Prosecution Insights
Last updated: April 19, 2026
Application No. 17/881,763

PROVISION OF A THERAPY PLAN

Non-Final OA §102§103
Filed
Aug 05, 2022
Examiner
BASET, NESHAT
Art Unit
3798
Tech Center
3700 — Mechanical Engineering & Manufacturing
Assignee
Siemens Healthcare GmbH
OA Round
3 (Non-Final)
30%
Grant Probability
At Risk
3-4
OA Rounds
3y 11m
To Grant
58%
With Interview

Examiner Intelligence

Grants only 30% of cases
30%
Career Allow Rate
19 granted / 63 resolved
-39.8% vs TC avg
Strong +28% interview lift
Without
With
+27.6%
Interview Lift
resolved cases with interview
Typical timeline
3y 11m
Avg Prosecution
47 currently pending
Career history
110
Total Applications
across all art units

Statute-Specific Performance

§101
11.9%
-28.1% vs TC avg
§103
48.1%
+8.1% vs TC avg
§102
13.7%
-26.3% vs TC avg
§112
20.3%
-19.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 63 resolved cases

Office Action

§102 §103
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 . 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 11/20/2025 has been entered. Response to Amendment This office action is in response to the remarks filed on 11/20/2025. The amendment filed 11/20/2025 has been entered. Claims 1-15 and 17-20 remain pending in the application, claim 16 has been canceled, and claims 4 and 11-12 have been previously withdrawn. The 35 U.S.C. § 101 rejection has been withdrawn in light of amendments. Claim Rejections - 35 USC § 102 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. Claims 1-3, 5-7, 13-15, and 17-18 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Schulz et al. (US 20110130614 A1, hereinafter "Schulz"). Regarding claim 1, Schulz teaches: receiving a dataset that is preacquired, (Acquired images are stored in an images memory 12 [0023], fig. 1) wherein the dataset maps an examination object including a first tissue area at at least one first timepoint ([0014] and [0023] disclose a “planning image” which an image that is received that is segmented into segments delineating a target feature to be irradiated, i.e. maps a first tissue area at a first time point); identifying a mapping of the first tissue area in the dataset as a first state ([0014] and [0023] discloses the “planning image” which maps out a first tissue area that needs to be treated, i.e. the first state); specifying a second state for the first tissue area, wherein the second state defines a spatial extent ([0029] and [0039] disclose that the “foreseeable change”,i.e. second state includes shrinking tumor or necrotizing areas of the tumor i.e. a spatial extent), a second tissue parameter, or a combination thereof of at least a part of the first tissue area at at least one second timepoint, the at least one second timepoint being after the at least one first timepoint ([0013]-[0014], [0028]-[0029] discloses adjusting segments from the planning image or the “first state” to form an image that represents a “foreseeable change”, which is a second state for the first tissue area that takes place at second timepoint after the first timepoint where the area shrinks) ; determining a therapy plan for a therapy apparatus (radiation therapy plan selector 30 [0044], fig 1) by application of a model to input data ([0044] discloses that the therapy plan 30 utilizes input data), wherein the input data is based on the dataset and the second state ([0023] discloses that the input data includes the preparatory image/data set and the second state), wherein the therapy plan has at least one parameter for control of the therapy apparatus (therapy control system 34 to deliver the therapeutic radiation in accordance with the selected most appropriate radiation therapy plan [0035]), wherein a change in the first tissue area between the at least one first timepoint and the at least one second timepoint is createable through the control of the therapy apparatus in accordance with the therapy plan (Once the radiation therapy plan selector 30 selects the most appropriate radiation therapy plan, a suitable apparatus 32 for delivering therapeutic radiation is controlled by a suitable radiation therapy control system 34 to deliver the therapeutic radiation in accordance with the selected most appropriate radiation therapy plan [0035]), wherein the model simulates future anatomical changes including (For a first one of the predicted changes 42, the segments of the segmented planning image 40 is or are adjusted to the predicted deformation or deformations (or density change or changes or other change or changes) in a computational operation 44. For geometric anatomical changes, such as tumor shrinkage or growth, organ movement, size, or shape changes, or so forth, the deformational operation 44 optionally utilizes the deformational feature models 22 to model the foreseen geometric anatomical change [0039]) a biological growth and the change in the first tissue area between the at least one first timepoint and the at least one second timepoint, and wherein the model maps the first state to the second state, the second state to the first state, or a combination thereof (the segments of the segmented planning image 40 is or are