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 .
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Claims status: amended claims: 1, 3, 6, 18; new claims: 21-22; canceled claims: 2 & 19; the rest is unchanged.
Response to Arguments
Applicant's arguments filed 02/10/2026 have been fully considered but they are not persuasive. Applicant argues in pg.12 -13 of the remarks that the combined references do not teach: "the modifications of the delineation of the ROl and the radiotherapy dose optimization of the ROI are performed at least partially overlap temporally". The examiner respectfully disagrees. Peltola et al. disclose: in para. [0051] that "the modifications of the delineation of the ROl and the radiotherapy dose optimization of the ROI are performed at least partially overlap temporally" is done during treatment session. Regarding claim 3, applicant asserts that Peltola et al. are silent about: “while performing the radiotherapy dose optimization on the ROI, outputting in real time a dose distribution result and a dose volume histogram (DVH) corresponding to the radiotherapy dose being optimized”. In para. [0051] Peltola et al. disclose: “while performing the radiotherapy dose optimization on the ROI, outputting in real time a dose distribution result and a dose volume histogram (DVH) corresponding to the radiotherapy dose being optimized” is done during treatment session. As for claim applicant argues in pg.15 of the remarks that Purdie et al. do not teach: “the determining the target radiotherapy plan of the object includes: determining, based on the modified delineation of the ROI, whether to perform the radiotherapy dose optimization on the ROI based on an initial radiotherapy plan”. Para. [0125] teaches modifying ROI delineation in the purpose of modifying the proposed treatment plan. As for the combination of Purdie, Peltola and Da Silva, applicant argues in pg.17 of the remarks that Da Silva does not remedy the deficiencies of claim 1. However, the rejection of claim is not deficient as shown above. As for the combination of Purdie, Peltola and Chen, applicant argues in pg.18 of the remarks that Chen does not remedy the deficiencies of claim 1. However, the rejection of claim is not deficient as shown above. Regarding claim 17, applicant argues in pg.19 of the remarks that Chen et al. do not teach: “the second sub-model is obtained by a training process including: obtaining a plurality of training samples, each of the plurality of training samples including a sample image and a label image corresponding to the sample image, the sample image including delineations of at least one sample target region, the label image including a delineation of a sample specific region; and obtaining the second sub-model by training, based on the plurality of training samples, a preliminary second sub-model”. The examiner respectfully disagrees because Chen et al. disclose: the second sub-model is obtained by a training process including: obtaining a plurality of training samples, each of the plurality of training samples including a sample image and a label image corresponding to the sample image, the sample image including delineations of at least one sample target region, the label image including a delineation of a sample specific region; and obtaining the second sub-model by training, based on the plurality of training samples, a preliminary second sub-model in para. [0065], [0081], [0140]. As for claim 18, the claim is now in condition for allowance. Therefore, the rejections are maintained and made final.
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 1-4, 12-13, 15-16, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Purdie et al. (US 2018/0211725 A1; pub. Jul. 26, 2018) in view of Peltola et al. (US 2021/0069527 A1; pub. Mar. 11, 2021).
Regarding claim 1, Purdie et al. disclose: A system, comprising: at least one storage device including a set of instructions; and at least one processor in communication with the at least one storage device, wherein when executing the set of instructions, the at least one processor causes the system to perform operations (para. [0023]) including: obtaining a delineation of a region of interest (ROI) in an image of an object, the ROI including at least one target region (para. [0097], [0130]); obtaining a modified delineation of the ROI based on one or more modifications to the delineation of the ROI (para. [0125]); and determining a target radiotherapy plan of the object by performing a radiotherapy dose optimization on the ROI (para. [0060]).
Purdie et al. are silent about: the modifications of the delineation of the ROI and the radiotherapy dose optimization of the ROI are performed at least partially overlap temporally.
In a similar field of endeavor Peltola et al. disclose: the modifications of the delineation of the ROI and the radiotherapy dose optimization of the ROI are performed at least partially overlap temporally (para. [0051]) motivated by the benefits for optimizing an adapted treatment plan in an adaptive workflow (Peltola et al. para. [0016]).
