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 .
Information Disclosure Statement
The listing of references in the specification is not a proper information disclosure statement. 37 CFR 1.98(b) requires a list of all patents, publications, or other information submitted for consideration by the Office, and MPEP § 609.04(a) states, "the list may not be incorporated into the specification but must be submitted in a separate paper." Therefore, unless the references have been cited by the examiner on form PTO-892, they have not been considered.
Claim Objections
Claims 1, 17, and 18 are objected to because of the following informalities:
Claim 1, lines 46-47 recites “finding asymmetry index.” This should read “finding the asymmetry index.”
Claim 1, lines 47-48 recites “thresholding and clustering to obtain processed image.” This should read “thresholding and clustering to obtain a processed image.”
Claim 1, line 50 recites “storage (C3) that has large capacity.” This should read “storage (C3) that has a large capacity.”
Claim 1, line 53 recites “equipped with fast processor (C6).” This should read “equipped with a fast processor (C6).”
Claim 1, line 55 recites “independent of healthy control PET data.” This should read “independent of
Claim 17, line 39 recites “images.”. This should read “images
Claim 18, line 10 recites “using PET detector (A11).” This should read “using the PET detector (A11).”
Claim 18, line 11 recites “scanning simultaneously using PET and MRI detectors.” This should read “using the PET and MRI detectors.”
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are:
“acquisition module” in claim 1, line 3;
“acquisition submodule” in claim 1, line 5;
“injection unit” in claim 1, line 9;
“tool” in claim 1, line 12;
“storage and communication module” in claim 1, line 15;
“computation module” in claim 1, line 19;
“computing submodule” in claim 1, line 24;
“processing submodule” in claim 1, line 25;
“storage device” in claim 1, line 26;
“language and interactive tool” in claim 1, line 27;
“toolbox” in claim 1, line 30;
“tools for analyzing and processing” in claim 1, line 14;
“tools for segmentation, co-registration, registration, smoothing, quantitative analysis etc.” in claim 1, lines 40-41;
“image reconstruction submodule” in claim 7, line 2;
“MRI sequences tool” in claim 7, lines 4-5; and
“high end processing computing submodule” in claim 13, line 2.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 1, the phrase "such as" renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “such as but not limited to Fluorodeoxyglucose (FDG)” in claim 1, lines 10-11 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “to include tools for segmentation, co-registration, registration, smoothing, quantitative analysis etc.” in claim 1, lines 40-41 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “by steps such as but not limited to flipping, image segmentation, forward warping, inverse warping, finding asymmetry index, multiplying greyscale map, thresholding and clustering” in claim 1, lines 45-47 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The term “large capacity” in claim 1, lines 50-51 is a relative term which renders the claim indefinite. The term “large capacity” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
The term “high data volumes” in claim 1, line 51 is a relative term which renders the claim indefinite. The term “high data volumes” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
The term “fast processor (C6)” in claim 1, line 53 is a relative term which renders the claim indefinite. The term “fast processor (C6)” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
The term “accurate” in claim 1, line 55 is a relative term which renders the claim indefinite. The term “accurate” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
The term “efficient” in claim 1, line 55 is a relative term which renders the claim indefinite. The term “efficient” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
The term “at affordable cost” in claim 1, lines 56-57 is a relative term which renders the claim indefinite. The term “at affordable cost” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
The phrase “such as syngo MR E11 Platform” in claim 2, lines 2-3 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “such as but not limited to PET scanner with Lutetium Oxyorthosilicate (LSO) crystals with effective detection of gamma rays and quick decay times” in claim 3, lines 2-4 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “such as but not limited to 30Tesla MRI (3T MRI)” in claim 5, lines 2-3 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “such as 3D FLAIR that is set with specific repetition time (TR), echo time (TE), inversion time (TI), matrix, and number of excitations” in claim 6, lines 2-3 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “such as… 3D MPRAGE that is a T1-weighted sequence providing high-resolution, isotropic 3D imaging of brain structures” in claim 6, lines 3-5 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “such as 3D FLAIR and 3D T1-weighted MPRAGE, including timing (TR, TE, TI), field of view (FOV), matrix size, and number of excitation (NEX)” in claim 8, lines 2-4 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “preferably 5” in claim 9, line 2 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “preferably 21 subsets” in claim 9, line 3 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The term “high data volumes” in claim 11, line 2 is a relative term which renders the claim indefinite. The term “high data volumes” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
