sex and smoking as taught by Min is that it would improve the combined system of Udupa, Negasheva and Hospers by taking the full scope of patient demographics into account in the computation. (Min [1008])
Claims 9 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Udupa US 20230129957 A1) in view of Kakadiaris (US 20170337343).
Regarding claim 9 Udupa fails to disclose; The health screening system of claim 1 wherein the body composition measurements are selected from the group consisting of: bone density, fat proportion, muscle proportion, liver volume, spleen volume, and aortic plaque.
However, in the same field of endeavor, Kakadiaris teaches; The health screening system of claim 1 wherein the body composition measurements are selected from the group consisting of: bone density, fat proportion, muscle proportion, liver volume, spleen volume, and aortic plaque (Kakadiaris [0188] the abdominal CT contains the heart, liver and other abdominal organs including the spleen, [0439]-[0468] details that the system has a 3D volume of all the abdominal organs with labels which can be used in analysis, therefore the liver and spleen volumes would be computed here [0645] abdominal fat can be computed from CT volumes and used in the analysis, [0068] the overall muscle structure, and bone density and structure are collected, [0296] the aorta is modeled included calcifications (plaques)).
The combination of Udupa and Kakadiaris would be obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. Udupa teaches a method of computing body composition, but does not teach using organ volumes or plaque volumes. Kakadiaris teaches this deficiency. The addition of the volumes of Kakadiaris to the body composition model of Udupa would improve the accuracy and considerations using in patient risk scoring, thereby improving the system (Kakadiaris [0188]-[0190]).
Regarding claim 20 the combination of Udupa and Kakadiaris teaches; The method of claim 12 wherein the body composition measurements are selected from the group consisting of: bone density, fat classification, area, and density, muscle bulk and density, liver volume and density, spleen volume, and aortic plaque burden (Kakadiaris [0188] the abdominal CT contains the heart, liver and other abdominal organs including the spleen, [0439]-[0468] details that the system has a 3D volume of all the abdominal organs with labels which can be used in analysis, therefore the liver and spleen volumes would be computed here [0645] abdominal fat can be computed from CT volumes and used in the analysis, [0068] the overall muscle structure, and bone density and structure are collected, [0296] the aorta is modeled included calcifications (plaques)).
The combination of Udupa and Kakadiaris would be obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. Udupa teaches a method of computing body composition, but does not teach using organ volumes or plaque volumes. Kakadiaris teaches this deficiency. The addition of the volumes of Kakadiaris to the body composition model of Udupa would improve the accuracy and considerations using in patient risk scoring, thereby improving the system (Kakadiaris [0188]-[0190]).
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.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. For a listing of analogous prior art as cited by the examiner, please see the attached PTO 892 Notice of References Cited form.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JORDAN M ELLIOTT whose telephone number is (703)756-5463. The examiner can normally be reached M-F 8AM-5PM ET.
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, Emily Terrell can be reached at (571) 270-3717. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/J.M.E./Examiner, Art Unit 2666 /Molly Wilburn/Primary Examiner, Art Unit 2666
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