DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Responsive to the communication dated 5/15/2024.
Claims 1 – 10 are presented for examination
Priority
ADS dated 11/28/2022 claims foreign priority to KR 10-2022-0014011 dated 2/3/2022.
Information Disclosure Statement
IDS dated 11/28/2022 and 5/15/2024 have been reviewed. See attached.
Drawings
The drawings dated 11/28/2022 have been reviewed. They are accepted.
Specification
The abstract dated 11/28/2022 has 54 words and 4 lines. The abstract, however, cites purported benefits/merits. MPEP 608.01(b) states: “…the abstract should not refer to purported merits or speculative applications of the invention and should not compare the invention with the prior art…”. Accordingly, the Office objects to the abstract.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 8 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because claim 8 recites “a program for modeling…” and a program is not one of the four statutory categories. MPEP 2106.03 indicates that a process, machine, manufacture, and compositions of matter are eligible categories. The claim recites “a program” and a “program” does not have a physical or tangible form and is therefore considered to be a computer program per se.
While the claim recites “… the medium… with a computer that is hardware” there is no indication that the “medium” is not a non-transitory one. While the instant specification indicates that the medium “may be implemented as at least one storage medium of a non-volatile memory…” this is merely an example and as such does not limit the “medium” to a non-volatile one. Accordingly, the claim is a disembodied signal/data per se with an unconnected computer. While the claim recites “in combination with a computer that is hardware” there is no indication that the computer is doing anything with the claimed “program.”
If the “program” was stored on non-transitory media communicatively connected to a computer process that was executing the program then there would be sufficient structure for the claimed “program” to be found to be in tangible form.
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.
Claim 8 recites the limitation "the medium" in line two. There is insufficient antecedent basis for this limitation in the claim.
Claim Rejections - 35 USC § 103
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.
Claims 1, 8, 9 are rejected under 35 U.S.C. 103 as being unpatentable over Brown_2016 (US 9,414,747 B2) in view of Uthgenannt_2010 (US 2010/0324692 A1).
Claim 1. Brown_2016 makes obvious “A method performed by an apparatus for modeling a user-customized assistive tool (abstract: “systems and methods of integrating a virtual prosthesis with a tissue model…”; COL 1 line 55: “… thus there is still a need for providing method of modeling prosthesis and tissues… The inventive subject matter provides apparatus, systems, and methods that allows individuals to observe prosthetic device – tissue interactions…”; COL 2 lines 13 – 15: “…FIG. 3 is an example interface allowing a user to measure physical points of a tissue model and adjust a virtual prosthesis model…”; COL 5 lines35 – 40: “… such an approach is considered advantageous when constructing a desirable or custom prosthesis that specifically targets tissue…”), the method comprising: obtaining a three-dimensional body [data] of a user (FIG. 4: signals 415, sensors 420, Tissue database 453 illustrate the process of obtaining image data from physical signals reflected from tissue and collected by sensors. COL 1 lines 60 – 66: “… the modeling engine constructs an observable model the combines a tissue model and a prosthesis mode. The modeling engine then presents the observable model (e.g., 2D, 3D, 4D) or other dimensional rendering…” COL 3 lines 30 – 35: “… pre-operative assessment is based on a single phase or multi-phase CT scan… a CT scan of the graft clearly shows the metal “skeleton” of the graft as illustrated in FIG. 1…”; COL 4: “… for example, tissue 410 could include a bone to which an artificial joint couples. In such a scenario, tissue 410 could also include neighboring muscles, cartilage, ligaments, or other portions of the body. Tissues 410 can include wide variety of tissues, preferably including tissues that are amenable to couple with a prosthesis. Examples tissues include vessels, bone, arteries, valves, joints, organs, anatomical structures, or other types of tissues… human, mammal, or other animals… the reader should appreciate that tissues 410 can comprise other structures or tissues (e.g., bone, organs, muscles, etc.). In some embodiments, modeling system 400 can obtain tissue characteristics from signals 415 originating from tissue 410 where signals 415 include information reflecting one or more tissue properties… signals 415 include acoustic signals (e.g., ultrasound), signals 415 can be representative of size, shape, volume, or density of tissues 415. In other embodiments, signal 415 could include electromagnetic signals (e.g., MRI, X-Ray, CT, etc.)