In light of the benefits for optimizing an adapted treatment plan in an adaptive workflow as taught by Peltola 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 Purdie et al. with the teachings Peltola et al.
Regarding claim 2, Purdie et al. disclose: the modified delineation of the ROI is determined by manually modifying the delineation of the ROI (para. [0187]).
Regarding claim 3, Peltola et al. disclose: the operations further includes: while performing the radiotherapy dose optimization on the ROI, outputting in real time a dose distribution result and a dose volume histogram (DVH) corresponding to the radiotherapy dose being optimized (para. [0051]) motivated by the benefits for optimizing an adapted treatment plan in an adaptive workflow (Peltola et al. para. [0016]).
Regarding claim 4, Purdie et al. disclose: the determining the target radiotherapy plan of the object includes: determining, based on the modified delineation of the ROI, whether to perform the radiotherapy dose optimization on the ROI based on an initial radiotherapy plan (para. [0125]).
Regarding claim 12, Purdie et al. disclose: the target radiotherapy plan is determined online during a radiotherapy treatment session of the object that includes a delivery of the radiotherapy dose to the at least one target region of the object (para. [0023]-[0024]).
Regarding claim 13, Purdie et al. disclose: the image of the object is an identification image that is determined using a trained identification model, the trained identification model being configured to delineate the at least one target region and the specific region in an initial image to determine the identification image, and the operations further include determining a radiotherapy dose of the specific region based on the identification image (para. [0068], [0071]).
Regarding claim 15, Purdie et al. disclose: the determining the radiotherapy dose of the specific region based on the identification image includes: determining an optimization objective by performing a dose prediction based on the delineation of the specific region; obtaining a dose constraint corresponding to the specific region based on the optimization objective; and determining the radiotherapy dose of the specific region based on the dose constraint (para. [0060], [0307]).
Regarding claim 16, Purdie et al. disclose: the obtaining the dose constraint corresponding to the specific region based on the feature of the specific region includes: determining, using a dose distribution prediction model, the dose constraint corresponding to the specific region (para. [0060], [0307]).
Regarding claim 20, Purdie et al. disclose: A method for radiotherapy planning, implemented on a computing device having at least one storage device storing a set of instructions, and at least one processor in communication with the at least one storage device (para. [0023]), the method comprising:
obtaining a delineation of a region of interest (ROI) in an image of an object, the ROI including at least one target region (para. [0097], [0130]);
obtaining a modified delineation of the ROI based on one or more modifications to the delineation of the ROI (para. [0125]); and
determining a target radiotherapy plan of the object by performing a radiotherapy dose optimization on the ROI (para. [0060]).
Purdie et al. are silent about: the modifications of the delineation of the ROI and the radiotherapy dose optimization of the ROI are performed at least partially overlap temporally.
In a similar field of endeavor Peltola et al. disclose: the modifications of the delineation of the ROI and the radiotherapy dose optimization of the ROI are performed at least partially overlap temporally (para. [0051]) motivated by the benefits for optimizing an adapted treatment plan in an adaptive workflow (Peltola et al. para. [0016]).
In light of the benefits for optimizing an adapted treatment plan in an adaptive workflow as taught by Peltola 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 Purdie et al. with the teachings Peltola et al.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Purdie et al. (US 2018/0211725 A1; pub. Jul. 26, 2018) in view of Peltola et al. (US 2021/0069527 A1; pub. Mar. 11, 2021) and further in view of Da Silva Rodrigues et al. (US 2018/0318605 A1; pub. Nov. 8, 2018).
Regarding claim 10, the combined references are silent about: the determining the target radiotherapy plan of the object includes:
determining at least one predicted delineation of the ROI by predicting a modification of the delineation of the ROI;
determining at least one predicted radiotherapy plan of the object by performing, based on the at least one predicted delineation of the ROI, the radiotherapy dose optimization on the ROI; and
determining the target radiotherapy plan of the object by evaluating, based on the modified delineation of the ROI, the at least one predicted radiotherapy plan.