The term “high end processing computing submodule (C1)” in claim 13, line 2 is a relative term which renders the claim indefinite. The term “high end processing computing submodule (C1)” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
The term “fast processor (C6)” in claim 13, line 3 is a relative term which renders the claim indefinite. The term “fast processor (C6)” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
The phrase “such as Core i7 processor” in claim 13, line 3 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “such as but not limited to DARTEL” in claim 15, line 2 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “such as 8-mm full width at half maximum (FWHM) Gaussian kernel” in claim 16, line 2 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “such as syngo MR platform” in claim 17, line 7 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “such as DARTEL import files through toolbox (C5)” in claim 17, line 34 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “such as SPM12 for high level language and interactive tool (C4)” in claim 17, lines 34-35 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “such as DARTEL import files through nonlinear co-registration of the grey and white matter of flipped (IFM1, ITM1) and un flipped MRI (IFM, ITM) images” in claim 17, lines 37-39 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “such as an 8-mm full width at half maximum (FWHM) Gaussian kernel to improve the signal-to-noise ratio” in claim 17, lines 54-55 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “such as by retaining the cluster of at least 100 voxels connected to the voxel with the peak AI value” in claim 17, lines 69-70 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “such as FDG for PET scanning” in claim 18, lines 5-6 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “such as for MRI 3D FLAIR MRI, T1-weighted MRI (ITM) and settings tailored for brain imaging to obtain PET and MRI data” in claim 18, lines 12-14 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
The phrase “such as standard DICOM (Digital Imaging and Communications in Medicine) protocols” in claim 20, lines 3-4 renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
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 1-9, 11, and 15-16 are rejected under 35 U.S.C. 102(a)(1) as anticipated by or, in the alternative, under 35 U.S.C. 103 as obvious over Poirier et al. (“18F-FDG PET-guided diffusion tractography reveals white matter abnormalities around the epileptic focus in medically refractory epilepsy: implications for epilepsy surgical evaluation” 2020”), hereinafter “Poirier,” as evidenced by Siemens (“Biograph mMR” 2011), hereinafter "Siemens.”
Regarding claim 1, Poirier discloses a system (S) for automatic detection of epileptogenic focus (EF) (processing using computer software on a computer processor to automatically detect epileptic focus, Abstract, P.4, ¶2 – P.5, ¶1, P.5, ¶3 – P.6, ¶1) in subjects (Su) with pharmacoresistant epilepsy (medically refractory epilepsy patients failing treatment with antiepileptic drugs, Abstract, P.4, ¶1) the said system (S) comprising of
at least one acquisition module (A01, A02,…An) (3T hybrid PET/MRI scanner system, Biograph mMR, Abstract, P.4, ¶2 – P.5, ¶1), said acquisition module (A) comprising of
at least one acquisition submodule (A101, A102,…A1n) that is a medical hardware system (A1) comprising of PET detector (A11) and MRI scanner (A12) (3T hybrid PET/MRI scanner, Biograph mMR, Abstract, P.4, ¶2 – P.5, ¶1) for acquiring and pre-processing of inputs that are in the form of PET data (IP) and MRI data (IM) of said subjects (Su) (acquiring and pre-processing of PET and MRI data of patients, Abstract, P.4, ¶2 – P.5, ¶1)
at least one injection unit (A201, A202,...A2n) for intravenous administration of radiotracer such as but not limited to Fluorodeoxyglucose (FDG) for PET scanning (injection of fluorodeoxyglucose for PET scanning, Abstract, P.4, ¶2 – P.5, ¶1) and
at least one tool (A301, A302,….A3n) that controls the operation of said MRI scanner (A12) to include the initiation of sequences, data acquisition parameters and integration with said PET detector (A11) (workstation of 3T hybrid PET/MRI scanner system, Biograph mMR, controls the operation of the MRI scanner to include the initiation of sequences, data acquisition parameters and integration with the PET detector, Abstract, P.4, ¶2 – P.5, ¶1)