… regardless of the form signals 415, signals 415 can be received or otherwise obtained via one or more sensors 420… which collect and convert signals 415 into digital data…”); Providing one or more applicable shape templates of an assistive tool (COL 5: “… when constructing a desirable or custom prosthesis that specifically targets tissue 410… modeling engine 450 can then obtain a prosthesis template from prosthesis database 455 possibly from a manufacturer, and then flesh out the attributes of the template based on the determined properties…”) based on disease information of the user, skeletal information of a part where the assistive tool is worn, joint information (COL 5 lines 25 – 55: “… prosthesis database 455 can comprise a catalog of known prosthesis, possibly stored according to a schema that indexes the prosthesis by type, make, model, manufacturer, size, dimensions, target tissue type, product code, or other schema… such an approach is considered advantageous when constructing a desirable or custom prosthesis that specifically targets tissues 410… example prosthesis include a stent, a valve, a joint replacement, a sensory implant (e.g., ocular, cochlear, vestibular, hearing aid, cornea, etc.), an electrical implant (e.g., pace-maker, neural shunt, etc.), a living tissue (e.g., transplant, graft, etc.), an artificial muscle, or other types of prosthesis known or yet to be invented…”
COL 4 lines 9 – 25: “… a prosthesis interacts with a target tissue to which to prosthesis is coupled, one should appreciate that tissue 410 could also include a neighboring tissue. For example, tissue 410 could include a bone to which an artificial joint couple… Tissues 410 can include a wide variety of tissues, preferably including tissues that are amenable to couple with a prosthesis. Example tissues include vessels, bone, arteries, valves, joints, organs, anatomical structures… tissue 410 can comprise other structures or tissue (e.g., bone…”; COL 8 lines 43 – 46: “… tissue characteristics can be classified according to number of patient categorizations including race, gender, genetic markers, disease, cancer, age, geography, or other demographic…”
EXAMINER NOTE: the above citation teaches that a prosthesis template is stored and retrieved from a database according to, for example, target tissue or type of implant. The above citation, however, does not EXPLICITLY recite that the template is based on “disease,” however, the “type” of implant implies if not inherently includes the disease information. The above citation, for example, lists types of templates called “stent”, “ocular”, “cochlear”, “pace-maker”, etc. and these types of implant templates implies artery disease (i.e., stent), a vision disease (i.e., ocular), a hearing disease (i.e., cochlear), and heart disease (i.e., pace maker). Further, the above citation teaches that the template is stored and retrieved according to target tissue and according to COL 4 the target tissue includes “bone to which an artificial joint couples… Examples of tissues include vessels, bone, arteries, valves, joints… (e.g., bone, organs, muscle, etc.)…”. Therefore, the template may be retrieved from the template database based on skeletal information (i.e., bone) and joint information. Additionally, COL 8 teaches that the tissue characteristics can be classified according to “disease” and “cancer”. Therefore, if the template is retrieved based on target tissue and the tissue is classified by “disease” and “cancer” the template is based on disease.), and characteristic information (COL 5: “… modeling engine 450 preferably also has access to one or more prosthesis characteristics… prosthesis characteristics can also include a wide spectrum of possible properties… the prosthesis characteristics are complementary to the tissue characteristics. Example prosthesis characteristics can include electrical properties (e.g., resistance, conductivity, inductance, etc.), chemical properties (e.g., p.H., etc.), mechanical properties (e.g., stress, strain, shear, elasticity, hardness, density, etc.), state, geometric properties (e.g., lengths, widths, size, volume, dimensions, etc.), temporal properties (e.g., degradation, ability to move or flex with time, state changes, wear or tear, etc.), or other prosthetic properties… prosthesis characteristics can be stored in prosthesis database 455, which is configured to store properties. In some embodiments, prosthesis database 455 can comprise a catalog of known prosthesis, possibly stored according to a schema that indexes the prosthesis by type, make, model, manufacturer, size, dimension, target tissue type, produce code, or other schema…”); and when the shape template of the assistive tool is selected (COL 6: “… a user can select one or more of prosthesis from prosthesis database 455 where prosthesis database 455 is configured to store available prosthesis as discussed previously…”; COL 8: “… a healthcare provider can select a desired prosthesis from the prosthesis database for inclusion into the model, where the selected prosthesis from the database can have the desirable characteristics…”), processing the selected shape template to be user-customized (COL 2 lines 13 – 15: “…FIG. 3 is an example interface allowing a user to measure physical points of a tissue model and adjust a virtual prosthesis model…”; COL 5 lines 35 – 47: “… such an approach is considered advantageous when constructing a desirable or custom prosthesis that specifically targets tissue… obtain a prosthesis template from prosthesis database 455 possibly from a manufacturer, and then flesh out the attributes of the template based on determined properties…”).
While Brown_2016 teaches to obtain body “data” and to create a 3D model from this data, and while this may make to obtain “three-dimensional body image” obvious to those of ordinary skill in the art because the body data taught by Brown_2016 includes CT-scan, X-ray, MRI, and ultrasound data that is commonly called CT image data, X-ray image data, MRI image data, and ultrasound image data, Brown_2016 does not explicitly use the phrase “image.”
