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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 May 07, 2026 has been entered.
Status of Claims
This office action for the 18/192915 application is in response to the communications filed May 07, 2026.
Claims 1 and 11 were cancelled May 07, 2026.
Claims 1, 3, 4, 8-11, 13 and 14 and 18-20 are currently pending and considered below.
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 1, 3, 4, 8-11, 13, 14 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Lachaine et al. (US 2020/0129780; herein referred to as Lachaine) in view of Nakai et al. (US 2017/0119340; herein referred to as Nakai).
As per claim 1,
Lachaine teaches an apparatus, comprising: a control circuit to facilitate generating an optimized radiation treatment plan during a radiation treatment planning workflow that precedes delivering therapeutic energy to a corresponding patient:
(Paragraph [0026] of Lachaine. The teaching describes an image processing computing system 110 may include processing circuitry 112, memory 114, a storage device 116, and other hardware and software-operable features such as a user interface 140, communication interface, and the like.)
Lachaine teaches access projection data for a given patient, wherein the projection data comprises, at least in part, three-dimensional cone beam CT images:
(Paragraphs [0017], [0020] and [0037] of Lachaine. The teaching describes a patient state generator may receive partial measurements (e.g., a 2D image) as an input and generate (e.g., estimate) a patient state (e.g., a 3D image) as an output. These partial measurements may be from a single modality, such as an x-ray projection or MRI slice, or from multiple modalities, such as positions of reflective surface markers on the patient's surface synchronized with x-ray projections. The image data 160 may include one or more MRI images (e.g., 2D MRI, 3D MRI, 2D streaming MRI, 4D MRI, 4D volumetric MRI, 4D cine MRI, etc.), functional MRI images (e.g., fMRI, DCE-MRI, diffusion MM), Computed Tomography (CT) images (e.g., 2D CT, Cone beam CT, 3D CT, 4D CT), ultrasound images (e.g., 2D ultrasound, 3D ultrasound, 4D ultrasound), Positron Emission Tomography (PET) images, X-ray images, fluoroscopic images, radiotherapy portal images, Single-Photo Emission Computed Tomography (SPECT) images, computer generated synthetic images (e.g., pseudo-CT images) and the like. IGRT may use computed tomography (CT) imaging, cone beam CT (CBCT), magnetic resonance (MR) imaging, positron-emission tomography (PET) imaging, or the like to obtain a 3D or 4D image of a patient prior to irradiation.)
Lachaine further teaches background process the projection data during the radiation treatment planning workflow to generate a plurality of different images:
(Paragraphs [0066]-[0069] and [0077] of Lachaine. The teaching describes that patient model generator 408 may include creation of a low dimensional patient state representation. In an example, prior measurements are first reconstructed into a 4D image. 4D images may include a series of 3D images of a representative respiratory cycle. For example, for a 4D CBCT, a number of x-ray projections are acquired and sorted into a number of bins. Sorting may be done, for example, by detecting a diaphragm position in each projection directly in the images, or using a separate respiratory signal acquired simultaneously with the kV projections, and binning the projection according to the phase or amplitude of the signal. Each bin is then reconstructed separately with the kV projections assigned to that bin to form a 3D image per bin. Similar techniques may be used to generate a 4D MR image. A model may then be constructed using the 4D image as an interim step. In practical radiotherapy applications, partial measurements (e.g., a 2D image or image slice) provide incomplete information about the patient state (e.g., a 3D image). For example, a 2D MRI slice is a single cut through a 3D representation of the patient, and an x-ray projection is an integration through voxels along ray-lines of a 3D representation. Using either image results in impartial information (e.g., a 2D image rather than a 3D representation of patient anatomy). The patient state generator 408 may use the partial information and the patient model 406 generated from past measurements and/or offline (pre-treatment) acquisitions to estimate the patient state 410. The patient state generator 408 uses an instantaneous partial measurement 402 and a preliminary motion model of a patient 406 to estimate a patient state, output at block 410. The preliminary motion model 406 is generated using previous measurements 404, including previous patient states corresponding to the previous measurements 404. The patient state is understood to be generated in real-time, i.e. during an imaging workflow)