at least one storage and communication module (SC01, SC02,…SCn) said storage and communication module (SC) is a medical imaging technology used for storing, retrieving, presenting, and sharing or communicating said preprocessed PET (IPP) and MRI data (IMP) from acquisition module (A) (workstation of 3T hybrid PET/MRI scanner system, Biograph mMR, stores, retrieves, presents, and shares/communicates the preprocessed PET and MRI data acquired by the 3T hybrid PET/MRI scanner system, Biograph mMR, Abstract, P.4, ¶2 – P.5, ¶1; as evidenced by Siemens, P.18-19 wherein the Biography mMR system incorporates a workstation for storage and communication of PET and MRI data) and
at least one computation module (C01, C02,..Cn) for accessing said preprocessed PET (IPP) and MRI data (IMP) from storage and communication module (SC) and performing advance processing of said preprocessed PET (IPP) and MRI data (IMP) to localize epileptogenic focus (EF) (processing using computer software on a computer processor with memory to automatically detect epileptic focus from preprocessed PET and MRI data stored by the workstation of the 3T hybrid PET/MRI scanner system, Biograph mMR, including FSL, ANTS, SPM12, MATLAB, MRtrix3, and clinical imaging software for visualization, SygnoVia, Abstract, P.4, ¶2 – P.5, ¶1, P.5, ¶2, P.5, ¶3 – P.6, ¶1, P.6, ¶2; see also software integration, P.16, ¶3; as evidenced by Siemens, P.18-19 wherein the Biography mMR system incorporates a workstation for storage and communication of preprocessed PET and MR data for access by a processor implementing computer software for processing the preprocessed PET and MR data), said computation module (C) comprising of
at least one computing submodule (C101, C102,…C1n) (processing using computer software on a computer processor with memory to automatically detect epileptic focus from preprocessed PET and MRI data stored by the workstation of the 3T hybrid PET/MRI scanner system, Biograph mMR, including FSL, ANTS, SPM12, MATLAB, MRtrix3, and clinical imaging software for visualization, SygnoVia, Abstract, P.4, ¶2 – P.5, ¶1, P.5, ¶2, P.5, ¶3 – P.6, ¶1, P.6, ¶2; see also software integration, P.16, ¶3),
at least one processing submodule(C201, C202,…C2n) (processing using computer software on a computer processor with memory to automatically detect epileptic focus from preprocessed PET and MRI data stored by the workstation of the 3T hybrid PET/MRI scanner system, Biograph mMR, including FSL, ANTS, SPM12, MATLAB, MRtrix3, clinical imaging software for visualization, SygnoVia, and computer-assisted diagnosis software, Abstract, P.4, ¶2 – P.5, ¶1, P.5, ¶2, P.5, ¶3 – P.6, ¶1, P.6, ¶2, Fig. 2; see also software integration, P.16, ¶3),
at least one storage device (C301, C302,…C3n) (processing using computer software on a computer processor with memory to automatically detect epileptic focus from preprocessed PET and MRI data stored by the workstation of the 3T hybrid PET/MRI scanner system, Biograph mMR, including FSL, ANTS, SPM12, MATLAB, MRtrix3, clinical imaging software for visualization, SygnoVia, and computer-assisted diagnosis software, Abstract, P.4, ¶2 – P.5, ¶1, P.5, ¶2, P.5, ¶3 – P.6, ¶1, P.6, ¶2, Fig. 2; see also software integration, P.16, ¶3; as evidenced by Siemens, P.18-19 wherein the Biography mMR system incorporates a workstation for storage and communication of preprocessed PET and MR data for access by a processor containing memory/storage implementing computer software for processing the preprocessed PET and MR data),
at least one language and interactive tool (C401, C402,…C4n) that is a high-level language and interactive environment to run said processing submodule (C2) (processing using computer software on a computer processor with memory to automatically detect epileptic focus from preprocessed PET and MRI data stored by the workstation of the 3T hybrid PET/MRI scanner system, Biograph mMR, including FSL, ANTS, SPM12, MATLAB, MRtrix3, clinical imaging software for visualization, SygnoVia, and computer-assisted diagnosis software, Abstract, P.4, ¶2 – P.5, ¶1, P.5, ¶2, P.5, ¶3 – P.6, ¶1, P.6, ¶2, Fig. 2; see also software integration, P.16, ¶3) and
at least one toolbox (C501, C502,…C5n) that is based on said language and interactive tool (C4) required for Image Processing (Ip) by said processing submodule (C2) (processing using computer software on a computer processor with memory to automatically detect epileptic focus from preprocessed PET and MRI data stored by the workstation of the 3T hybrid PET/MRI scanner system, Biograph mMR, including FSL, ANTS, SPM12, MATLAB, MRtrix3, clinical imaging software for visualization, SygnoVia, and computer-assisted diagnosis software, Abstract, P.4, ¶2 – P.5, ¶1, P.5, ¶2, P.5, ¶3 – P.6, ¶1, P.6, ¶2, Fig. 2; see also software integration, P.16, ¶3),
wherein
said processing submodule (C2) of said computation module (C) applies a technique of PET asymmetry after anatomical symmetrization coregistered to MRI (PASCOM) for analyzing and processing preprocessed PET (IPP)and MRI data (IMP) from storage and communication module (SC) (processing using computer software on a computer processor with memory determines the PET asymmetry after anatomical symmetrization coregistered to the MRI data for analyzing and processing preprocessed PET and MRI data from the 3T hybrid PET/MRI system, Biograph mMR, workstation storage, Abstract, P.5, ¶3 – P.6, ¶1),