adjusted to the predicted deformation or deformations (or density change or changes or other change or changes) in a computational operation 44. For geometric anatomical changes, such as tumor shrinkage or growth, organ movement, size, or shape changes, or so forth, the deformational operation 44 optionally utilizes the deformational feature models 22 to model the foreseen geometric anatomical change [0039]); and providing the therapy plan as output data of the model (Once the radiation therapy plan selector 30 selects the most appropriate radiation therapy plan, a suitable apparatus 32 for delivering therapeutic radiation is controlled by a suitable radiation therapy control system 34 to deliver the therapeutic radiation in accordance with the selected most appropriate radiation therapy plan [0035]; The output of the predicted change operation 44 is an adjusted segmented planning image 46, which is then input to the radiation therapy planner 16 to generate the predictive adapted radiation therapy plan that is also stored in the radiation therapy plans data storage 18 [0040]). PNG media_image1.png 1306 1047 media_image1.png Greyscale Fig. 1 of Schulz reproduced above executing the therapy plan (performing a therapy session on the subject in accordance with a selected one of the plurality of therapy plans [0011]), the executing of the therapy plan comprising controlling a therapy apparatus based on the therapy plan (The output of the predicted change operation 44 is an adjusted segmented planning image 46, which is then input to the radiation therapy planner 16 to generate the predictive adapted radiation therapy plan that is also stored in the radiation therapy plans data storage 18 [0040]), wherein the executed therapy plan accounts for the future anatomical changes, which are after the therapy plan is executed (Once the radiation therapy plan selector 30 selects the most appropriate radiation therapy plan, a suitable apparatus 32 for delivering therapeutic radiation is controlled by a suitable radiation therapy control system 34 to deliver the therapeutic radiation in accordance with the selected most appropriate radiation therapy plan [0035]). Regarding claim 2, Schulz teaches the method of claim 1, as discussed above. Schulz further teaches wherein the spatial extent is a maximum spatial extent ([0029] discloses that the spatial extent can include the second state “foreseeable change” includes areas where the tumor can both grow or shrink, i.e. the maximum spatial extent to which the tumor spreads). Regarding claim 3, Schulz teaches the method of claim 1, as discussed above. Schulz further teaches wherein the dataset has at least one first tissue parameter of the first tissue area ([0031] discloses that the dataset includes segmenting the first area to find features within the area including tumors, critical areas, etc.), a further tissue area, or the first tissue area and the further tissue area, wherein the further tissue area borders on the first tissue area. Regarding claim 5, Schulz teaches the method of claim 1, as discussed above. Schulz further teaches wherein identifying the mapping of the first tissue area comprises identifying a mapping of at least one critical structure ([0023]-[0024] discloses critical features affecting radiation include organs that are not to be irradiated), an edge area, or the at least one critical structure and the edge area of the first tissue area in the dataset, and wherein the model leaves out the at least one critical structure, the edge area, or the at least one critical structure and the edge area in the simulation of the change in the first tissue area (([0023]-[0024] discloses critical features affecting radiation include organs that are not to be irradiated, and how the model takes this into account to avoid those areas during the therapeutic treatment; [0032] further discloses that critical structures are accommodated for in the therapeutic plan). Regarding claim 6, Schulz teaches the method of claim 1, as discussed above. Schulz further teaches wherein the second state defines a value, a range of values, or the value and the range of values for the spatial extent ([0040] discloses shrinking the tumor/area by any preferred percentage, i.e. the value and the range of values for the spatial extent), the second tissue parameter of the at least one part of the first tissue area for the at least one second timepoint, a period of time comprising a number of second timepoints, up to a temporal maximum value, or comprising the number of second timepoints and up to a temporal maximum value, or any combination thereof. Regarding claim 7, Schulz teaches the method of claim 1, as discussed above. Schulz further teaches: wherein the first tissue area, in at least one area, borders on a further tissue area ([0031] discloses that the preparatory image includes multiple features that are segmented out, i.e. the first tissue area borders on a further tissue area), and wherein the second state defines the value, the range of values, or the value and the range of values for the spatial extent ([0040] discloses shrinking the tumor/area by any preferred