Lachaine further teaches wherein the plurality of different images includes at least three of: an image presenting directly reconstructed relative electron density for photon or electron treatment dose calculation and for kV imaging dose calculation; an image presenting directly reconstructed stopping power ratio for proton treatment dose calculation; a post-processed virtual monoenergetic image, with energy selected for optimal visibility of structures to be contoured; a virtual non-contrast image; an effective atomic number image; a phase binned 4D-cone beam computed tomography image tailored to a particular intended use; an amplitude binned 4D-cone beam computed tomography image tailored to a particular intended use; a 5D-cone beam computed tomography image tailored to a particular intended use; an image highlighting at least one patient implant:
(Paragraphs [0020] and [0069] of Lachaine. The teaching describes that 4D images may include a series of 3D images of a representative respiratory cycle. For example, for a 4D CBCT, a number of x-ray projections are acquired and sorted into a number of bins. Sorting may be done, for example, by detecting a diaphragm position in each projection directly in the images, or using a separate respiratory signal acquired simultaneously with the kV projections, and binning the projection according to the phase or amplitude of the signal. Each bin is then reconstructed separately with the kV projections assigned to that bin to form a 3D image per bin. Similar techniques may be used to generate a 4D MR image. A model may then be constructed using the 4D image as an interim step. A patient state may be a 3D image, or of ‘multi-modality,’ for example the patient state may include two or more 3D images that offer different information on the patient state, such as a ‘MR-like’ for enhanced tissue contrast, a ‘CT-like’ for high geometric accuracy and voxels related to density that are useful for dose calculations, or a ‘functional MR-like’ to provide function information about the patient. Patient state may also include non-imaging information.)
Lachaine further teaches store the plurality of different images to provide stored images:
(Paragraph [0032] of Lachaine. The teaching describes a storage device 116 and memory 114 may store and host data to perform these purposes, including the image data 160, patient data, and other data required to create and implement a radiation therapy treatment plan and associated patient state estimation operations)
Lachaine further teaches receive a request that corresponds to at least one item of task-supportive content that corresponds to a particular radiation therapy workflow step; access the stored images to select at least one particular image that corresponds to the particular radiation therapy workflow step and transmit the at least one particular image that corresponds to the particular radiation therapy workflow step, wherein the at least one particular image comprises a consistent representation of the task-supportive content regardless of what image-capture modality was employed to capture the projection data used to generate the at least one particular image:
(Paragraphs [0041] and [0044]-[0046] of Lachaine. The teaching describes image acquisition device 170 can be configured to acquire one or more images of the patient's anatomy for a region of interest (e.g., a target organ, a target tumor or both). Each image, typically a 2D image or slice, can include one or more parameters (e.g., a 2D slice thickness, an orientation, and a location, etc.). The patient state processing logic 120 in the image processing computing system 110 is depicted as implementing a patient state estimation workflow 130 with various aspects of model generation and estimation processing operations. In an example, the patient state estimation workflow 130 operated by the patient state processing logic 120 generates and uses a preliminary motion model 132 generated from patient data (e.g., from a patient being treated, from multiple previous patients, or the like). The patient state processing logic 120 and the patient state estimation workflow 130 may be used when generating the radiation therapy treatment plan, within use of software programs. The output device 142 may include a display device which outputs a representation of the user interface 140 and one or more aspects, visualizations, or representations of the medical images. The output device 142 may include one or more display screens that display medical images, interface information, treatment planning parameters (e.g., contours, dosages, beam angles, labels, maps, etc.) treatment plans, a target, localizing a target or tracking a target, patient state estimations (e.g., a 3D image), or any related information to the user.)
Lachaine does not explicitly teach wherein the plurality of different images includes at least five of: an image presenting directly reconstructed relative electron density for photon or electron treatment dose calculation and for kV imaging dose calculation; an image presenting directly reconstructed stopping power ratio for proton treatment dose calculation; a post-processed virtual monoenergetic image, with energy selected for optimal visibility of structures to be contoured; a virtual non-contrast image; an effective atomic number image; a phase binned 4D-cone beam computed tomography image tailored to a particular intended use; an amplitude binned 4D-cone beam computed tomography image tailored to a particular intended use; a 5D-cone beam computed tomography image tailored to a particular intended use; an image highlighting at least one patient implant.