said processing submodule (C2) of said computation module (C) is configured with tools for analyzing and processing said preprocessed PET (IPP) and MRI data, to include tools for segmentation, co-registration, registration, smoothing, quantitative analysis etc. (processing using computer software on a computer processor with memory includes tools for analyzing and processing said preprocessed PET and MRI data including tools for segmentation, co-registration, registration, smoothing, and quantitative analysis, Abstract, P.5, ¶3 – P.6, ¶1),
said processing submodule (C2) of said computation module (C) performs analysis and processing of said preprocessed PET (IPP) and MRI data (IMP) using said technique of PET asymmetry after anatomical symmetrization coregistered to MRI (PASCOM) by steps such as but not limited to flipping, image segmentation, forward warping, inverse warping, finding asymmetry index, multiplying greyscale map, thresholding and clustering to obtain processed image that depicts the hypometabolic cerebral cortex for detection of Epileptogenic focus (EF) (processing using computer software on a computer processor with memory performs analysis and processing of the preprocessed PET and MRI data using the PET asymmetry after anatomical symmetrization coregistered to the MRI data by steps such as flipping, image segmentation, forward warping, inverse warping, finding asymmetry index, multiplying greyscale map, thresholding and clustering to obtain processed image that depicts the hypometabolic cerebral cortex for detection of epileptic focus, Abstract, P.5, ¶3 – P.6, ¶1),
said computation module (C) is configured with storage (C3) that has large capacity to handle the high data volumes generated by PET and MRI data of high-resolution (processing using computer software on a computer processor with memory to automatically detect epileptic focus from preprocessed high-resolution PET and MRI data stored by the workstation of the 3T hybrid PET/MRI scanner system, Biograph mMR, including FSL, ANTS, SPM12, MATLAB, MRtrix3, clinical imaging software for visualization, SygnoVia, and computer-assisted diagnosis software, Abstract, P.4, ¶2 – P.5, ¶1, P.5, ¶2, P.5, ¶3 – P.6, ¶1, P.6, ¶2, Fig. 2; see also software integration, P.16, ¶3; as evidenced by Siemens, P.18-19 wherein the Biography mMR system incorporates a workstation for storage and communication of preprocessed PET and MR data for access by a processor containing memory/storage implementing computer software for processing the preprocessed PET and MR data) and
said computation module (C) is equipped with fast processor (C6) thereby enabling said system (S) to automatically detect epileptogenic focus (EF) in subjects (Su) (processing using computer software on a computer processor with memory to automatically detect epileptic focus from preprocessed PET and MRI data stored by the workstation of the 3T hybrid PET/MRI scanner system, Biograph mMR, including FSL, ANTS, SPM12, MATLAB, MRtrix3, and clinical imaging software for visualization, SygnoVia, Abstract, P.4, ¶2 – P.5, ¶1, P.5, ¶2, P.5, ¶3 – P.6, ¶1, P.6, ¶2; see also software integration, P.16, ¶3; as evidenced by Siemens, P.18-19 wherein the Biography mMR system incorporates a workstation for storage and communication of preprocessed PET and MR data for access by a processor containing memory/storage implementing computer software for processing the preprocessed PET and MR data), using accurate and efficient technique that is independent of healthy control PET data (epileptic focus is automatically detected from patient PET/MRI without healthy control PET data, Abstract, P.3, ¶ 2, P.4, ¶2 – P.5, ¶1, P.5, ¶2, P.5, ¶3 – P.6, ¶1, P.6, ¶2), facilitating implementation and multicenter translation at affordable cost thereby assisting healthcare professionals in presurgical evaluation (processing using computer software on a computer processor with memory to automatically detect epileptic focus from preprocessed PET and MRI data stored by the workstation of the 3T hybrid PET/MRI scanner system, Biograph mMR, is useful for clinical decision-making and presurgical planning, Abstract, P.3, ¶2-3, P.6, ¶1; see also P.11, ¶3 – P.12, ¶2, P.13, ¶ 2, P.16, ¶2-3; note that the limitation “facilitating implementation and multicenter translation at affordable cost thereby assisting healthcare professionals in presurgical evaluation” is merely a purpose and/or intended use for the claimed computation module and therefore does not have patentable weight as it does not result in a structural difference from the processing using computer software on a computer processor with memory, MPEP 2111.02 II.).
Regarding claim 2, Poirier discloses said medical hardware system (A1) is an integrated PET-MRI system with system platform such as syngo MR E11 Platform (3T hybrid PET/MRI scanner system, Biograph mMR, Abstract, P.4, ¶2 – P.5, ¶1).
Regarding claim 3, Poirier discloses said PET detector (A11) is a high-definition PET scanner with capacity for high-resolution imaging such as but not limited to PET scanner with Lutetium Oxyorthosilicate (LSO) crystals with effective detection of gamma rays and quick decay times (3T hybrid PET/MRI scanner system, Biograph mMR, acquires high-resolution PET images, Abstract, P.4, ¶2 – P.5, ¶1).
