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 information disclosure statement (IDS) submitted is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The limitations, under their broadest reasonable interpretation, cover mental process (concept performed in a human mind, including as observation, evaluation, judgment, opinion, organizing human activity and mathematical concepts and calculations). The claim(s) recite(s) a method, and computer-readable storage medium configured to preoperatively assessing fracture risk for a patient receiving a prosthetic implant. These claims are directed at collecting patient data, analyzing the data to evaluate fracture risk and reporting the result. This judicial exception is not integrated into a practical application because the steps do not add meaningful limitations to be considered specifically applied to a particular technological problem to be solved .The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the steps of the claimed invention can be done mentally and no additional features in the claims would preclude them from being performed as such except for the generic computer elements at high level of generality (i.e., processor, memory).
According to the USPTO guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that claims 1 and 10 are directed to an abstract idea as shown below:
STEP 1: Do the claims fall within one of the statutory categories? YES. Claim(s) 1, 8 and 16 are directed to a method, a computer readable medium, i.e. a system and an apparatus.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea? YES, the claims are directed toward a mental process (i.e. abstract idea).
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
The method in claim 1 (non-transitory computer-readable medium in claims 8 and apparatus in claim 16) comprise a mental process that can be practicably performed in the human mind (or generic computers or components configured to perform the method) and, therefore, an abstract idea. the claim is directed to collecting patient data, analyzing the data to evaluate fracture risk, and reporting the result. That is an abstract concept of data analysis, evaluation, and reporting, i.e., a diagnostic/assessment process. The claims are directed at collecting patient data, analyzing the data to evaluate fracture risk, and reporting the result. That is an abstract concept of data analysis, evaluation, and reporting, i.e., a diagnostic/assessment process.
Regarding Claims 1, 8 and 16: the method recites the steps (functions) of:
accessing patient medical information, the patient medical information including at least a medical image of the patient, the medical image including at least the bone that will receive the prosthetic implant (mental process including observation and evaluation, and can be done mentally in the human mind; accessing patient medical information… at least a medical image of the patient);
analyzing the medical image to obtain a physical characteristic of the bone (mental process including observation and evaluation, and can be done mentally in the human mind; analyzing medical image…);
determining a fracture risk score based on the physical characteristic of the bone (mental process including observation and evaluation, and can be done mentally in the human mind; determining fracture risk score…)
transmitting a fracture risk summary to a medical professional, the fracture risk summary including at least the fracture risk score (mental process including observation and evaluation, and can be done mentally in the human mind; transmitting/reporting fracture risk summary to a medical processional…);
These limitations, as drafted, are a simple process that, under their broadest reasonable interpretation, covers performance of the limitations in the mind or by a human. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that “can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same). As such, a person could mentally analyze the medical image, determine fracture risk by observation and report the information to a medical professional, either mentally or using a pen and paper. The mere nominal recitation that the various steps are being executed by a device/in a device (e.g. processing unit) does not take the limitations out of the mental process grouping. Thus, the claims recite a mental process.
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? NO, the claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Claims 1, 8 and 16 does/do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. Claim 8 recites the further limitations of:
At least one non-transitory computer-readable medium, the at least one non-transitory computer-readable medium including instructions that when executed by processing circuitry, cause the processing circuitry to perform operations comprising (instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea).
These limitations are recited at a high level of generality (i.e. as general action or change being taken based on the results of the acquiring step) and amount to mere post solution actions, which is a form of insignificant extra-solution activity. Further, the claims are claimed generically and are operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? NO, the claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, the examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Claims 1, 8 and 16 does/do not recite any additional elements that are not well-understood, routine or conventional. The use of a computer to “obtaining, analyzing, determining, and transmitting, etc., as claimed in Claims 1, 8 and 16 is a routine, well-understood and conventional process that is performed by computers.
Thus, since Claims 1, 8 and 16 are: (a) directed toward an abstract idea, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that Claims 1, 8 and 16 are not eligible subject matter under 35 U.S.C 101.