percentage, i.e. the value and the range of values for the spatial extent), the second tissue parameter at least for the border, or a combination thereof. Regarding claim 13, Schulz teaches the method of claim 1, as discussed above. Schulz further teaches: wherein the dataset maps an initial change in the first tissue area ([0031] discloses if a change takes place prior to therapy, then geometrical features of the area is updated, along with the therapy plan), wherein the initial change has been created before a beginning of the method by the therapy apparatus in accordance with an initial therapy plan ([0027] discloses the initial change takes place prior to the therapy), and wherein the dataset also has the initial therapy plan ([0031]-[0034] disclose that all therapy plans are taken into consideration prior to selection of the best therapy plan). Regarding claim 14, Schulz teaches the method of claim 1, as discussed above. Schulz further teaches: wherein providing the therapy plan comprises transmitting the at least one parameter to the therapy apparatus (Once the radiation therapy plan selector 30 selects the most appropriate radiation therapy plan, a suitable apparatus 32 for delivering therapeutic radiation is controlled by a suitable radiation therapy control system 34 to deliver the therapeutic radiation in accordance with the selected most appropriate radiation therapy plan [0035]), performing a preparatory adjustment of at least one operating parameter, at least one positioning parameter, or the at least one operating parameter and the at least one positioning parameter to the therapy apparatus in accordance with the therapy plan, or a combination thereof. Regarding claim 15, Schulz teaches the method of claim 14, as discussed above. Schulz further teaches: wherein the transmitting, the performing, or the transmitting and the performing are without the control of the therapy apparatus ([0099] discloses that the radiation plan gets developed prior to sending to the therapy apparatus). Regarding claim 17, Schulz teaches a provision unit for provision of a therapy plan, the provision unit comprising: a processor (processor [0036]) configured to: receive a dataset that is preacquired (Acquired images are stored in an images memory 12 [0023], fig. 1), wherein the dataset maps an examination object including a first tissue area at at least one first timepoint ([0014] and [0023] disclose a “planning image” which an image that is received that is segmented into segments delineating a target feature to be irradiated, i.e. maps a first tissue area at a first time point); identify a mapping of the first tissue area in the dataset as a first state ([0014] and [0023] discloses the “planning image” which maps out a first tissue area that needs to be treated, i.e. the first state); specify a second state for the first tissue area, wherein the second state defines a spatial extent ([0029] and [0039] disclose that the “foreseeable change”,i.e. second state includes shrinking tumor or necrotizing areas of the tumor i.e. a spatial extent), a second tissue parameter, or a combination thereof of at least a part of the first tissue area at at least one second timepoint, the at least one second timepoint being after the at least one first timepoint([0013]-[0014], [0028]-[0029] discloses adjusting segments from the planning image or the “first state” to form an image that represents a “foreseeable change”, which is a second state for the first tissue area that takes place at second timepoint after the first timepoint where the area shrinks); determine a therapy plan for a therapy apparatus (radiation therapy plan selector 30 [0044], fig 1) by application of a model to input data ([0044] discloses that the therapy plan 30 utilizes input data), wherein the input data is based on the dataset and the second state ([0023] discloses that the input data includes the preparatory image/data set and the second state), wherein the therapy plan has at least one parameter for control of the therapy apparatus (therapy control system 34 to deliver the therapeutic radiation in accordance with the selected most appropriate radiation therapy plan [0035]), wherein a change in the first tissue area between the at least one first timepoint and the at least one second timepoint is createable through the control of the therapy apparatus in accordance with the therapy plan (Once the radiation therapy plan selector 30 selects the most appropriate radiation therapy plan, a suitable apparatus 32 for delivering therapeutic radiation is controlled by a suitable radiation therapy control system 34 to deliver the therapeutic radiation in accordance with the selected most appropriate radiation therapy plan [0035]), wherein the model simulates future anatomical changes (For a first one of the predicted changes 42, the segments of the segmented planning image 40 is or are adjusted to the predicted deformation or deformations (or density change or changes or other change or changes) in a computational operation 44. For geometric anatomical changes, such as tumor shrinkage or growth, organ movement, size, or shape changes, or