Regarding claim 4, Poirier discloses said PET data (IP) from PET detector (A11) is a high resolution FDG PET acquired interictally (3T hybrid PET/MRI scanner system, Biograph mMR, acquires high-resolution PET images of medically refractory epilepsy patients failing treatment with antiepileptic drugs while the patients were not actively seizing, i.e., interictally, Abstract, P.4, ¶1 – P.5, ¶1).
Regarding claim 5, Poirier discloses said MRI scanner (A12) is capable of providing high-resolution magnetic resonance imaging such as but not limited to 3-Tesla MRI (3T MRI) (3T hybrid PET/MRI scanner system, Biograph mMR, acquires high-resolution MRI images, Abstract, P.4, ¶2 – P.5, ¶1).
Regarding claim 6, Poirier discloses said MRI scanner (A12) is set for imaging protocols such as 3D FLAIR that is set with specific repetition time (TR), echo time (TE), inversion time (TI), matrix, and number of excitations and 3D MPRAGE that is a T1-weighted sequence providing high-resolution, isotropic 3D imaging of brain structures (3T hybrid PET/MRI scanner system, Biograph mMR, is set for imaging protocols such as 3D FLAIR that is set with specific repetition time (TR), echo time (TE), inversion time (TI), matrix, and number of excitations and 3D MPRAGE that is a T1-weighted sequence providing high-resolution, isotropic 3D imaging of brain structures, Abstract, P.4, ¶2 – P.5, ¶1).
Regarding claim 7, Poirier discloses said PET detector (A11) comprises of one image reconstruction submodule (A111) for iterative reconstruction of PET data (IP) from said PET detector(A11) enhancing image quality and providing pre-processed PET data (IPP) (3T hybrid PET/MRI scanner workstation, Biograph mMR, performs a list-mode PET imaging session and pre-processes and reconstructs the acquired data into one image volume using 3 iterations, Abstract, P.4, ¶2 – P.5, ¶1) and said MRI scanner (A12) comprises of one MRI sequences tool (A121) for controlling parameters for MRI sequences from said MRI scanner (A12) (workstation of 3T hybrid PET/MRI scanner system, Biograph mMR, controls the operation of the MRI scanner for controlling parameters for MRI sequences, Abstract, P.4, ¶2 – P.5, ¶1).
Regarding claim 8, Poirier discloses said MRI sequences tool (A121) of MRI scanner (A12) controls parameters for MRI sequences such as 3D FLAIR and 3D T1-weighted MPRAGE, including timing (TR, TE, TI), field of view (FOV), matrix size, and number of excitations (NEX) (workstation of 3T hybrid PET/MRI scanner system, Biograph mMR, controls the operation of the MRI scanner for controlling parameters for MRI sequences such as 3D FLAIR and 3D T1-weighted MPRAGE, including timing (TR, TE, TI), field of view (FOV), matrix size, and number of excitations (NEX), Abstract, P.4, ¶2 – P.5, ¶1).
Regarding claim 9, Poirier discloses said reconstruction of PET data is done in iterations in the range of 3-8 iterations preferably 5 and a plurality of subsets in the range of 15-30 preferably 21 subsets (PET data is reconstructed into one image volume using 3 iterations and 21 subsets, P.4, ¶2 - P.5, ¶1).
Regarding claim 11, Poirier discloses said storage and communication module (SC) has large-capacity storage (SC1) to handle high data volumes generated by high-resolution PET (IP) and MRI scans (IM) (workstation of 3T hybrid PET/MRI scanner system, Biograph mMR, stores, retrieves, presents, and shares/communicates the preprocessed high-resolution PET and MRI data acquired by the 3T hybrid PET/MRI scanner system, Biograph mMR, Abstract, P.4, ¶2 – P.5, ¶1; as evidenced by Siemens, P.18-19 wherein the Biography mMR system incorporates a workstation for storage and communication of preprocessed PET and MR data for access by a processor containing memory/storage implementing computer software for processing the preprocessed PET and MR data).
Regarding claim 15, Poirier discloses said tools for registration are computing tools for image registration (C7) such as but not limited to DARTEL (registration is performed using software computing tools for image registration including FSL, ANTS, SPM12, and clinical imaging software, SygnoVia, P.5, ¶3 – P.6, ¶2).
Regarding claim 16, Poirier discloses said smoothing tool (C8) is Gaussian kernel such as 8-mm full width at half maximum (FWHM) Gaussian kernel (smoothing is performed using a 2-mm full width at half maximum (FWHM) Gaussian kernel, P.4, ¶2 – P.5, ¶1, P.5, ¶3 – P.6, ¶1).
Claims 10 and 12 are rejected as being anticipated, or, in the alternative, obvious over Poirier as evidenced by Siemens as detailed in claim 1 above, and further in view of Siemens.