Uthgenannt_2010 however, makes obvious “Three-dimensional body image” (par 44: “… start 502 with an input of the three-dimensional image of the patient’s anatomy 510…”; par 65: “… by selecting a relatively large number of parameters corresponding to the patient’s anatomy, as captured in the three-dimensional image of the corresponding joint portion of the patient, the semi-custom implant can be made to correspond to the patient’s anatomy as closely as desired…”; page 9 item 13: “… specific medial angles and three patient-specific lateral angles, wherein the lengths and medial and lateral angles are selected preoperatively based on a three-dimensional image of an anatomy of a patient to match the anatomy of the patient…”) and “disease” (par 39: “… tissue associated with the affected anatomy… torn or diseased tissue…” and “processing the selected shape template to be user-customized” (Figure 1, 13B “semi-custom”; par 33: “… a custom made implant specific to the patient, an implant that is only partially custom-made or semi-custom implant…”).
Brown_2016 and Uthgenannt_2010 are analogous art because they are from the same field of endeavor called prosthetics. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Brown_2016 and Uthgenannt_2010. The rationale for doing so would have been that Brown_2016 teaches to obtain tissue data and to select a prosthetic template and to adjust the prosthetic and to have custom prosthesis and to flesh out attributes of the template based on the target tissue. Uthgenannt_2010 teaches that three-dimensional images of the target body tissue can provide parameters used to customize the prosthetic to match the patient’s anatomy. Therefore, it would have been obvious to combine Brown_2016 and Uthgenannt_2010 for the benefit of having data in the form of three-dimensional images that can provide parameters that support the customization of the prosthesis template to the patient’s anatomy to obtain the invention as specified in the claims.
Claim 8. The limitations of claim 8 are substantially the same as those of claim 1 and are therefore rejected due to the same reasons as outlined above for claim 1. Additionally, Brown_2016 makes obvious the further limitations of “A program for modeling a user-customized assistive tool stored in the medium to execute the method of claim 1 in combination with a computer that is hardware” (COL 2: “… while the following description is drawn to a computer/server based tissue analysis or modeling system, various alternative configurations are also deemed suitable and may employ various computing devices including servers, controllers… the computing device comprises a processor configured to execute software instructions stored on tangible, non-transitory computer readable storage medium (e.g., hard drive, solid state drive, RAM, flash, ROM, etc.)…”).
Claim 9. he limitations of claim 9 are substantially the same as those of claim 1 and are therefore rejected due to the same reasons as outlined above for claim 1. Additionally, Brown_2016 makes obvious the further limitations of “An apparatus for modeling a user-customized assistive tool, the apparatus comprising: At least one processor; and A memory electrically connected to the processor to store at least one code executed by the processor, Wherein the memory stores code that, when executed, cause the processor to” (COL 2: “… while the following description is drawn to a computer/server based tissue analysis or modeling system, various alternative configurations are also deemed suitable and may employ various computing devices including servers, controllers… the computing device comprises a processor configured to execute software instructions stored on tangible, non-transitory computer readable storage medium (e.g., hard drive, solid state drive, RAM, flash, ROM, etc.)…”).
Claims 2, 3, 4, 5, 6, 7, 10 are rejected under 35 U.S.C. 103 as being unpatentable over Brown_2016 in view of Uthgenannt_2010 in view of Mahfouz_2019 (US 10,258,256 B2)
Claim 2. Mahfouz_2019 makes obvious “wherein the providing of the shape templates include: Providing a wear suitability of each of the shape templates based on a percentage” (FIG. 29 illustrates a distribution with patient specific implant being suitable for 10% of the population wile mass customization is suitable for 90% of the population. FIG. 31 illustrates clustering used to generate implants for population clusters (i.e., implants suitable for a percentages of the population); COL 24: “… the mathematical descriptor is clustered or grouped based upon a statistical analysis. In particular, the descriptor is statistically analyzed and compared to other descriptors from other patients/cadavers to identify unique defect classes within a given population. Obviously, this classification is premised upon multiple descriptors from multiple patients/cadavers that refine the classification and identification of discrete groups as the number of patients/cadavers grows. The output from this statistical analysis is a set of defect classes that are used to classify new input anatomical data and determine the number of templates. The output of the defect classification module is directed to a template module. In exemplary form, the template module includes data that is specific as to each of the defect classifications identified by the defect classification module… …outputs from the template module and the statistical atlas are utilized by a mass customization module to design, test, and allow fabrication of mass customized implants, fixation devices, instruments or molds…”; COL 30: “… the shape/surface outputs come from a shape/surface module also receiving inputs from the statistical atlas. In the context of the shape/surface module, the virtual, 3D models within the statistical atlas population are analyzed for shape/surface features that are not encompassed by the automatic landmarking. In other words, features corresponding to the overall 3D shape of the anatomy, but not belonging to features defined in the previous automatic landmarking step are calculated as well. For example, curvature data is calculated for the virtual 3D models. Outputs from the surface/shape analysis module and the automatic landmarking module are directed to a feature extraction module. Using a combination of landmarks and shape features, mathematical descriptors (i.e., curvature, dimensions) relevant to implant design are calculated for each instance in the atlas. These descriptors are used as input to a clustering process. The mathematical descriptor is clustered or grouped based upon a statistical analysis. In particular, the descriptor is statistically analyzed and compared to other descriptors form the remaining anatomy population to identify groups from the remaining anatomy population to identify groups (of anatomies) having similar features within the population. Obviously, this clustering is premised upon multiple descriptors from multiple anatomies across the population. As new instances are presented to the clustering, which were not presented in the initial clustering, the output clusters are refined to better represent the new population. The output from the statistical analysis is a finite number of implants (including implant families and sizes) covering all of the vast majority of the anatomical population…”
EXAMINER NOTE: The above citation teach that implants are designed to statistically match clustered groups of the population (i.e., White, Black, Asian, Male, Female, etc.) and that these clusters result in families of implants with sizes that statistically match (i.e., are suitable/fit) these population clusters. Accordingly, a patient’s tissue is measured/parameterized/characterized and if the patient’s measurements/parameters/characteristics statistically match one of these clusters then the implant family/size is suitable for that patient. The family of implants suitable for a cluster is a percentage of the total population. All implant families cover approximately 90% of the total population. This further means that the implants will not be suitable for approximately 10% of the population of total population.)