so forth, the deformational operation 44 optionally utilizes the deformational feature models 22 to model the foreseen geometric anatomical change [0039]) including a biological growth and the change in the first tissue area between the at least one first timepoint and the at least one second timepoint, and wherein the model maps the first state to the second state, the second state to the first state, or a combination thereof (the segments of the segmented planning image 40 is or are adjusted to the predicted deformation or deformations (or density change or changes or other change or changes) in a computational operation 44. For geometric anatomical changes, such as tumor shrinkage or growth, organ movement, size, or shape changes, or so forth, the deformational operation 44 optionally utilizes the deformational feature models 22 to model the foreseen geometric anatomical change [0039]); provide the therapy plan as output data of the model (Once the radiation therapy plan selector 30 selects the most appropriate radiation therapy plan, a suitable apparatus 32 for delivering therapeutic radiation is controlled by a suitable radiation therapy control system 34 to deliver the therapeutic radiation in accordance with the selected most appropriate radiation therapy plan [0035]; The output of the predicted change operation 44 is an adjusted segmented planning image 46, which is then input to the radiation therapy planner 16 to generate the predictive adapted radiation therapy plan that is also stored in the radiation therapy plans data storage 18 [0040]). execute therapy plan (performing a therapy session on the subject in accordance with a selected one of the plurality of therapy plans [0011]), the execution of the therapy plan comprising control of a therapy apparatus based on the therapy plan, wherein the executed therapy plan accounts for the future anatomical changes, which are after the therapy plan is executed (Once the radiation therapy plan selector 30 selects the most appropriate radiation therapy plan, a suitable apparatus 32 for delivering therapeutic radiation is controlled by a suitable radiation therapy control system 34 to deliver the therapeutic radiation in accordance with the selected most appropriate radiation therapy plan [0035]).. Regarding claim 18, Schulz teaches a system comprising: a provision unit for provision of a therapy plan (suitable apparatus 32 for delivering therapeutic radiation [0035]), the provision unit comprising: a processor (processor [0036]) configured to: receive a dataset that is preacquired (Acquired images are stored in an images memory 12 [0023], fig. 1), wherein the dataset maps an examination object including a first tissue area at at least one first timepoint ([0014] and [0023] disclose a “planning image” which an image that is received that is segmented into segments delineating a target feature to be irradiated, i.e. maps a first tissue area at a first time point); identify a mapping of the first tissue area in the dataset as a first state ([0014] and [0023] discloses the “planning image” which maps out a first tissue area that needs to be treated, i.e. the first state); specify a second state for the first tissue area, wherein the second state defines a spatial extent ([0029] and [0039] disclose that the “foreseeable change”,i.e. second state includes shrinking tumor or necrotizing areas of the tumor i.e. a spatial extent), a second tissue parameter, or a combination thereof, of at least a part of the first tissue area at at least one second timepoint, the at least one second timepoint being after the at least one first timepoint ([0013]-[0014], [0028]-[0029] discloses adjusting segments from the planning image or the “first state” to form an image that represents a “foreseeable change”, which is a second state for the first tissue area that takes place at second timepoint after the first timepoint where the area shrinks); determine a therapy plan for a therapy apparatus (radiation therapy plan selector 30 [0044], fig 1) by application of a model to input data ([0044] discloses that the therapy plan 30 utilizes input data), wherein the input data is based on the dataset and the second state ([0023] discloses that the input data includes the preparatory image/data set and the second state), wherein the therapy plan has at least one parameter for control of the therapy apparatus (therapy control system 34 to deliver the therapeutic radiation in accordance with the selected most appropriate radiation therapy plan [0035]), wherein a change in the first tissue area between the at least one first timepoint and the at least one second timepoint is createable through the control of the therapy apparatus in accordance with the therapy plan (Once the radiation therapy plan selector 30 selects the most appropriate radiation therapy plan, a suitable apparatus 32 for delivering therapeutic radiation is controlled by a suitable radiation therapy control system 34 to deliver the therapeutic radiation in accordance with the selected most appropriate radiation therapy plan [0035]), wherein the model simulates future anatomical changes (For a