Regarding claim 10, Poirier discloses said pre-processed PET (IPP) and MRI data (IMP) and other associated data from medical hardware system (A1) is transferred to said storage and communication module (using the 3T hybrid PET/MR scanner system, Biograph mMR, to acquire and transfer pre-processed PET and MRI data for reception by the computer software on a computer processor with memory to automatically perform processing to detect epileptic focus from the preprocessed PET and MRI data stored by the workstation of the 3T hybrid PET/MRI scanner system, Biograph mMR, including FSL, ANTS, SPM12, MATLAB, MRtrix3, and clinical imaging software for visualization, SygnoVia, located at the Lawson Health Research Institute (Abstract, P.4, ¶2 – P.5, ¶1, P.5, ¶2, P.5, ¶3 – P.6, ¶1, P.6, ¶2; see also software integration, P.16, ¶3).
However, Poirier does not appear to explictly disclose transfer to said storage and communication module (SC) via a secure hospital network using protocols.
However, in the same field of endeavor of PET imaging, Siemens teaches PET (IPP) and MRI data (IMP) and other associated data from medical hardware system (A1) is transferred to said storage and communication module (SC) via a secure hospital network using protocols (3T hybrid PET/MR scanner system, Biograph mMR, transfers data to storage and communication module using the system workstation via a hospital clinical network that is secured using protocols such as standard Digital Imaging and Communication in Medicine (DICOM) protocols, Siemens, P.18-19).
It would have been obvious to one having ordinary skill in the art before the effective filing date to have applied Siemens’ known technique of acquiring and transferring data for storage and communication from the hybrid PET/MR scanner system via a hospital clinical network that is secured using protocols such as standard Digital Imaging and Communication in Medicine (DICOM) protocols to Poirier’s known process of acquiring and transferring data for storage and communication from the hybrid PET/MR scanner system to achieve the predictable result that this allows for easy viewing, sharing, and management of acquired PET and MR image data. See, e.g., Siemens, P.18-19.
Regarding claim 12, Poirier discloses said storage and communication module (SC) allows storage and accessibility of said PET (IPP) and MRI data (IMP) to computation module (C) for further processing (workstation of 3T hybrid PET/MRI scanner system, Biograph mMR, stores, retrieves, presents, and shares/communicates the preprocessed high-resolution PET and MRI data acquired by the 3T hybrid PET/MRI scanner system, Biograph mMR, for access by the processing using computer software on a computer processor with memory to automatically detect epileptic focus from preprocessed PET and MRI data stored by the workstation of the 3T hybrid PET/MRI scanner system, Biograph mMR, including FSL, ANTS, SPM12, MATLAB, MRtrix3, clinical imaging software for visualization, SygnoVia, and computer-assisted diagnosis software, Abstract, P.4, ¶2 – P.5, ¶1, P.5, ¶2, P.5, ¶3 – P.6, ¶1, P.6, ¶2, Fig. 2; see also software integration, P.16, ¶3; as evidenced by Siemens, P.18-19 wherein the Biography mMR system incorporates a workstation for storage and communication of preprocessed PET and MR data for access by a processor containing memory/storage implementing computer software for processing the preprocessed PET and MR data).
However, while Poirier disclose storage and accessibility, Poirier may not explictly disclose the accessibility is remote accessibility.
However, in the same field of endeavor of PET imaging, Siemens teaches said storage and communication module (SC) allows storage and remote accessibility of said PET (IPP) and MRI data (IMP) to computation module (C) for further processing (3T hybrid PET/MR scanner system, Biograph mMR, transfers data to storage and communication module using the system workstation and allows for storage and remote accessibility of the stored PET and MRI datasets from different locations within the hospital over the hospital clinical network to computer software for further analysis and processing, Siemens, P.18-19).
It would have been obvious to one having ordinary skill in the art before the effective filing date to have applied Siemens’ known technique of acquiring and transferring data for storage and communication from the hybrid PET/MR scanner system via a hospital clinical network that is secured using protocols such as standard Digital Imaging and Communication in Medicine (DICOM) protocols to Poirier’s known process of acquiring and transferring data for storage and communication from the hybrid PET/MR scanner system to achieve the predictable result that this allows for easy viewing, sharing, and management of acquired PET and MR image data. See, e.g., Siemens, P.18-19.
Claim 13 is rejected as being anticipated, or, in the alternative, obvious over Poirier as evidenced by Siemens as detailed in claim 1 above, and further in view of Kim et al. ("Feasibility of computed tomography-guided methods for spatial normalization of dopamine transporter positron emission tomography image” 2015), hereinafter “Kim.”