Brown_2016 and Uthgenannt_2010 and Mahfouz_2019 are analogous art because they are from the same field of endeavor called prosthetics. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Brown_2016 and Uthgenannt_2010 and Mahfouz_2019
The rationale for doing so would have been that both Brown_2016 and Uthgenannt_2010 teach to have customized prosthetics/implants. Uthgenannt_2010 in particular teaches that prosthetics/implants may be standard off-the-shelf, semi-custom or full custom implants (FIG. 1). Brown_2016 teaches that a prosthetic template can be obtain and then the attributes of the prosthetic template can be fleshed out when constructing custom template that specifically target patient tissue (COL 5 lines 35 – 46). Mahfouz_2019 teaches to create families of implant models with sizes that are suitable/fit for segments of the overall population and also teaches that if the patient’s target tissue does not statistically match (i.e., suitably fit that % of the population) to create a custom implant. Therefore, it would have been obvious to combine Brown_2016 and Uthgenannt_2010 and Mahfouz_2019 for the benefit of identifying if an off-the-shelf prosthesis/implant suitably fits the patient and knowing when to use a semi-custom (i.e., modified off-the-shelf prosthesis/implant) or full-custom prosthesis/implant to obtain the invention as specified in the claims.
Claim 3. Mahfouz_2019 makes obvious “wherein the providing of the wear suitability includes: Providing the wear suitability based on a percentage by inputting the skeletal information, the joint information of the user, and the characteristic information of the part into a pre-learned fit analysis model” (COL 24: “… the mathematical descriptor is clustered or grouped based upon a statistical analysis. In particular, the descriptor is statistically analyzed and compared to other descriptors from other patients/cadavers to identify unique defect classes within a given population. Obviously, this classification is premised upon multiple descriptors from multiple patients/cadavers that refine the classification and identification of discrete groups as the number of patients/cadavers grows. The output from this statistical analysis is a set of defect classes that are used to classify new input anatomical data and determine the number of templates. The output of the defect classification module is directed to a template module. In exemplary form, the template module includes data that is specific as to each of the defect classifications identified by the defect classification module… …outputs from the template module and the statistical atlas are utilized by a mass customization module to design, test, and allow fabrication of mass customized implants, fixation devices, instruments or molds…”; COL 30: “… the shape/surface outputs come from a shape/surface module also receiving inputs from the statistical atlas. In the context of the shape/surface module, the virtual, 3D models within the statistical atlas population are analyzed for shape/surface features that are not encompassed by the automatic landmarking. In other words, features corresponding to the overall 3D shape of the anatomy, but not belonging to features defined in the previous automatic landmarking step are calculated as well. For example, curvature data is calculated for the virtual 3D models. Outputs from the surface/shape analysis module and the automatic landmarking module are directed to a feature extraction module. Using a combination of landmarks and shape features, mathematical descriptors (i.e., curvature, dimensions) relevant to implant design are calculated for each instance in the atlas. These descriptors are used as input to a clustering process. The mathematical descriptor is clustered or grouped based upon a statistical analysis. In particular, the descriptor is statistically analyzed and compared to other descriptors form the remaining anatomy population to identify groups from the remaining anatomy population to identify groups (of anatomies) having similar features within the population. Obviously, this clustering is premised upon multiple descriptors from multiple anatomies across the population. As new instances are presented to the clustering, which were not presented in the initial clustering, the output clusters are refined to better represent the new population. The output from the statistical analysis is a finite number of implants (including implant families and sizes) covering all of the vast majority of the anatomical population…”
EXAMINER NOTE: Clustering premised upon multiple descriptors from multiple anatomies across a population implies to those of ordinary skill in the art an unsupervised, integrative, multi-view machine learning approach designed to group individuals (or biological samples) by analyzing complex, high-dimensional, and heterogeneous data from diverse anatomical locations simultaneously. In other words, this is a training of the clustering analysis model. Indeed, the above citations recite that “the output clusters are refined to better represent the new population.” This indicates that current version of the model is “pre-learned” on previous data.)