first one of the predicted changes 42, the segments of the segmented planning image 40 is or are adjusted to the predicted deformation or deformations (or density change or changes or other change or changes) in a computational operation 44. For geometric anatomical changes, such as tumor shrinkage or growth, organ movement, size, or shape changes, or so forth, the deformational operation 44 optionally utilizes the deformational feature models 22 to model the foreseen geometric anatomical change [0039]) including a biological growth and the change in the first tissue area between the at least one first timepoint and the at least one second timepoint, and wherein the model maps the first state to the second state, the second state to the first state, or a combination thereof (the segments of the segmented planning image 40 is or are adjusted to the predicted deformation or deformations (or density change or changes or other change or changes) in a computational operation 44. For geometric anatomical changes, such as tumor shrinkage or growth, organ movement, size, or shape changes, or so forth, the deformational operation 44 optionally utilizes the deformational feature models 22 to model the foreseen geometric anatomical change [0039]); and provide the therapy plan as output data of the model (Once the radiation therapy plan selector 30 selects the most appropriate radiation therapy plan, a suitable apparatus 32 for delivering therapeutic radiation is controlled by a suitable radiation therapy control system 34 to deliver the therapeutic radiation in accordance with the selected most appropriate radiation therapy plan [0035]; The output of the predicted change operation 44 is an adjusted segmented planning image 46, which is then input to the radiation therapy planner 16 to generate the predictive adapted radiation therapy plan that is also stored in the radiation therapy plans data storage 18 [0040]). wherein the therapy apparatus is configured to create the change in the first tissue area (a suitable apparatus 32 for delivering therapeutic radiation [0035]), wherein the provision unit is configured to control the therapy apparatus with the aid of the therapy plan such that the change is created in the first tissue area between the at least one timepoint and the at least one second timepoint (Once the radiation therapy plan selector 30 selects the most appropriate radiation therapy plan, a suitable apparatus 32 for delivering therapeutic radiation is controlled by a suitable radiation therapy control system 34 to deliver the therapeutic radiation in accordance with the selected most appropriate radiation therapy plan [0035]), and wherein the therapy plan, with the aid of which the therapy apparatus is controlled, accounts for the future anatomical changes, which are after the therapy apparatus is controlled with the aid of the therapy plan (Once the radiation therapy plan selector 30 selects the most appropriate radiation therapy plan, a suitable apparatus 32 for delivering therapeutic radiation is controlled by a suitable radiation therapy control system 34 to deliver the therapeutic radiation in accordance with the selected most appropriate radiation therapy plan [0035]). 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. 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 8-10 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Schulz et al. (US 20110130614 A1, hereinafter "Schulz") in view of Thomas (US 20190198177 A1, hereinafter "Thomas") . Regarding claim 8, Schulz teaches the method of claim 1, as discussed above. Schulz, however, does not teach wherein, during the control of the therapy apparatus in accordance with the therapy plan, at least one lesion is creatable in the first tissue area, wherein the model simulates a reduction in the spatial extent of the first tissue area, a change in the second tissue parameter as the change between the at least one first timepoint and the at least one second timepoint, or a combination thereof, and wherein the simulation of the change comprises a simulation of a transporting away of lysed tissue from the at least one lesion. Thomas is considered analogous to the instant application as “Simulation and patient-specific scale tissue modelling of the growth of prostate cancer” is disclosed (title). Thomas teaches: during the control of the therapy apparatus in accordance with the therapy plan, at least one lesion is creatable in the first tissue area ([0081], [0083] describes selectively killing cells using radiation in a tumor, i.e. lysed tissue, displaying the simulation on a display), wherein the model simulates a reduction in the spatial extent of the first tissue area ([0081], [0083] describes selectively killing cells using radiation in a tumor, i.e. lysed tissue, displaying the simulation on a display, selectively killing cells depicts a reduction the spatial extent of the first tissue area), wherein the simulation of the change comprises a simulation of a transporting away of lysed tissue from the at least one lesion ([0039]-[0040] discloses that simulation takes place inside of the body, changes of the tumor/cancer takes place physiologically; [0081], [0083] describes selectively killing cells using radiation in a tumor, i.e. lysed tissue, displaying the simulation on a display). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the invention to include wherein, during the control of the therapy apparatus in accordance with the therapy plan, at least one lesion is creatable in the first tissue area, wherein the model simulates a reduction in the spatial extent of the first tissue area, and wherein the simulation of the change comprises a simulation of a transporting away of lysed tissue from the at least one lesion, as taught by Thomas. Doing so would aid in the diagnosis of the disease, the prediction of its evolution, assessment of alternative treatments, and management of follow-up, as suggested by Thomas ([0095]). Regarding claim 9, modified Schulz teaches the method of claim 8, as discussed above. Schulz, however, does not teach wherein the transporting is physiological transporting. Thomas, however, teaches: wherein the transporting is physiological transporting ([0039] simulation takes place inside of the body, changes of the tumor/cancer takes place physiologically). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the invention to include wherein the transporting is physiological transporting, as taught by Thomas. Doing so would aid in the diagnosis of the disease, the prediction of its evolution, assessment of alternative treatments, and management of follow-up, as suggested by Thomas ([0095]). Regarding claim 10, modified Schulz teaches the method of claim 8, as discussed above. Schulz, however, does not teach wherein the therapy apparatus has an ultrasound unit, wherein therapeutic ultrasound is emittable by the ultrasound unit during the control of the therapy apparatus in accordance with the therapy plan into the first tissue area, wherein the at least one parameter predetermines a frequency, a bandwidth, an amplitude, a phase, a pulse duration, a focus position, a beam alignment, a beam shaping, a duty cycle, or any combination thereof of the therapeutic ultrasound, such that the at least one lesion is creatable in the first tissue area by the therapeutic ultrasound. Thomas, however, teaches:wherein the therapy apparatus has an ultrasound unit (HIFU treatment [0083]), wherein therapeutic ultrasound is emittable by the ultrasound unit during the control of the therapy apparatus in accordance with the therapy plan into the first tissue area (a type of prostate cancer treatment (e.g., chemotherapy, radiation, surgery, high intensity focused ultrasound (HIFU), hormonal therapy, etc.) for the subject may be selected based on the output dataset. [0078]; a session of radiation treatment in order to radiatively kill cells in at least a portion of the tumor may be planned based on the output dataset [0081]; a session of high intensity focused ultrasound (HIFU) may be planned based on the output dataset, in order to kill cells in at least a portion of the tumor. A plan for the HIFU session may be outputted via an output device (e.g., displayed via a display device) [0083]); , wherein the at least one parameter predetermines a beam alignment (a trajectory of beam direction and intensity for a radiation beam may be determined based on the output dataset [0081]), such that the at least one lesion is creatable in the first tissue area by the therapeutic ultrasound ([0083] discloses killing cells in at least a portion of a tumor/ i.e. forming a lesion). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the invention to include wherein therapeutic ultrasound is emittable by the ultrasound unit during the control of the therapy apparatus in accordance with the therapy plan into the first tissue area, wherein therapeutic ultrasound is emittable by the ultrasound unit during the control of the therapy apparatus in accordance with the therapy plan into the first tissue area, and wherein the at least one parameter predetermines a beam alignment, as taught by Thomas. Doing so would aid in the diagnosis of the disease, the prediction of its evolution, assessment of alternative treatments, and management of follow-up, as suggested by Thomas ([0095]). Regarding claim 19, modified Schulz teaches system of claim 18, as discussed above. Schulz further teaches wherein the therapy apparatus includes an ultrasound unit (high intensity focused ultrasound (HIFU) procedures and HIFU planning). Schulz, however, does not teach: wherein the ultrasound unit is configured to send therapeutic ultrasound into the first tissue area, and wherein the therapeutic ultrasound is configured to create at least one lesion in the first tissue area as the change. Thomas is considered analogous to the instant application as “Simulation and patient-specific scale tissue modelling of the growth of prostate cancer” is disclosed (title). Thomas teaches: wherein the ultrasound unit is configured to send therapeutic ultrasound into the first tissue area (a session of radiation treatment in order to radiatively kill cells in at least a portion of the tumor may be planned based on the output dataset [0081]; a session of high intensity focused ultrasound (HIFU) may be planned based on the output dataset, in order to kill cells in at least a portion of the tumor. A plan for the HIFU session may be outputted via an output device (e.g., displayed via a display device) [0083]), and wherein the therapeutic ultrasound is configured to create at least one lesion in the first tissue area as the change (radiatively kill cells in at least a portion of the tumor may be planned based on the output dataset [0081]; killing cells in a at least part of the tumor is the lesion as claimed). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the invention to include wherein the ultrasound unit is configured to send therapeutic ultrasound into the first tissue area, and wherein the therapeutic ultrasound is configured to create at least one lesion in the first tissue area as the change, as taught by Thomas. Doing so would aid in the diagnosis of the disease, the prediction of its evolution, assessment of alternative treatments, and management of follow-up, as suggested by Thomas ([0095]). Regarding claim 20, modified Schulz teaches system of claim 18, as discussed above. Schulz further teaches: a medical imaging device (imaging modality 10 [0022], fig. 1), wherein the medical imaging device is configured to record (imaging modality 10 suitable for acquiring planning images for planning the radiation therapy [0022]), provide, or record and provide the dataset. Response to Arguments Applicant's arguments filed 06/19/2025 have been fully considered but they are not persuasive. Regarding the 35 U.S.C. § 102 rejection of claim 1, applicant argues on pages 10-13 hat Schulz does not teach or disclose “Schulz et al. do not teach or disclose that "the executed therapy plan accounts for the future anatomical changes, which are after the therapy plan is executed”. The examiner respectfully disagrees. Schulz discloses, as noted in the rejection above, in paragraph [0039], that “For a first one of the predicted changes 42, the segments of the segmented planning image 40 is or are adjusted to the predicted deformation or deformations (or density change or changes or other change or changes) in a computational operation 44. For geometric anatomical changes, such as tumor shrinkage or growth, organ movement, size, or shape changes, or so forth, the deformational operation 44 optionally utilizes the deformational feature models 22 to model the foreseen geometric anatomical change”. Schulz further discloses in [0035] and [0040] that based off of the predicted change, the therapy plan is selected and executed. The predicted changes takes place before the therapy takes place. Accordingly, the argument is not persuasive and the rejection is maintained. Accordingly, this argument is not persuasive and the 35 U.S.C. § 102 rejection of claims 1 and 17 is maintained. Applicant argues that claims 2, 3, 5-10, and 13-15 are allowable due to dependency on allowable claim 1 on page 13. The examiner respectfully disagrees for the reasons noted above. Regarding the 35 U.S.C. § 102 rejection of claims 17 and 18, the applicant’s arguments are premised upon the assertion that the claims are allowable for the same reasons as claim 1 on page 14 of remarks. The examiner respectfully disagrees for the reasons noted above. Applicant argues that claims 19 and 20 are allowable due to dependency on allowable claim 18 on page 14 of remarks. The examiner respectfully disagrees for the reasons noted above. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to NESHAT BASET whose telephone number is (571)272-5478. The examiner can normally be reached M-F 8:30-17:30 CST. 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, PASCAL M. BUI-PHO can be reached at (571) 272-2714. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /N.B./ Examiner, Art Unit 3798 /PASCAL M BUI PHO/ Supervisory Patent Examiner, Art Unit 3798
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Prosecution Timeline

Aug 05, 2022
Application Filed
Mar 08, 2025
Non-Final Rejection — §102, §103
Jun 19, 2025
Response Filed
Aug 15, 2025
Final Rejection — §102, §103
Nov 20, 2025
Request for Continued Examination
Dec 03, 2025
Response after Non-Final Action
Dec 19, 2025
Non-Final Rejection — §102, §103 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12582377
ULTRASOUND BASED THREE-DIMENSIONAL LESION VERIFICATION WITHIN A VASCULATURE
2y 5m to grant Granted Mar 24, 2026
Patent 12558065
ULTRASOUND TRANSDUCER
2y 5m to grant Granted Feb 24, 2026
Patent 12376758
BIOLOGICAL INFORMATION MONITORING APPARATUS AND MAGNETIC RESONANCE APPARATUS
2y 5m to grant Granted Aug 05, 2025
Patent 12350097
DEVICES, SYSTEMS, AND METHODS FOR TRANS-VAGINAL, ULTRASOUND-GUIDED HYSTEROSCOPIC SURGICAL PROCEDURES
2y 5m to grant Granted Jul 08, 2025
Patent 12285289
MODULAR ULTRASOUND APPARATUS AND METHODS
2y 5m to grant Granted Apr 29, 2025
Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
30%
Grant Probability
58%
With Interview (+27.6%)
3y 11m
Median Time to Grant
High
PTA Risk
Based on 63 resolved cases by this examiner. Grant probability derived from career allow rate.

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