Regarding claim 13, Poirier disclose said computation module (C) is equipped with high end processing computing submodule (C1) that has fast processor (C6) such as Core i7 processor and said storage (C3) (processing using computer software on a computer processor with memory to automatically detect epileptic focus from preprocessed PET and MRI data stored by the workstation of the 3T hybrid PET/MRI scanner system, Biograph mMR, including FSL, ANTS, SPM12, MATLAB, MRtrix3, clinical imaging software for visualization, SygnoVia, and computer-assisted diagnosis software, Abstract, P.4, ¶2 – P.5, ¶1, P.5, ¶2, P.5, ¶3 – P.6, ¶1, P.6, ¶2, Fig. 2; see also software integration, P.16, ¶3; as evidenced by Siemens, P.18-19 wherein the Biography mMR system incorporates a workstation for storage and communication of preprocessed PET and MR data for access by a processor containing memory/storage implementing computer software for processing the preprocessed PET and MR data).
However, Poirier does not appear to explictly disclose said storage with minimum 16 GB RAM.
However, in the same field of endeavor of PET imaging, Kim teaches a computation module (C) equipped with high end processing computing submodule (C1) that has fast processor (C6) such as Core i7 processor and said storage (C3) (image processing of the PET and MR images is performed using a dual 3.2GHz quad core Xeon CPU and 16 GB memory, P.12, ¶5 – P.14, ¶3; see also image processing of PET and MR images, Abstract, P.3, ¶5 – P.6, ¶ 4).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have applied Kim’s known technique of performing image processing using a dual 3.2GHz quad core Xeon CPU and 16 GB memory to Poirier’s known apparatus performing image processing using computer software implemented on a processor to achieve the predictable result that spatial normalization computing time as part of image processing of MR and PET images is dependent on the speed and memory capacity of the computer and that the computing time would be reduced by increasing the speed and memory capacity of the computer to increase computing throughput.
Claim 14 is rejected as being anticipated, or, in the alternative, obvious over Poirier as evidenced by Siemens as detailed in claim 1 above, and further as evidenced by The Wellcome Centre for Human Neuroimaging (“SPM 12 – Statistical Parametric Mapping” July 2023), hereinafter “SPM 2023.”
Regarding claim 14, Poirier discloses said language and interactive tool (C4) is MATLAB R2017b or later version with toolbox (C5) based on said language and interactive tool (C4) is SPM 12 toolbox (PET preprocessing and data analysis is performed using the SPM12 toolbox, Abstract, P.4, ¶2 – P.5, ¶1, P.5, ¶2, P.5, ¶3 – P.6, ¶1, P.6, ¶2, Fig. 2; see also software integration, P.16, ¶3; SPM12 is a toolbox implemented in the MATLAB software suite versions R2007a to R2023a as evidenced by SPM 2023).
Allowable Subject Matter
Claims 17-20 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action.
The following is a statement of reasons for the indication of allowable subject matter:
The cited and pertinent prior art does not appear to teach the combination of features of claim 17, lines 36-52:
creating an average symmetrical template (IT) using said computing tool for image registration (C7) such as DARTEL import files through nonlinear co-registration of the grey and white matter of flipped (IFM1, ITM1) and un flipped MRI (IFM, ITM) images
warping of all said images (IPP, ITM, IPP1, ITM1) to the average symmetrical template (IT) space created by computing tool for image registration (C7) using the corresponding flow fields of un-flipped by flow field 1 and flipped by flow field 2 images thereby obtaining warped images (IPPW, IPP1W, ITMW, ITM1W) that are corrected for interhemispheric structural asymmetry due to the precise overlap of anatomical regions on said flipped (IPP1, ITM1) and un flipped images (IPP, ITM),
warping inversely all said warped images (IPPW, IPP1W, ITMW, ITM1W) using flow field 1 causing warping of the un flipped images back to the native space and warping of the flipped images to anatomically overlap the grey and white matter of the un flipped images.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Aslam et al. (“Asymmetry index in anatomically symmetrized FDG-PET for improved epileptogenic focus detection in pharmacoreistant epilepsy” August 5, 2022) discloses a 3T hybrid PET/MR scanner system, workstation, and computer software for acquiring, pre-processing, and processing PET and MR images to automatically localize the epileptogenic focus in patients with pharmacoresistant epilepsy including using DARTEL to create a symmetrical template, warping flipped and unflipped images according to the symmetrical template, inversely warping the warped images, and using the inversely warped images to calculate the asymmetry index between flipped and unflipped images.
Poirier (“A hybrid PET/MRI brain connectivity approach for improving epilepsy surgical evaluation” 2020) discloses using a 3t hybrid PET/MR scanner system, workstation, and computer software for acquiring, pre-processing, and processing PET and MR images to automatically localize the epileptogenic focus in patients with pharmacoresistant epilepsy using the asymmetry index between flipped and unflipped images.