Uthgenannt_2010 makes obvious “the disease information, age information, gender information” (par 60: “the system manager 402 can provide access to patient’s file information… each patient file can include personal and medical information of the patient, such as, for example, weight, height, gender, age, lifestyle, pertinent medical records and medical history, as well as information on patient assessment that includes physical and kinematic evaluation pertaining to the orthopedic procedure…” EXAMINER NOTE: physical and kinematic assessment is disease information because an orthopedic disease impacts physical and kinematic behavior of the patient.)
Brown_2016 also makes obvious “… the disease information… the skeletal information, the joint information of the user (COL 5 lines 25 – 55: “… prosthesis database 455 can comprise a catalog of known prosthesis, possibly stored according to a schema that indexes the prosthesis by type, make, model, manufacturer, size, dimensions, target tissue type, product code, or other schema… such an approach is considered advantageous when constructing a desirable or custom prosthesis that specifically targets tissues 410… example prosthesis include a stent, a valve, a joint replacement, a sensory implant (e.g., ocular, cochlear, vestibular, hearing aid, cornea, etc.), an electrical implant (e.g., pace-maker, neural shunt, etc.), a living tissue (e.g., transplant, graft, etc.), an artificial muscle, or other types of prosthesis known or yet to be invented…”
COL 4 lines 9 – 25: “… a prosthesis interacts with a target tissue to which to prosthesis is coupled, one should appreciate that tissue 410 could also include a neighboring tissue. For example, tissue 410 could include a bone to which an artificial joint couple… Tissues 410 can include a wide variety of tissues, preferably including tissues that are amenable to couple with a prosthesis. Example tissues include vessels, bone, arteries, valves, joints, organs, anatomical structures… tissue 410 can comprise other structures or tissue (e.g., bone…”; COL 8 lines 43 – 46: “… tissue characteristics can be classified according to number of patient categorizations including race, gender, genetic markers, disease, cancer, age, geography, or other demographic…”
EXAMINER NOTE: the above citation teaches that a prosthesis template is stored and retrieved from a database according to, for example, target tissue or type of implant. The above citation, however, does not EXPLICITLY recite that the template is based on “disease,” however, the “type” of implant implies if not inherently includes the disease information. The above citation, for example, lists types of templates called “stent”, “ocular”, “cochlear”, “pace-maker”, etc. and these types of implant templates implies artery disease (i.e., stent), a vision disease (i.e., ocular), a hearing disease (i.e., cochlear), and heart disease (i.e., pace maker). Further, the above citation teaches that the template is stored and retrieved according to target tissue and according to COL 4 the target tissue includes “bone to which an artificial joint couples… Examples of tissues include vessels, bone, arteries, valves, joints… (e.g., bone, organs, muscle, etc.)…”. Therefore, the template may be retrieved from the template database based on skeletal information (i.e., bone) and joint information. Additionally, COL 8 teaches that the tissue characteristics can be classified according to “disease” and “cancer”. Therefore, if the template is retrieved based on target tissue and the tissue is classified by “disease” and “cancer” the template is based on disease.), and the characteristic information of the part…” (COL 5: “… modeling engine 450 preferably also has access to one or more prosthesis characteristics… prosthesis characteristics can also include a wide spectrum of possible properties… the prosthesis characteristics are complementary to the tissue characteristics. Example prosthesis characteristics can include electrical properties (e.g., resistance, conductivity, inductance, etc.), chemical properties (e.g., p.H., etc.), mechanical properties (e.g., stress, strain, shear, elasticity, hardness, density, etc.), state, geometric properties (e.g., lengths, widths, size, volume, dimensions, etc.), temporal properties (e.g., degradation, ability to move or flex with time, state changes, wear or tear, etc.), or other prosthetic properties… prosthesis characteristics can be stored in prosthesis database 455, which is configured to store properties. In some embodiments, prosthesis database 455 can comprise a catalog of known prosthesis, possibly stored according to a schema that indexes the prosthesis by type, make, model, manufacturer, size, dimension, target tissue type, produce code, or other schema…”)