In a similar field of endeavor Da Silva Rodrigues et al. disclose: the determining the target radiotherapy plan of the object includes:
determining at least one predicted delineation of the ROI by predicting a modification of the delineation of the ROI;
determining at least one predicted radiotherapy plan of the object by performing, based on the at least one predicted delineation of the ROI, the radiotherapy dose optimization on the ROI; and
determining the target radiotherapy plan of the object by evaluating, based on the modified delineation of the ROI, the at least one predicted radiotherapy plan (para. [0017]-[0018], [0020]) motivated by the benefits for a more efficient generation of a treatment plan for a radiotherapy treatment (Da Silva Rodrigues et al. para. [0008]).
In light of the benefits for a more efficient generation of a treatment plan for a radiotherapy treatment as taught by Da Silva Rodrigues 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 Purdie et al. and Peltola et al. with the teachings Da Silva Rodrigues et al.
Claims 14, 17 are rejected under 35 U.S.C. 103 as being unpatentable over Purdie et al. (US 2018/0211725 A1; pub. Jul. 26, 2018) in view of Peltola et al. (US 2021/0069527 A1; pub. Mar. 11, 2021) and further in view of Chen et al. (US 2022/0296930 A1; pub. Sep. 22, 2022).
Regarding claim 14, the combined references are silent about: the trained identification model includes a first sub-model and a second sub-model, and the determining the identification image using the trained identification model includes: determining, using the first sub-model, an intermediate identification image based on the initial image, the intermediate identification image including delineations of the at least one target region; and determining the identification image by delineating the specific region in the intermediate identification image using the second sub-model.
In a similar field of endeavor Chen et al. disclose: the trained identification model includes a first sub-model and a second sub-model, and the determining the identification image using the trained identification model includes: determining, using the first sub-model, an intermediate identification image based on the initial image (para. [0065], [0140]), the intermediate identification image including delineations of the at least one target region; and determining the identification image by delineating the specific region in the intermediate identification image using the second sub-model (para. [0081]) motivated by the benefits for a treatment that is adapted in real time in response to changes in tumor position, shape, biology and spatial relationship to critical organs at the time of treatment (Chen et al. para. [0005]).
In light of the benefits for a treatment that is adapted in real time in response to changes in tumor position, shape, biology and spatial relationship to critical organs at the time of treatment as taught by Chen 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 Purdie et al. and Peltola et al. with the teachings Chen et al.
Regarding claim 17, the combined references are silent about: the second sub-model is obtained by a training process including: obtaining a plurality of training samples, each of the plurality of training samples including a sample image and a label image corresponding to the sample image, the sample image including delineations of at least one sample target region, the label image including a delineation of a sample specific region; and obtaining the second sub-model by training, based on the plurality of training samples, a preliminary second sub-model.
In a similar field of endeavor Chen et al. disclose: the second sub-model is obtained by a training process including: obtaining a plurality of training samples, each of the plurality of training samples including a sample image and a label image corresponding to the sample image, the sample image including delineations of at least one sample target region, the label image including a delineation of a sample specific region; and obtaining the second sub-model by training, based on the plurality of training samples, a preliminary second sub-model (para. [0065], [0081], [0140]) motivated by the benefits for a treatment that is adapted in real time in response to changes in tumor position, shape, biology and spatial relationship to critical organs at the time of treatment (Chen et al. para. [0005]).
In light of the benefits for a treatment that is adapted in real time in response to changes in tumor position, shape, biology and spatial relationship to critical organs at the time of treatment as taught by Chen 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 Purdie et al. and Peltola et al. with the teachings Chen et al.
Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over Purdie et al. (US 2018/0211725 A1; pub. Jul. 26, 2018) in view of Chen et al. (US 2022/0296930 A1; pub. Sep. 22, 2022).
Regarding claim 19, Purdie et al. are silent about: the trained identification model includes a first sub-model and a second sub-model, and
the determining the identification image using the trained identification model includes:
determining, using the first sub-model, an intermediate identification image based on the initial image, the intermediate identification image including delineations of the at least one target region; and determining the identification image by delineating the specific region in the
intermediate identification image using the second sub-model.