However, Nakai teaches an apparatus that generates an image presenting directly reconstructed relative electron density for photon or electron treatment dose calculation and for kV imaging dose calculation and an effective atomic number image:
(Paragraph [0072] of Nakai. The teaching describes that the processing circuitry 6 reconstructs the photon-counting projection data applied with the pre-process, and generates a substance decomposing image, as illustrated in FIG. 2 (Step S8). The processing circuitry 36 reads a computer program corresponding to the image generating function 363 from the memory circuitry 35 and executes the computer program in the same manner as at Step S4. The image generating function 63 includes a function for reconstructing the photon-counting projection data stored in the projection data memory circuitry 33, and generating a substance decomposing image. The reconstruction method is as described at Step S4. The substance decomposing image generated by the image generating function 363 is stored in the image memory circuitry 34. The image generating function 363 may generate at least one of the substance decomposing image, the electron density image, the effective atomic number image, and the monochromatic X-ray image.)
It would have been obvious to one of ordinary skill in the art before the time of filing to add to the medical image generation techniques of Lachaine, the medical image generation techniques of Nakai. Paragraph [0082] of Nakai teaches the process of generating the image presenting directly reconstructed relative electron density for photon or electron treatment dose calculation and for kV imaging dose calculation and an effective atomic number image is associated with a reliability measurement for each of the pictures generated. One of ordinary skill in the art in possession of Lachaine would have looked to Nakai to achieve these advantageous medical image generation techniques. One of ordinary skill in the art would have added to the teaching of Lachaine, the teaching of Nakai based on this incentive without yielding unexpected results.
As per claim 3,
The combined teaching of Lachaine and Nakai teaches the limitations of claim 2.
Lachaine further teaches wherein the projection data consists entirely of three-dimensional cone beam computed tomography images:
(Paragraph [0017] of Lachaine. The teaching describes that the Image guided radiation therapy may use computed tomography (CT) imaging, cone beam CT (CBCT), magnetic resonance (MR) imaging, positron-emission tomography (PET) imaging, or the like to obtain a 3D or 4D image of a patient prior to irradiation. Because this list describes embodiments of the invention, the reference anticipates projection data that is based solely on cone beam CT images)
As per claim 4,
The combined teaching of Lachaine and Nakai teaches the limitations of claim 1.
Lachaine further teaches wherein the control circuit is configured to background process the projection data during a radiation therapy workflow process:
(Paragraph [0068] and [0069] of Lachaine. The teaching describes that patient model generator 408 may include creation of a low dimensional patient state representation. In an example, prior measurements are first reconstructed into a 4D image. 4D images may include a series of 3D images of a representative respiratory cycle. For example, for a 4D CBCT, a number of x-ray projections are acquired and sorted into a number of bins. Sorting may be done, for example, by detecting a diaphragm position in each projection directly in the images, or using a separate respiratory signal acquired simultaneously with the kV projections, and binning the projection according to the phase or amplitude of the signal. Each bin is then reconstructed separately with the kV projections assigned to that bin to form a 3D image per bin. Similar techniques may be used to generate a 4D MR image. A model may then be constructed using the 4D image as an interim step.)
(Paragraphs [0041] and [0044]-[0046] of Lachaine. The teaching describes image acquisition device 170 can be configured to acquire one or more images of the patient's anatomy for a region of interest (e.g., a target organ, a target tumor or both). Each image, typically a 2D image or slice, can include one or more parameters (e.g., a 2D slice thickness, an orientation, and a location, etc.). The patient state processing logic 120 in the image processing computing system 110 is depicted as implementing a patient state estimation workflow 130 with various aspects of model generation and estimation processing operations. In an example, the patient state estimation workflow 130 operated by the patient state processing logic 120 generates and uses a preliminary motion model 132 generated from patient data (e.g., from a patient being treated, from multiple previous patients, or the like). The patient state processing logic 120 and the patient state estimation workflow 130 may be used when generating the radiation therapy treatment plan, within use of software programs. The output device 142 may include a display device which outputs a representation of the user interface 140 and one or more aspects, visualizations, or representations of the medical images. The output device 142 may include one or more display screens that display medical images, interface information, treatment planning parameters (e.g., contours, dosages, beam angles, labels, maps, etc.) treatment plans, a target, localizing a target or tracking a target, patient state estimations (e.g., a 3D image), or any related information to the user.)