Claim 10. Mahfouz_2019 makes obvious “Wherein the processor is configured to, when a wear suitability of each of the shape templates based one a percentage is provided, provide the wear suitability based on a percentage by (COL 24: “… the mathematical descriptor is clustered or grouped based upon a statistical analysis. In particular, the descriptor is statistically analyzed and compared to other descriptors from other patients/cadavers to identify unique defect classes within a given population. Obviously, this classification is premised upon multiple descriptors from multiple patients/cadavers that refine the classification and identification of discrete groups as the number of patients/cadavers grows. The output from this statistical analysis is a set of defect classes that are used to classify new input anatomical data and determine the number of templates. The output of the defect classification module is directed to a template module. In exemplary form, the template module includes data that is specific as to each of the defect classifications identified by the defect classification module… …outputs from the template module and the statistical atlas are utilized by a mass customization module to design, test, and allow fabrication of mass customized implants, fixation devices, instruments or molds…”; COL 30: “… the shape/surface outputs come from a shape/surface module also receiving inputs from the statistical atlas. In the context of the shape/surface module, the virtual, 3D models within the statistical atlas population are analyzed for shape/surface features that are not encompassed by the automatic landmarking. In other words, features corresponding to the overall 3D shape of the anatomy, but not belonging to features defined in the previous automatic landmarking step are calculated as well. For example, curvature data is calculated for the virtual 3D models. Outputs from the surface/shape analysis module and the automatic landmarking module are directed to a feature extraction module. Using a combination of landmarks and shape features, mathematical descriptors (i.e., curvature, dimensions) relevant to implant design are calculated for each instance in the atlas. These descriptors are used as input to a clustering process. The mathematical descriptor is clustered or grouped based upon a statistical analysis. In particular, the descriptor is statistically analyzed and compared to other descriptors form the remaining anatomy population to identify groups from the remaining anatomy population to identify groups (of anatomies) having similar features within the population. Obviously, this clustering is premised upon multiple descriptors from multiple anatomies across the population. As new instances are presented to the clustering, which were not presented in the initial clustering, the output clusters are refined to better represent the new population. The output from the statistical analysis is a finite number of implants (including implant families and sizes) covering all of the vast majority of the anatomical population…”
EXAMINER NOTE: Clustering premised upon multiple descriptors from multiple anatomies across a population implies to those of ordinary skill in the art an unsupervised, integrative, multi-view machine learning approach designed to group individuals (or biological samples) by analyzing complex, high-dimensional, and heterogeneous data from diverse anatomical locations simultaneously. In other words, this is a training of the clustering analysis model. Indeed, the above citations recite that “the output clusters are refined to better represent the new population.” This indicates that current version of the model is “pre-learned” on previous data.)
Uthgenannt_2010 makes obvious “the disease information, age information, gender information” (par 60: “the system manager 402 can provide access to patient’s file information… each patient file can include personal and medical information of the patient, such as, for example, weight, height, gender, age, lifestyle, pertinent medical records and medical history, as well as information on patient assessment that includes physical and kinematic evaluation pertaining to the orthopedic procedure…” EXAMINER NOTE: physical and kinematic assessment is disease information because an orthopedic disease impacts physical and kinematic behavior of the patient.)
Brown_2016 also makes obvious “… the disease information… the skeletal information, the joint information of the user (COL 5 lines 25 – 55: “… prosthesis database 455 can comprise a catalog of known prosthesis, possibly stored according to a schema that indexes the prosthesis by type, make, model, manufacturer, size, dimensions, target tissue type, product code, or other schema… such an approach is considered advantageous when constructing a desirable or custom prosthesis that specifically targets tissues 410… example prosthesis include a stent, a valve, a joint replacement, a sensory implant (e.g., ocular, cochlear, vestibular, hearing aid, cornea, etc.), an electrical implant (e.g., pace-maker, neural shunt, etc.), a living tissue (e.g., transplant, graft, etc.), an artificial muscle, or other types of prosthesis known or yet to be invented…”
COL 4 lines 9 – 25: “… a prosthesis interacts with a target tissue to which to prosthesis is coupled, one should appreciate that tissue 410 could also include a neighboring tissue. For example, tissue 410 could include a bone to which an artificial joint couple… Tissues 410 can include a wide variety of tissues, preferably including tissues that are amenable to couple with a prosthesis. Example tissues include vessels, bone, arteries, valves, joints, organs, anatomical structures… tissue 410 can comprise other structures or tissue (e.g., bone…”; COL 8 lines 43 – 46: “… tissue characteristics can be classified according to number of patient categorizations including race, gender, genetic markers, disease, cancer, age, geography, or other demographic…”