In a similar field of endeavor Chen et al. disclose: the trained identification model includes a first sub-model and a second sub-model, and
the determining the identification image using the trained identification model includes:
determining, using the first sub-model, an intermediate identification image based on the initial image, the intermediate identification image including delineations of the at least one target region; and determining the identification image by delineating the specific region in the
intermediate identification image using the second sub-model (para. [0065], [0081], [0140]) motivated by the benefits for a treatment that is adapted in real time in response to changes in tumor position, shape, biology and spatial relationship to critical organs at the time of treatment (Chen et al. para. [0005]).
In light of the benefits for a treatment that is adapted in real time in response to changes in tumor position, shape, biology and spatial relationship to critical organs at the time of treatment as taught by Chen 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 Purdie et al. with the teachings Chen et al.
Allowable Subject Matter
Claims 5 -9, 11 are 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.
Regarding claim 5, the prior arts alone or in combination fail to teach, disclose, suggest or render obvious: the determining, based on the modified delineation of the ROI, whether to perform the radiotherapy dose optimization on the ROI based on the initial radiotherapy plan includes:
in response to that the modified delineation of the ROI satisfies a condition, performing the radiotherapy dose optimization on the ROI based on the initial radiotherapy plan; and
in response to that the modified delineation of the ROI fails to satisfy the condition, abandoning the initial radiotherapy plan and performing the radiotherapy dose optimization on the ROI based on the modified delineation of the ROI.
Claims 6-9 would be allowable on the same basis as claim 5 for dependency reasons.
Regarding claim 11, the prior arts alone or in combination fail to teach, disclose, suggest or render obvious: the determining the target radiotherapy plan of the object includes:
determining a probability density distribution of each of voxels or pixels corresponding to the ROI, the probability density distribution indicating a probability that the each voxel or pixel belongs to the ROI;
determining a predicted radiotherapy plan of the object by performing, based on probability density distributions corresponding to the pixels or voxels in the ROI, the radiotherapy dose optimization on the ROI; and
determining the target radiotherapy plan of the object by evaluating, based on the modified delineation, the predicted radiotherapy plan.
Regarding claim 21, the prior arts alone or in combination fail to teach, disclose, suggest or render obvious: the determining, based on the modified delineation of the ROI, whether to perform the radiotherapy dose optimization on the ROI based on the initial radiotherapy plan includes:
in response to that the modified delineation of the ROI satisfies a condition, performing the radiotherapy dose optimization on the ROI based on the initial radiotherapy plan.
Regarding claim 22, the prior arts alone or in combination fail to teach, disclose, suggest or render obvious: the determining, based on the modified delineation of the ROI, whether to perform the radiotherapy dose optimization on the ROI based on the initial radiotherapy plan includes: in response to that the modified delineation of the ROI fails to satisfy a condition, abandoning the initial radiotherapy plan and performing the radiotherapy dose optimization on the ROI based on the modified delineation of the ROI.
Claim 18 is allowed.
The following is an examiner’s statement of reasons for allowance:
Regarding claim 18, Purdie et al. disclose: A system, comprising: at least one storage device including a set of instructions; and at least one processor in communication with the at least one storage device, wherein when executing the set of instructions, the at least one processor causes the system to perform operations (para. [0023]) including: obtaining an initial image of an object, the initial image including at least one target region (para. [0018]-[0019]); determining an identification image using a trained identification model (para. [0054]-[0057]).
Chen et al. disclose: the trained identification model includes a first sub-model and a second sub-model (para. [0065], [0081], [0140]).
The prior arts alone or in combination fail to teach, disclose, suggest or render obvious: the determining the identification image using the trained identification model includes: determining, using the first sub-model, an intermediate identification image based on the initial image, the intermediate identification image including delineations of the at least one target region; and determining the identification image by delineating a specific region in the intermediate identification image using the second determining a radiotherapy dose of the specific region based on the identification image.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
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.
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/MAMADOU FAYE/Examiner, Art Unit 2884
/UZMA ALAM/ Supervisory Patent Examiner, Art Unit 2884
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