Regarding claims 2 – 7: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. These limitations merely recite the physical characteristics of the bone can be one or more of a cortical thickness, a cortical density, or a bone shape, analyzing the medical image by segmenting the bone and measuring the cortical thickness, cortical density and bone shape, selecting by the medical processional a planned implant type and planned procedure preoperatively and providing a fracture risk summary. These claims are best characterized as a diagnostic/data-analysis method that uses a medical image to calculate and report fracture risk. Because the claims lack a specific technological improvement or particular machine tied to the analysis, they are not eligible subject matter under 35 U.S.C 101.
Regarding claims 9 – 15: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. These limitations merely recite the physical characteristics of the bone can be one or more of a cortical thickness, a cortical density, or a bone shape, analyzing the medical image by segmenting the bone and measuring the cortical thickness, cortical density and bone shape, selecting by the medical processional a planned implant type and planned procedure preoperatively and providing a fracture risk summary. These claims are best characterized as a diagnostic/data-analysis method that uses a medical image to calculate and report fracture risk. Because the claims lack a specific technological improvement or particular machine tied to the analysis, they are not eligible subject matter under 35 U.S.C 101.
Regarding claims 17 – 20: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. These limitations merely recite the physical characteristics of the bone can be one or more of a cortical thickness, a cortical density, or a bone shape, analyzing the medical image by segmenting the bone and measuring the cortical thickness, cortical density and bone shape, selecting by the medical processional a planned implant type and planned procedure preoperatively and providing a fracture risk summary. These claims are best characterized as a diagnostic/data-analysis method that uses a medical image to calculate and report fracture risk. Because the claims lack a specific technological improvement or particular machine tied to the analysis, they are not eligible subject matter under 35 U.S.C 101.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
(g)(1) during the course of an interference conducted under section 135 or section 291, another inventor involved therein establishes, to the extent permitted in section 104, that before such person’s invention thereof the invention was made by such other inventor and not abandoned, suppressed, or concealed, or (2) before such person’s invention thereof, the invention was made in this country by another inventor who had not abandoned, suppressed, or concealed it. In determining priority of invention under this subsection, there shall be considered not only the respective dates of conception and reduction to practice of the invention, but also the reasonable diligence of one who was first to conceive and last to reduce to practice, from a time prior to conception by the other.
A rejection on this statutory basis (35 U.S.C. 102(g) as in force on March 15, 2013) is appropriate in an application or patent that is examined under the first to file provisions of the AIA if it also contains or contained at any time (1) a claim to an invention having an effective filing date as defined in 35 U.S.C. 100(i) that is before March 16, 2013 or (2) a specific reference under 35 U.S.C. 120, 121, or 365(c) to any patent or application that contains or contained at any time such a claim.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1, 8, 13 and 16 are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by Bianco et al. (US 20230169655 A1; hereafter referred to as Bianco).
Regarding Claim 1, Bianco teaches:
A method to preoperatively assess a risk of bone fracture during or after installing a prosthetic implant into a bone of a patient (Bianco, [0007] “described herein relate to various systems, devices, and techniques for providing preoperative planning for orthopedic procedures that include implant insertion, joint arthroplasty (including but not exhaustive of spinal, shoulder, elbow, wrist, hand, fingers, knee, ankle, foot, and toes) fracture fixation, and/or bony fusion (e.g., total hip arthroplasty, joint arthroplasty, and fracture fixation including spine, hip, and wrist fractures and joint fusions, etc.), including providing adjunct automated bone mineral density and fracture risk assessment from digital X-rays”), the method comprising:
accessing patient medical information, the patient medical information including at least a medical image of the patient, the medical image including at least the bone that will receive the prosthetic implant (Bianco, [0028] “the environment 100 may include hospital information system (HIS)/radiology information system (RIS)/electronic patient records (EPR) 140, which may store patient records that may be obtained, utilized, and updated by the orthopedic surgical planning system 120”; [0027] “ the environment 100 may include picture archiving and communication system 130, which may store patient X-ray images that may be obtained and analyzed by the orthopedic surgical planning system 120 to determine a patient's BMD score”);
analyzing the medical image to obtain a physical characteristic of the bone (Bianco, [0030] “, the orthopedic surgical planning system 120 of the cloud analysis server 110 may obtain image data including information relating to cortical bone tissue of at least a part of a first bone, e.g., from the picture archiving an communication system 130. In an example, responsive to a request from one of the clients 150-1, . . . , 150-n to perform a BMD analysis and/or fracture risk assessment for a particular patient having an electronic patient record in the HIS/RIS/EPR 140, the orthopedic surgical planning system 120 may obtain portions of the electronic patient record for the patient from the HIS/RIS/EPR 140 and may obtain X-ray image data for the patient from the picture archiving and communication system 130”);