Shang et al. (“Clinical value of hybrid TOF-PET/MR imaging- Based multiparametric imaging in localizing seizure focus in patients with MRI-negative temporal lobe epilepsy” 2018) discloses using a hybrid PET/MR scanner system, workstation, and computer software for acquiring, pre-processing, and processing PET and MR images to automatically localize the epileptogenic focus in patients with pharmacoresistant epilepsy using the asymmetry index between flipped and unflipped images.
Glazzo et al. ("Cerebral metabolism and perfusion in MR-negative individuals with refractory focal epilepsy assessed by simultaneous acquisition of 18FDG PET and arterial spin labeling” 2016) discloses a 3T hybrid PET/MR scanner system, workstation, and computer software for acquiring, pre-processing, and processing PET and MR images to automatically localize the epileptogenic focus in patients with pharmacoresistant epilepsy including simultaneously acquiring PET and MR images while patients rested in a dark quiet room while in a fixed bed position for a 15-minute duration scan, and using right/left images to calculate the asymmetry index between the right and left images.
Siemens (“Biograph mMR” 2021) discloses a 3T hybrid PET/MR scanner system, workstation, and computer software for acquiring, pre-processing, and processing PET and MR images.
Didelot et al. (“Voxel-based analysis of asymmetry index maps increases the specificity of 18F-MPPF PET abnormalities for localizing the epileptogenic zone in temporal lobe epilepsies” 2010) discloses using a 1.5T MR scanner and PET scanner system, workstations, and computer software for acquiring, pre-processing, and processing PET and MR images to automatically localize the epileptogenic focus in patients with pharmacoresistant epilepsy using the asymmetry index between flipped and unflipped images.
Aslam et al. ("Statistical asymmetry analysis of volumetric MRI and FDG PET in temporal lobe epilepsy” July 5, 2022) discloses using a 3T MR scanner and PET scanner system, workstations, and computer software for acquiring, pre-processing, and processing PET and MR images to automatically localize hypmetabolism in patients with pharmacoresistant epilepsy using DARTEL to wrmp the flowfields of the right and left side images for calculating the asymmetry index (percentage metabolism loss) between the warped right and left side images.
Li et al. (“Gray matter asymmetry atypical patterns in subgrouping minors with autism based on core symptoms” January 2023) discloses using a MR scanner system, workstation, and computer software for acquiring, pre-processing, and processing MR images including using DARTEL to create a symmetrical template, warping flipped and unflipped images according to the symmetrical template, and using the warped images to calculate the asymmetry index.
Floris et al. (“Atypically rightward cerebral asymmetry in male adults with autism stratifies individuals with and without language delay” 2015) discloses using a MR scanner system, workstation, and computer software for acquiring, pre-processing, and processing MR images including using DARTEL to create a symmetrical template, warping flipped and unflipped images according to the symmetrical template, and using the warped images to calculate the asymmetry index.
Pizzagalli (“Etude par neuroimagerie IRM de la representation centrale des mouvements de la main chez les sujects sains et chez les patients apres chirurgie de la main” 2013) discloses using a MR scanner system, workstation, and computer software for acquiring, pre-processing, and processing MR images including using DARTEL to create a symmetrical template, warping flipped and unflipped images according to the symmetrical template, and using the warped images to calculate the asymmetry index.
Kim et al. (“Asymmetric gray matter volume changes associated with epilepsy duration and seizure frequency in temporal-lobe-epilepsy patients with favorable surgical outcome” 2016) discloses using a MR scanner system, workstation, and computer software for acquiring, pre-processing, and processing MR images including using DARTEL to create a symmetrical template, warping flipped and unflipped images according to the symmetrical template, and using the warped images to calculate the asymmetry index.
Soma et. al. (“Usefulness of extent analysis for statistical parametric mapping with asymmetry index using inter-ictal FGD-PET in mesial temporal lobe epilepsy” 2012) discloses a PET scanner system, workstation, and computer software for acquiring, pre-processing, and processing PET images to automatically localize the epileptogenic focus in patients with pharmacoresistant epilepsy including acquiring PET images while patients rested in a supine position on the imaging bed with an eye mask to control the environment and to exclude clinical seizure activity, and creating a symmetrical template, and using flipped and unflipped images to calculate the asymmetry index between flipped and unflipped images.
The Wellcome Centre for Human Neuroimaging (“SPM12 Manual” 2021) discloses the tools/toolboxes available in the MATLAB high-level language and interactive environment using the SPM12 tool/toolbox including DARTEL.
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/J.M./Examiner, Art Unit 3798
/KEITH M RAYMOND/Supervisory Patent Examiner, Art Unit 3798