As per claim 8,
The combined teaching of Lachaine and Nakai teaches the limitations of claim 1.
Lachaine further teaches wherein the control circuit is further configured to: select a particular imaging protocol for a cone beam computed tomography imaging system from amongst a plurality of available imaging protocols, such that the projection data is captured as a function of the particular imaging protocol:
(Paragraph [0037] of Lachaine. The teaching describes that the image data 160 may include one or more Computed Tomography (CT) [cone beam computed tomography imaging system] images (e.g., 2D CT, Cone beam CT, 3D CT, 4D CT [plurality of available imaging protocols]))
As per claim 9,
The combined teaching of Lachaine and Nakai teaches the limitations of claim 1.
Lachaine further teaches wherein the control circuit is configured to background process the projection data to generate the plurality of different images by, at least in part, selecting a plurality of reconstruction methods from amongst a plurality of available reconstruction methods:
(Paragraph [0068] and [0069] of Lachaine. The teaching describes that patient model generator 408 may include creation of a low dimensional patient state representation. In an example, prior measurements are first reconstructed into a 4D image. 4D images may include a series of 3D images of a representative respiratory cycle. For example, for a 4D CBCT, a number of x-ray projections are acquired and sorted into a number of bins. Sorting may be done, for example, by detecting a diaphragm position in each projection directly in the images, or using a separate respiratory signal acquired simultaneously with the kV projections, and binning the projection according to the phase or amplitude of the signal. Each bin is then reconstructed separately with the kV projections assigned to that bin to form a 3D image per bin. Similar techniques may be used to generate a 4D MR image. A model may then be constructed using the 4D image as an interim step.)
(Paragraph [0082] of Lachaine. The teaching describes a PCA-to-DVF reconstruction is performed. A full DVF may be reconstructed using the randomly generated PCA coefficients (e.g., 2-3 coefficients representing degrees of freedom of the moving patient). The DVF is converted to a raw patient state volume by warping the reference volume using the full DVF. A partial measurement is created from the raw patient state volume. For a CT-based motion model, a 2D digitally reconstructed radiograph is computed from the raw patient state volume using, for example, a Siddon-Jacobs algorithm.)
These reconstruction methods constitutes a plurality of reconstruction methods.
As per claim 10,
The combined teaching of Lachaine and Nakai teaches the limitations of claim 1.
Lachaine further teaches wherein the control circuit is further configured to: post-process the at least one particular image that corresponds to the particular radiation therapy workflow step to generate at least one post-processed particular image; and wherein the control circuit is configured to transmit the at least one particular image that corresponds to the particular radiation therapy workflow step by transmitting the at least one post-processed particular image that corresponds to the particular radiation therapy workflow step:
(Paragraph [0068] and [0069] of Lachaine. The teaching describes that patient model generator 408 may include creation of a low dimensional patient state representation. In an example, prior measurements are first reconstructed into a 4D image. 4D images may include a series of 3D images of a representative respiratory cycle. For example, for a 4D CBCT, a number of x-ray projections are acquired and sorted into a number of bins. Sorting may be done, for example, by detecting a diaphragm position in each projection directly in the images, or using a separate respiratory signal acquired simultaneously with the kV projections, and binning the projection according to the phase or amplitude of the signal. Each bin is then reconstructed separately with the kV projections assigned to that bin to form a 3D image per bin. Similar techniques may be used to generate a 4D MR image. A model may then be constructed using the 4D image as an interim step.)
(Paragraphs [0041] and [0044]-[0046] of Lachaine. The teaching describes image acquisition device 170 can be configured to acquire one or more images of the patient's anatomy for a region of interest (e.g., a target organ, a target tumor or both). Each image, typically a 2D image or slice, can include one or more parameters (e.g., a 2D slice thickness, an orientation, and a location, etc.). The patient state processing logic 120 in the image processing computing system 110 is depicted as implementing a patient state estimation workflow 130 with various aspects of model generation and estimation processing operations. In an example, the patient state estimation workflow 130 operated by the patient state processing logic 120 generates and uses a preliminary motion model 132 generated from patient data (e.g., from a patient being treated, from multiple previous patients, or the like). The patient state processing logic 120 and the patient state estimation workflow 130 may be used when generating the radiation therapy treatment plan, within use of software programs. The output device 142 may include a display device which outputs a representation of the user interface 140 and one or more aspects, visualizations, or representations of the medical images. The output device 142 may include one or more display screens that display medical images, interface information, treatment planning parameters (e.g., contours, dosages, beam angles, labels, maps, etc.) treatment plans, a target, localizing a target or tracking a target, patient state estimations (e.g., a 3D image), or any related information to the user.)