EXAMINER NOTE: the above citation teaches that a prosthesis template is stored and retrieved from a database according to, for example, target tissue or type of implant. The above citation, however, does not EXPLICITLY recite that the template is based on “disease,” however, the “type” of implant implies if not inherently includes the disease information. The above citation, for example, lists types of templates called “stent”, “ocular”, “cochlear”, “pace-maker”, etc. and these types of implant templates implies artery disease (i.e., stent), a vision disease (i.e., ocular), a hearing disease (i.e., cochlear), and heart disease (i.e., pace maker). Further, the above citation teaches that the template is stored and retrieved according to target tissue and according to COL 4 the target tissue includes “bone to which an artificial joint couples… Examples of tissues include vessels, bone, arteries, valves, joints… (e.g., bone, organs, muscle, etc.)…”. Therefore, the template may be retrieved from the template database based on skeletal information (i.e., bone) and joint information. Additionally, COL 8 teaches that the tissue characteristics can be classified according to “disease” and “cancer”. Therefore, if the template is retrieved based on target tissue and the tissue is classified by “disease” and “cancer” the template is based on disease.), and the characteristic information of the part…” (COL 5: “… modeling engine 450 preferably also has access to one or more prosthesis characteristics… prosthesis characteristics can also include a wide spectrum of possible properties… the prosthesis characteristics are complementary to the tissue characteristics. Example prosthesis characteristics can include electrical properties (e.g., resistance, conductivity, inductance, etc.), chemical properties (e.g., p.H., etc.), mechanical properties (e.g., stress, strain, shear, elasticity, hardness, density, etc.), state, geometric properties (e.g., lengths, widths, size, volume, dimensions, etc.), temporal properties (e.g., degradation, ability to move or flex with time, state changes, wear or tear, etc.), or other prosthetic properties… prosthesis characteristics can be stored in prosthesis database 455, which is configured to store properties. In some embodiments, prosthesis database 455 can comprise a catalog of known prosthesis, possibly stored according to a schema that indexes the prosthesis by type, make, model, manufacturer, size, dimension, target tissue type, produce code, or other schema…”)
Brown_2016 and Uthgenannt_2010 and Mahfouz_2019 are analogous art because they are from the same field of endeavor called prosthetics. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Brown_2016 and Uthgenannt_2010 and Mahfouz_2019
The rationale for doing so would have been that both Brown_2016 and Uthgenannt_2010 teach to have customized prosthetics/implants. Uthgenannt_2010 in particular teaches that prosthetics/implants may be standard off-the-shelf, semi-custom or full custom implants (FIG. 1). Brown_2016 teaches that a prosthetic template can be obtain and then the attributes of the prosthetic template can be fleshed out when constructing custom template that specifically target patient tissue (COL 5 lines 35 – 46). Mahfouz_2019 teaches to create families of implant models with sizes that are suitable/fit for segments of the overall population and also teaches that if the patient’s target tissue does not statistically match (i.e., suitably fit that % of the population) to create a custom implant. Therefore, it would have been obvious to combine Brown_2016 and Uthgenannt_2010 and Mahfouz_2019 for the benefit of identifying if an off-the-shelf prosthesis/implant suitably fits the patient and knowing when to use a semi-custom (i.e., modified off-the-shelf prosthesis/implant) or full-custom prosthesis/implant to obtain the invention as specified in the claims.
Claim 4. Brown_2016 makes obvious “further comprising: displaying the obtained body image on a three-dimensional basis, Wherein the processing of the selected shape template includes: Selecting a plurality of reference points on a displayed body region on which an assistive tool is to be worn; and combining the displaying the selected shape template to the body region based on the plurality of selected reference points” (COL 2 lines 13 – 15: “…FIG. 3 is an example interface allowing a user to measure physical points of a tissue model and adjust a virtual prosthesis model…”; COL 9 lines 15 – 60: “… can include allowing one or more user to identify one or more physical points in space, or time, based on the presented observable model (e.g., an image) of an anatomical structure. The modeling engine can then generate one or more measurements at step 565 associated with the identified points. Consider the example illustrated in FIG. 3. The illustrated interface allows identification and selection of points in space, and time, to determine an appropriate size for a graft. The measurements can represent information beyond physical dimensions (e.g., distance, length, widths, area, volume, etc.). Example additional measurements can include stress strain, density, conductivity, perfusion, or other measurements of the tissue or prosthetic properties…. The modeling engine allows a user to select available prosthesis, providing prosthetic dimensions to an external prosthesis database (e.g., EMR, etc.), or input physical points in the model from which the modeling engine derives measurements (e.g., a distance, an area, a volume, a stress, a strain, a perfusion, etc.) relating to the tissue or prosthetic… further include obtaining prosthesis measurements from the observable model and submitting the measurement to a prosthesis database. Preferably, the measurements are derived from a deformable registration imaging system (see FIG. 3). For example, while observing a tissue model, a technician can determine the appropriate measurements for the target prosthesis… the manufacturer can then construct the prosthesis according to measurements…”).