determining a fracture risk score based on the physical characteristic of the bone (Bianco, [0030] “responsive to a request from one of the clients 150-1, . . . , 150-n to perform a BMD analysis and/or fracture risk assessment for a particular patient having an electronic patient record in the HIS/RIS/EPR 140, the orthopedic surgical planning system 120 may obtain portions of the electronic patient record for the patient from the HIS/RIS/EPR 140 and may obtain X-ray image data for the patient from the picture archiving and communication system 130”; [0033] “ the system may determine a T-score value based on the bone mineral density of the first bone. In implementations, at block 220, the orthopedic surgical planning system 120 of the cloud analysis server 110 may determine a T-score value based on the bone mineral density of the first bone); and
transmitting a fracture risk summary to a medical professional, the fracture risk summary including at least the fracture risk score ([0034] “the system may provide, on a user interface, an output based on the T-score value. In implementations, at block 225, the orthopedic surgical planning system 120 of the cloud analysis server 110 may provide, on a user interface of the client 150-1, . . . , 150-n that requested the BMD analysis and/or fracture risk assessment for the particular patient, an output based on the T-score value determined at block 220”; [0026] “the clients 150-1, . . . , 150-n may be user computing devices associated with an individual or an entity or organization such as a hospital, doctor's office, clinic, etc. or any other organization that uses an orthopedic surgical planning application.. a surgeon may operate an orthopedic surgical planning application to determine a patient's BMD score, to perform a fracture risk assessment, and/or to determine an appropriate treatment and treat a patient”).
Regarding Claim 8, Bianco teaches:
At least one non-transitory computer-readable medium, the at least one non-transitory computer-readable medium including instructions that when executed by processing circuitry (Bianco, [0017] “a non-transitory computer readable storage medium storing instructions executable by one or more processors (e.g., central processing unit(s) (CPU(s)), graphics processing unit(s) (GPU(s)), digital signal processor(s) (DSP(s)), and/or tensor processing unit(s) (TPU(s)) to perform a method such as one or more of the methods described”), cause the processing circuitry to perform operations comprising:
access patient medical information, the patient medical information including at least a medical image of the patient, the medical image including at least the bone that will receive the prosthetic implant (Bianco, [0028] “the environment 100 may include hospital information system (HIS)/radiology information system (RIS)/electronic patient records (EPR) 140, which may store patient records that may be obtained, utilized, and updated by the orthopedic surgical planning system 120”; [0027] “ the environment 100 may include picture archiving and communication system 130, which may store patient X-ray images that may be obtained and analyzed by the orthopedic surgical planning system 120 to determine a patient's BMD score”);
analyze the medical image to obtain a physical characteristic of the bone (Bianco, [0030] “, the orthopedic surgical planning system 120 of the cloud analysis server 110 may obtain image data including information relating to cortical bone tissue of at least a part of a first bone, e.g., from the picture archiving an communication system 130. In an example, responsive to a request from one of the clients 150-1, . . . , 150-n to perform a BMD analysis and/or fracture risk assessment for a particular patient having an electronic patient record in the HIS/RIS/EPR 140, the orthopedic surgical planning system 120 may obtain portions of the electronic patient record for the patient from the HIS/RIS/EPR 140 and may obtain X-ray image data for the patient from the picture archiving and communication system 130”);
determine a fracture risk score based on the physical characteristic of the bone (Bianco, [0030] “responsive to a request from one of the clients 150-1, . . . , 150-n to perform a BMD analysis and/or fracture risk assessment for a particular patient having an electronic patient record in the HIS/RIS/EPR 140, the orthopedic surgical planning system 120 may obtain portions of the electronic patient record for the patient from the HIS/RIS/EPR 140 and may obtain X-ray image data for the patient from the picture archiving and communication system 130”; [0033] “ the system may determine a T-score value based on the bone mineral density of the first bone. In implementations, at block 220, the orthopedic surgical planning system 120 of the cloud analysis server 110 may determine a T-score value based on the bone mineral density of the first bone); and
transmit a fracture risk summary to a medical professional, the fracture risk summary including at least the fracture risk score ([0034] “the system may provide, on a user interface, an output based on the T-score value. In implementations, at block 225, the orthopedic surgical planning system 120 of the cloud analysis server 110 may provide, on a user interface of the client 150-1, . . . , 150-n that requested the BMD analysis and/or fracture risk assessment for the particular patient, an output based on the T-score value determined at block 220”; [0026] “the clients 150-1, . . . , 150-n may be user computing devices associated with an individual or an entity or organization such as a hospital, doctor's office, clinic, etc. or any other organization that uses an orthopedic surgical planning application.. a surgeon may operate an orthopedic surgical planning application to determine a patient's BMD score, to perform a fracture risk assessment, and/or to determine an appropriate treatment and treat a patient”).
