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 .
Claims status: amended claims: 1, 8, 15; the rest is unchanged.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 01/30/2026 has been entered.
Response to Arguments
Applicant’s arguments have been considered but are moot because the new ground of rejection does not rely on any combination of references applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. A new primary reference is currently being used in the present rejection.
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.
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.
Claims 1-5, 8-12, 15-19 are rejected under 35 U.S.C. 103 as being unpatentable over Willcut (US 2022/0245757 A1; pub. Aug.4, 2022) in view of Kuusela et al. (US 2021/0304866 A1; pub. Sep. 30, 2021).
Regarding claim 1, Willcut discloses: A method comprising: receiving, by a processor, an attribute of a radiation therapy treatment plan for a patient and at least one medical image of the patient (para. [0056]-[0057]); executing, by the processor, an artificial intelligence model to predict deformation data for at least one internal structure of the patient using the attribute and the at least one medical image (para. [0059]), wherein the artificial intelligence model is trained in accordance with a training dataset comprising a set of participants and their corresponding deformation data (para. [0106]), wherein predicted deformation data comprises deformation vectors representing spatial movement or volumetric change of at least one voxel based on a biomechanical model of the patient's internal anatomical structures (para. [0009], [0020]); and generating, by the processor using the artificial intelligence model, a synthetic medical image representing the at least one medical image deformed in accordance with the predicted deformation data (para. [0058]).
Willcut is silent about: fine-tuned for the patient based on the at least one medical image.
In a similar field of endeavor Kuusela et al. disclose: fine-tuned for the patient based on the at least one medical image (para. [0099], [0117]) motivated by the benefits for a treatment that is patient specific and avoids overexposure of healthy tissues (Kuusela et al. para. [0009]).
In light of the benefits for a treatment that is patient specific and avoids overexposure of healthy tissues as taught by Kuusela et al., it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Willcut with the teachings of Kuusela et al.
Regarding claim 2, Willcut discloses: the synthetic medical image is a different type than the at least one medical image (para. [0069]).
Regarding claim 3, Willcut discloses: the synthetic medical image is one of a computer tomography image, a cone beam computer tomography image, or a magnetic resonance image (para. [0069]).
Regarding claim 4, Willcut discloses: the deformation data corresponds to a movement, volume expansion, or volume shrinkage of at least one internal structure of the patient, the method further comprising:
transmitting, by the processor, the synthetic medical image to a second model (para. [0121).
Regarding claim 5, Willcut discloses: transmitting, by the processor, the deformation data to a plan optimizer computer model (para. [0006]-[0007]).
Regarding claim 8, X Willcut and Enderling et al. disclose: A non-transitory machine-readable storage medium having computer-executable instructions stored thereon that, when executed by one or more processors, cause the one or more processors to perform operations comprising: receive an attribute of a radiation therapy treatment plan for a patient and at least one medical image of the patient; execute an artificial intelligence model to predict deformation data for at least one internal structure of the patient using the attribute and the at least one medical image, wherein the artificial intelligence model is trained in accordance with a training dataset comprising a set of participants and their corresponding deformation data and fine-tuned for the patient based on the at least one medical image, wherein predicted deformation data comprises deformation vectors representing spatial movement or volumetric change of at least one voxel based on a biomechanical model of the patient's internal anatomical structures; and generate, using the artificial intelligence model, a synthetic medical image representing the at least one medical image deformed in accordance with the predicted deformation data (the claim contains the same substantive limitations as claim 1, therefore, the claim is rejected on the same basis).
Regarding claim 9, Willcut discloses: the synthetic medical image is a different type than the at least one medical image (the claim is rejected on the same basis as claim 2).
Regarding claim 10, Willcut discloses: the synthetic medical image is one of a computer tomography image, a cone beam computer tomography image, or a magnetic resonance image (the claim is rejected on the same basis as claim 3).
Regarding claim 11, Xiao et al. disclose: the deformation data corresponds to a movement, volume expansion, or volume shrinkage of at least one internal structure of the patient, wherein the instructions further cause the processor to transmit the synthetic medical image to a second model (the claim is rejected on the same basis as claim 4).
Regarding claim 12, Willcut discloses: the instructions further cause the processor to transmit the deformation data to a plan optimizer computer model (the claim is rejected on the same basis as claim 5).
Regarding claim 15, Willcut and Enderling et al. disclose: A system comprising a processor configured to: receive an attribute of a radiation therapy treatment plan for a patient and at least one medical image of the patient; execute an artificial intelligence model to predict deformation data for at least one internal structure of the patient using the attribute and the at least one medical image, wherein the artificial intelligence model is trained in accordance with a training dataset comprising a set of participants and their corresponding deformation data and fine-tuned for the patient based on the at least one medical image, wherein predicted deformation data comprises deformation vectors representing spatial movement or volumetric change of at least one voxel based on a biomechanical model of the patient's internal anatomical structures; and generate, using the artificial intelligence model, a synthetic medical image representing the at least one medical image deformed in accordance with the predicted deformation data (the claim contains the same substantive limitations as claim 1, therefore, the claim is rejected on the same basis).