As per claim 11,
Claim 11 is substantially similar to claim 1. Accordingly, claim 11 is rejected for the same reasons as claim 1.
As per claim 13,
Claim 13 is substantially similar to claim 3. Accordingly, claim 13 is rejected for the same reasons as claim 3.
As per claim 14,
Claim 14 is substantially similar to claim 4. Accordingly, claim 14 is rejected for the same reasons as claim 4.
As per claim 18,
Claim 18 is substantially similar to claim 8. Accordingly, claim 18 is rejected for the same reasons as claim 8.
As per claim 19,
Claim 19 is substantially similar to claim 9. Accordingly, claim 19 is rejected for the same reasons as claim 9.
As per claim 20,
Claim 20 is substantially similar to claim 10. Accordingly, claim 20 is rejected for the same reasons as claim 10.
Response to Arguments
Applicant's arguments filed December 04, 2025 have been fully considered.
Applicant’s arguments pertaining rejections made under 35 U.S.C. 103 are not persuasive.
The Applicant argues that the cited prior art does not disclose or reasonably teach “precedes delivering therapeutic energy to a corresponding patient”, citing previous arguments made.
The Examiner respectfully disagrees. The issue that the amended claims present hinge on how the term “therapeutic energy” is understood. The as-filed specification refers to this term as:
“By one approach the control circuit 101 can operably couple to an energy-based treatment platform 114 that is configured to deliver therapeutic energy 112 to a corresponding patient 104 having at least one treatment volume 105 and also one or more organs-at-risk (represented in FIG. 1 by a first through an Nth organ-at-risk 108 and 109) in accordance with the optimized energy-based treatment plan 113.” (Paragraph [0023] of the as-filed specification)
“Generally speaking, this process 200 serves to facilitate generating an optimized radiation treatment plan 113 to thereby facilitate treating a particular patient with therapeutic radiation using a particular radiation treatment platform per that optimized radiation treatment plan.” (Paragraph [0028] of the as-filed specification)
These citations do not in any way refer to a specific temporal order of events with regard to this “therapeutic energy”. Furthermore, the as-filed specification also states:
“the control circuit 101 generates the plurality of different images by, at least in part, selecting a plurality of reconstruction methods from amongst a plurality of available reconstruction methods. Reconstruction refers to the process of generating a two-dimensional or a three-dimensional image of an object from a set of X-ray projection images that are taken from different angles.” (Paragraph [0033] of the as-filed specification.)
This establishes that the imaging data is generated by radiative means, i.e., the patient was radiated with X-rays for an X-ray image to form. However, this imaging step as claimed requires that no “therapeutic energy” be administered to the patient prior to the claimed steps. This necessitates the understanding that “therapeutic energy” must refer to radiation being applied to a patient excluding imaging radiation. Any other interpretation would debase the entire premise of the invention because CT images require X-ray radiation. If the patient cannot be irradiated prior to the claimed steps, the apparatus necessarily cannot access the claimed projection data. Accordingly, there must be a distinction between “imaging radiation” and “therapeutic energy” as words and function. The cited prior art refers to imaging radiation that is being applied to the patient to generate the medical images. This amended feature of therapeutic energy does not change the prior art’s applicability. If it is the position of the Applicant that absolutely no radiation can be administered to the patient, imaging or otherwise, prior to the claimed steps, the as-filed specification has no written description for such a feature and in fact contradicts that argument by at least paragraph [0033] of the as-filed specification.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHAD A NEWTON whose telephone number is (313)446-6604. The examiner can normally be reached M-F 8:00AM-4:00PM (EST).
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/CHAD A NEWTON/Primary Examiner, Art Unit 3681
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