Regarding Claim 13, Bianco teaches the at least one non-transitory computer-readable medium of claim 8, wherein the patient medical information comprises at least one of:
a planned implant type, the planned implant type preoperatively selected by the medical professional (Bianco, [0040] “FIG. 2, at block 255, the system may provide, on a user interface, an output based on the recommended surgical implant type. In implementations, at block 255, the orthopedic surgical planning system 120 of the cloud analysis server 110 may provide, on a user interface of the client 150-1, . . . , 150-n that requested the BMD analysis and/or fracture risk assessment for the particular patient, an output based on the recommended surgical implant type determined at block 250”; [0026] “ the clients 150-1, . . . , 150-n may be user computing devices associated with an individual or an entity or organization such as a hospital, doctor's office, clinic, etc. or any other organization that uses an orthopedic surgical planning application. For example, a surgeon may operate an orthopedic surgical planning application to determine a patient's BMD score, to perform a fracture risk assessment, and/or to determine an appropriate treatment and treat a patient”); or
a planned implant procedure, the planned implant procedure preoperatively selected by the medical professional, the planned implant procedure includes one or more of an attachment mechanism to the bone, a maximum force planned for preparation of the bone, or a maximum force planned for impaction of the prosthetic implant within the bone (Bianco, [0042] “In response to determining that a femur or other bone has a T-score that satisfies (e.g., is greater than) both the first threshold and the second threshold (e.g., has a T-score that is greater than −1), the orthopedic surgical planning system 120 may recommend no change to surgical protocol, and standard implant selection. In response to determining that a femur or other bone has a T-score that satisfies the first threshold but does not satisfy the second threshold (e.g., has a T-score that is in the range of −1 to −3), the orthopedic surgical planning system 120 may recommend considering implant selection and prophylactic treatment for osteopenia”).
Regarding Claim 16, Bianco teaches:
A computing apparatus comprising:
a processor (Bianco, [0017] “a client device (e.g., a client device including at least an interface for interfacing with cloud-based component(s)) that includes processor(s) operable to execute stored instructions to perform a method”); and
a memory including instructions that, when executed by the processor (Bianco, [0024] “Any computing devices depicted in FIG. 1 or elsewhere in the figures may include logic such as one or more microprocessors (e.g., central processing units or “CPUs”, graphical processing units or “GPUs”) that execute computer-readable instructions stored in memory”), configure the computing apparatus to:
access patient medical information, the patient medical information including at least a medical image of the patient, the medical image including at least the bone that will receive the prosthetic implant (Bianco, [0028] “the environment 100 may include hospital information system (HIS)/radiology information system (RIS)/electronic patient records (EPR) 140, which may store patient records that may be obtained, utilized, and updated by the orthopedic surgical planning system 120”; [0027] “ the environment 100 may include picture archiving and communication system 130, which may store patient X-ray images that may be obtained and analyzed by the orthopedic surgical planning system 120 to determine a patient's BMD score”);
analyze the medical image to obtain a physical characteristic of the bone (Bianco, [0030] “, the orthopedic surgical planning system 120 of the cloud analysis server 110 may obtain image data including information relating to cortical bone tissue of at least a part of a first bone, e.g., from the picture archiving an communication system 130. In an example, responsive to a request from one of the clients 150-1, . . . , 150-n to perform a BMD analysis and/or fracture risk assessment for a particular patient having an electronic patient record in the HIS/RIS/EPR 140, the orthopedic surgical planning system 120 may obtain portions of the electronic patient record for the patient from the HIS/RIS/EPR 140 and may obtain X-ray image data for the patient from the picture archiving and communication system 130”);