Regarding claim 16, Willcut discloses: the synthetic medical image is a different type than the at least one medical image (the claim is rejected on the same basis as claim 2).
Regarding claim 17, Willcut discloses: the synthetic medical image is one of a computer tomography image, a cone beam computer tomography image, or a magnetic resonance image (the claim is rejected on the same basis as claim 3).
Regarding claim 18, Willcut discloses: the deformation data corresponds to a movement, volume expansion, or volume shrinkage of at least one internal structure of the patient, wherein the instructions further cause the processor to transmit the synthetic medical image to a second model (the claim is rejected on the same basis as claim 4).
Regarding claim 19, Willcut discloses: the processor is further configured to transmit the deformation data to a plan optimizer computer model (the claim is rejected on the same basis as claim 5).
Claims 6, 13, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Willcut (US 2022/0245757 A1; pub. Aug.4, 2022) in view of Kuusela et al. (US 2021/0304866 A1; pub. Sep. 30, 2021) and further in view of Enderling et al. (US 2023/0038942; pub. Feb. 9, 2023).
Regarding claim 6, the combined references are silent about: adjusting, by the processor, at least one attribute of a radiation therapy machine in accordance with the predicted deformation data.
In a similar field of endeavor Enderling et al. disclose: adjusting, by the processor, at least one attribute of a radiation therapy machine in accordance with the predicted deformation data (para. [0074]) motivated by the benefits for providing the clinician with flexibility to make adjustments to the total dose and/or dose per treatment (Enderling et al. para. [0074]).
In light of the benefits for providing the clinician with flexibility to make adjustments to the total dose and/or dose per treatment as taught by Enderling et al., it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Willcut and Kuusela et al. with the teachings of Enderling et al.
Regarding claim 13, the combined references are silent about: the instructions further cause the processor to adjust at least one attribute of a radiation therapy machine in accordance with the predicted deformation data.
In a similar field of endeavor Enderling et al. disclose: the instructions further cause the processor to adjust at least one attribute of a radiation therapy machine in accordance with the predicted deformation data (para. [0074]) motivated by the benefits for providing the clinician with flexibility to make adjustments to the total dose and/or dose per treatment (Enderling et al. para. [0074]).
In light of the benefits for providing the clinician with flexibility to make adjustments to the total dose and/or dose per treatment as taught by Enderling et al., it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Willcut and Kuusela et al. with the teachings of Enderling et al.
Regarding claim 20, the combined references are silent about: the instructions further cause the processor to adjust at least one attribute of a radiation therapy machine in accordance with the predicted deformation data
In a similar field of endeavor Enderling et al. disclose: the instructions further cause the processor to adjust at least one attribute of a radiation therapy machine in accordance with the predicted deformation data (para. [0092], [0114]) motivated by the benefits for providing the clinician with flexibility to make adjustments to the total dose and/or dose per treatment (Enderling et al. para. [0074]).
In light of the benefits for providing the clinician with flexibility to make adjustments to the total dose and/or dose per treatment as taught by Enderling et al., it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus of Willcut and Kuusela et al. with the teachings of Enderling et al.
Claims 7, 14 are rejected under 35 U.S.C. 103 as being unpatentable over Willcut (US 2022/0245757 A1; pub. Aug.4, 2022) in view of Kuusela et al. (US 2021/0304866 A1; pub. Sep. 30, 2021) and further in view of Mansi et al. (US 2020/0034654 A1; pub. Jan. 30, 2020).
Regarding claim 7, the combined references are silent about: the synthetic medical image comprises a deformation vector indicating a movement of at least one segment of the patient’s internal structure.
In a similar field of endeavor Mansi et al. disclose: the synthetic medical image comprises a deformation vector indicating a movement of at least one segment of the patient’s internal structure (para. [0020], [0059]) motivated by the benefits for accurate deformation registration (Mansi et al. para. [0074]).
In light of the benefits for accurate deformation registration as taught by Mansi et al., it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of X Willcut and Kuusela et al. with the teachings of Mansi et al.
Regarding claim 14, the combined references are silent about: the synthetic medical image comprises a deformation vector indicating a movement of at least one segment of the patient’s internal structure.
In a similar field of endeavor Mansi et al. disclose: the synthetic medical image comprises a deformation vector indicating a movement of at least one segment of the patient’s internal structure (para. [0020], [0059]) motivated by the benefits for accurate deformation registration (Mansi et al. para. [0074]).
In light of the benefits for accurate deformation registration as taught by Mansi et al., it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Willcut and Kuusela et al. with the teachings of Mansi et al.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MAMADOU FAYE whose telephone number is (571)270-0371. The examiner can normally be reached Mon – Fri 9AM-6PM.
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/MAMADOU FAYE/ Examiner, Art Unit 2884
/UZMA ALAM/ Supervisory Patent Examiner, Art Unit 2884