Claim 5. Brown_2016 makes obvious “wherein the processing of the selected shape template includes: visually guiding a number and positions of the plurality of reference points based on a part on which the assistive tool is to be worn and a shape of the assistive tool” COL 9 lines 15 – 60: “… can include allowing one or more user to identify one or more physical points in space, or time, based on the presented observable model (e.g., an image) of an anatomical structure. The modeling engine can then generate one or more measurements at step 565 associated with the identified points. Consider the example illustrated in FIG. 3. The illustrated interface allows identification and selection of points in space, and time, to determine an appropriate size for a graft. The measurements can represent information beyond physical dimensions (e.g., distance, length, widths, area, volume, etc.). Example additional measurements can include stress strain, density, conductivity, perfusion, or other measurements of the tissue or prosthetic properties…. The modeling engine allows a user to select available prosthesis, providing prosthetic dimensions to an external prosthesis database (e.g., EMR, etc.), or input physical points in the model from which the modeling engine derives measurements (e.g., a distance, an area, a volume, a stress, a strain, a perfusion, etc.) relating to the tissue or prosthetic… further include obtaining prosthesis measurements from the observable model and submitting the measurement to a prosthesis database. Preferably, the measurements are derived from a deformable registration imaging system (see FIG. 3). For example, while observing a tissue model, a technician can determine the appropriate measurements for the target prosthesis… the manufacturer can then construct the prosthesis according to measurements…”).
Claim 6. Brown_2016 makes obvious “wherein the processing of the selected shape template includes: adjusting a compression intensity level of the selected shape template (COL 7 lines 55 – 65: “… an astute reader will readily appreciate the value of presenting mutual deformation 458 and possible incompatibilities. For example, a finite element analysis of a graft skeleton model can be performed to estimate a probability of failure based on the amount of predicted deformation (e.g., sheer, strain, compression, tension, torsion, etc.). Thus, mutual deformation 458 can include predicted deformation that can be based on an absolute deformation of the tissue or prosthesis device, or a relative deformation between the tissue and prosthesis, possibly during a simulation of a specific activity…”
EXAMINER NOTE: it would be obvious to those of ordinary skill in the art to adjust the compression in the event that the above cited analysis indicates that the compression is incompatible with the tissue and/or failure of the prosthesis.), a size of a region covering the body region (COL 3 lines 30 – 40: “… the key to successful repair is correct sizing and placement of the graft… historically, the size of the graft is selected by measuring distance… each manufacturer offers standard sizes of varying configurations of the diameter and lengths. A volumetric model of the graft…”; COL 5 lines 10 – 50: “… one or more prosthesis characteristics… prosthesis characteristics can also include a wide spectrum of possible properties… geometric properties (e.g., length, width, size, volume, dimensions, etc.)… prosthesis database 455 can be populated with information obtained from tissue 410. Such and approach is considered advantageous when constructing a desirable or custom prosthesis that specifically targets tissue 410… modeling engine 450 can determine acceptable properties of a prosthesis (e.g., material or materials, size, shape, dimensions… modeling engine 450 can then obtain a prosthesis template from prosthesis database 455 possibly from a manufacturer, and then flesh out the attributes of the template based on the determined properties. The fleshed out template can then be submitted to the manufacturer… a 3D printer…”; COL 9 lines 20 – 40: “… selection of points in space, and time, to determine an appropriate size for a graft. The measurements can represent information beyond physical dimensions (e.g., distance, length, widths, area, volume, etc.)… input physical points in the model from which the modeling engine derives measurements (e.g., a distance, and area, a volume… relating to the tissue or prosthetic… a technician can determine the appropriate measurements for the target prosthetic… the manufacturer can then construct the prosthesis according to measurements…”
EXAMINER NOTE: the above citation teaches that the key to success is correct sizing of the prosthesis and teaches to adjust the size, shape, dimensions, volume, of the prosthesis to match the targeted tissue. Shape, size, dimension, length, width, and volume all make obvious a size of a region covering the target tissue.)
Uthgenannt_2010 makes obvious “and an arrangement angle” (par 6: “… implant further includes at least nine parameters adjusted preoperatively to correspond to a specific patient. In one embodiment, the femoral implant includes three patient-specific lengths, three patient specific medial angles and three patient specific lateral angles… based on a three-dimensional image of an anatomy of a patient to match the anatomy of the patient…”; par 7: “… preparing a three-dimensional image of a patient’s joint, selecting a non-custom implant closely matching the joint, and modifying at least siz angles of the implant to be patient-specific…”).
Claim 7. Brown_2016 makes obvious “further comprising: outputting the processed shape template by using a three-dimensional printer after the adjusting” (COL 7 lines 50 – 53: “… output device 460 can include other types of devices including 3D printers capable of “printing” a real prosthesis…”; COL 8 lines 59 -61: “… the modeling engine configuring an output device (e.g., computer, deformable registration imaging system, 3D printer, etc.)…” Figure 4 element 460: “3D Printer”).
Conclusion
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/BRIAN S COOK/Primary Examiner, Art Unit 2187