determine a fracture risk score based on the physical characteristic of the bone (Bianco, [0030] “responsive to a request from one of the clients 150-1, . . . , 150-n to perform a BMD analysis and/or fracture risk assessment for a particular patient having an electronic patient record in the HIS/RIS/EPR 140, the orthopedic surgical planning system 120 may obtain portions of the electronic patient record for the patient from the HIS/RIS/EPR 140 and may obtain X-ray image data for the patient from the picture archiving and communication system 130”; [0033] “ the system may determine a T-score value based on the bone mineral density of the first bone. In implementations, at block 220, the orthopedic surgical planning system 120 of the cloud analysis server 110 may determine a T-score value based on the bone mineral density of the first bone); and
transmit a fracture risk summary to a medical professional, the fracture risk summary including at least the fracture risk score ([0034] “the system may provide, on a user interface, an output based on the T-score value. In implementations, at block 225, the orthopedic surgical planning system 120 of the cloud analysis server 110 may provide, on a user interface of the client 150-1, . . . , 150-n that requested the BMD analysis and/or fracture risk assessment for the particular patient, an output based on the T-score value determined at block 220”; [0026] “the clients 150-1, . . . , 150-n may be user computing devices associated with an individual or an entity or organization such as a hospital, doctor's office, clinic, etc. or any other organization that uses an orthopedic surgical planning application.. a surgeon may operate an orthopedic surgical planning application to determine a patient's BMD score, to perform a fracture risk assessment, and/or to determine an appropriate treatment and treat a patient”).
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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 2 – 6, 9 – 12, 14 and 17 – 19 are rejected under 35 U.S.C. 103 as being unpatentable over Bianco et al. (US 20230169655 A1; hereafter referred to as Bianco) in view of Tromans (US 20260228886 A1; hereafter referred to as Tromans).
Regarding Claim 2, Bianco teaches the method of Claim 1, wherein the physical characteristic of the bone can be one or more of:
a cortical thickness (Bianco, [0030] “at block 205, the orthopedic surgical planning system 120 of the cloud analysis server 110 may obtain image data including information relating to cortical bone tissue of at least a part of a first bone, e.g., from the picture archiving an communication system 130”; [0003]);
a cortical density (Bianco, [0035] “referring to FIG. 2, at block 230, the system may determine a Z-score value based on the bone mineral density of the first bone”; Bianco, [0037] “at block 240, the system may determine a fracture risk based on the bone mineral density of the first bone”);
While Bianco teaches the physical characteristics as cortical bone tissue information and bone mineral density), it does not explicitly recite:
a cortical thickness; or
a bone shape;
In the same field of endeavor, Tromans teaches:
a cortical thickness (Tromans, Fig.2, [0123] “the upper femur 106 all trabeculae 115, 116, 117, 118 visible and of normal thickness”; Tromans, [0124] “method of analysing medical images disclosed herein, the ratio of cortical to trabecular bone is used to determine one or more of the at least one bone parameters of bone mineral density (e.g. using cortical ratios), trabecular features (e.g. orientation, length, width, and like characteristics of trabeculae)”); or
a bone shape (Tromans, [0139] “Measurement of the composition of the overall bone structure in terms of the underlying constituent bone types (cortical bone and trabecular bone), relative amounts of the two types, including thickness, density, and morphometry, for example size and shape”);
Bianco and Tromans are considered analogous art as they are reasonably pertinent to the same field of endeavor of medical image analysis. Therefore, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Bianco with the method of Tromans to make the invention that analyzes the cortical thickness and bone shape from the medical images; doing so can efficiently quantify medical images for one or more bone features that contribute to the bones overall biomechanical strength and identify clinically-actionable metrics such as predictions of post-operative outcomes and optimal therapeutic agents (Tromans, [0136]); thus, one of the ordinary skill in the art would have been motivated to combine the references.
Regarding Claim 3, Bianco in view of Tromans teaches the method of Claim 2, wherein analyzing the medical image to obtain the physical characteristic of the bone comprises:
segmenting the bone to obtain a segmented image of the bone from the medical image (Tromans, [0031] “Preferably, after the outer boundary of the cortical bone has been identified, performing a further segmentation step on the outer boundary”; Tromans, [0032] “the method further comprises the step of segmenting the region of cortical bone contained within the identified boundaries, within the region of interest”);
measuring the cortical thickness of the bone using the segmented image of the bone (Tromans, [0139] “Measurement of the composition of the overall bone structure in terms of the underlying constituent bone types (cortical bone and trabecular bone), relative amounts of the two types, including thickness, density, and morphometry, for example size and shape”; Tromans, [0140] “Measurement of the segmentation of the trabeculae within the trabecular bone that contribute to the bones overall biomechanical strength”);
measuring the cortical density of the bone using the segmented image of the bone (Tromans, [0139] “Measurement of the composition of the overall bone structure in terms of the underlying constituent bone types (cortical bone and trabecular bone), relative amounts of the two types, including thickness, density, and morphometry, for example size and shape”; Tromans, [0140] “Measurement of the segmentation of the trabeculae within the trabecular bone that contribute to the bones overall biomechanical strength”); and
determining the bone shape of the bone using the segmented image of the bone (Tromans, [0139] “Measurement of the composition of the overall bone structure in terms of the underlying constituent bone types (cortical bone and trabecular bone), relative amounts of the two types, including thickness, density, and morphometry, for example size and shape”; Tromans, [0140] “Measurement of the segmentation of the trabeculae within the trabecular bone that contribute to the bones overall biomechanical strength”).
The reasons for combining Bianco and Tromans are similar to that stated in the rejection of claim 2. In addition, this same reasoning is pertinent and applicable to the rejections of claims 4, 5 and 6 below.
Regarding Claim 4, Bianco in view of Tromans teaches the method of Claim 3, wherein the patient medical information includes a medical history report, and wherein the medical history report comprises any one of an age of the patient, a medical diagnosis affecting bone health, or an assigned sex of the patient (Tromans, [0133] “the actionable metric may be determined to take account of one or more of: age, sex, ethnicity, height, weight, BMI, smoking status, alcohol use, glucocorticoid use, prior fracture, age at menarche, age at menopause and family history”).
Regarding Claim 5, Bianco in view of Tromans teaches the method of Claim 4, wherein determining a fracture risk comprises:
analyzing the cortical thickness of the bone (Tromans, [0138] “extract and quantify one or more features of bone (including features of bone quantity, quality and morphometry) that are independently associated with bone strength, including: [0139] Measurement of the composition of the overall bone structure in terms of the underlying constituent bone types (cortical bone and trabecular bone), relative amounts of the two types, including thickness, density, and morphometry, for example size and shape”);
analyzing the cortical density of the bone (Bianco, [0035] “referring to FIG. 2, at block 230, the system may determine a Z-score value based on the bone mineral density of the first bone”; Bianco, [0037] “at block 240, the system may determine a fracture risk based on the bone mineral density of the first bone”);
analyzing the bone shape of the bone (Tromans, [0139] “at block 205, the orthopedic surgical planning system 120 of the cloud analysis server 110 may obtain image data including information relating to cortical bone tissue of at least a part of a first bone, e.g., from the picture archiving an communication system 130”); or
analyzing the age of the patient, the medical diagnosis affecting bone health, and the assigned sex (Tromans, [0057] “the system and method of analyzing medical images, the actionable metric may be determined to take account of one or more of: age, sex, ethnicity, height, weight, BMI, smoking status, alcohol use, glucocorticoid use, prior fracture, age at menarche, age at menopause and family history. Further preferably, the actionable metric further comprises a set of individual bone health metrics from imaging examinations acquired at different points in time”).
Regarding Claim 6, Bianco in view of Tromans teaches the method of Claim 4, wherein the patient medical information comprises at least one of:
a planned implant type, the planned implant type preoperatively selected by the medical professional (Bianco, [0040] “FIG. 2, at block 255, the system may provide, on a user interface, an output based on the recommended surgical implant type. In implementations, at block 255, the orthopedic surgical planning system 120 of the cloud analysis server 110 may provide, on a user interface of the client 150-1, . . . , 150-n that requested the BMD analysis and/or fracture risk assessment for the particular patient, an output based on the recommended surgical implant type determined at block 250”; [0026] “ the clients 150-1, . . . , 150-n may be user computing devices associated with an individual or an entity or organization such as a hospital, doctor's office, clinic, etc. or any other organization that uses an orthopedic surgical planning application. For example, a surgeon may operate an orthopedic surgical planning application to determine a patient's BMD score, to perform a fracture risk assessment, and/or to determine an appropriate treatment and treat a patient”); or
a planned implant procedure, the planned implant procedure preoperatively selected by the medical professional, the planned implant procedure includes one or more of an attachment mechanism to the bone, a maximum force planned for preparation of the bone, or a maximum force planned for impaction of the prosthetic implant within the bone (Bianco, [0042] “In response to determining that a femur or other bone has a T-score that satisfies (e.g., is greater than) both the first threshold and the second threshold (e.g., has a T-score that is greater than −1), the orthopedic surgical planning system 120 may recommend no change to surgical protocol, and standard implant selection. In response to determining that a femur or other bone has a T-score that satisfies the first threshold but does not satisfy the second threshold (e.g., has a T-score that is in the range of −1 to −3), the orthopedic surgical planning system 120 may recommend considering implant selection and prophylactic treatment for osteopenia”); and
wherein the fracture risk summary includes a predicted risk level for the planned implant type and the planned implant procedure (Tromans, [0051] “Preferably, the one or more bone parameters are used to determine one or more actionable metrics. The actionable metrics may comprise at least one of: [0052] “an indication of the presence of osteoporosis/osteopenia”; Tromans, [0054] “a risk of fracture in a given period”; Tromans, [0055] “a prediction of intra-operative fracture; [0056] a proposal of a suitable bone implant type including a prediction of surgical outcomes, such as peri-prosthetic fracture and aseptic loosening following insertion of a bone implant”; Tromans, [0136] “the cortical and trabecular features are used in a multi-variate statistical model to predict pathology states and other clinically-actionable metrics, e.g. the prediction of bone disease, peri-prosthetic fracture”; Tromans, [0103] “the classification and its likelihood can be thought of as an outcome prediction and a confidence level of that prediction…The classification and Failure Risk Score can thus be used by the surgeon to support decisions that lead to optimal outcomes and avoid suboptimal outcomes”), and wherein the fracture risk summary includes a surgical plan (Bianco, [0015] “in some implementations, the system may be used as a diagnostic and treatment tool to identify osteoporosis and provide a treatment plan to strengthen bone and/or prevent secondary fractures during or after surgery. In some implementations, the treatment plan may include pre-surgical treatment (e.g., injections to strengthen bone prior to surgery) and post-surgical treatment, as well as a determination of implant type and/or size and/or other treatments or techniques to be used during surgery”; Bianco, [0030] “the orthopedic surgical planning system 120 of the cloud analysis server 110 may obtain image data including information relating to cortical bone tissue of at least a part of a first bone, e.g., from the picture archiving an communication system 130. In an example, responsive to a request from one of the clients 150-1, . . . , 150-n to perform a BMD analysis and/or fracture risk assessment for a particular patient having an electronic patient record in the HIS/RIS/EPR 140, the orthopedic surgical planning system 120 may obtain portions of the electronic patient record for the patient from the HIS/RIS/EPR 140 ).
Regarding Claim 9, Bianco teaches the at least one non-transitory computer-readable medium of claim 8, wherein the physical characteristic of the bone can be one or more of a cortical thickness (Bianco, [0030] “at block 205, the orthopedic surgical planning system 120 of the cloud analysis server 110 may obtain image data including information relating to cortical bone tissue of at least a part of a first bone, e.g., from the picture archiving an communication system 130”; [0003]), a cortical density (Bianco, [0035] Still referring to FIG. 2, at block 230, the system may determine a Z-score value based on the bone mineral density of the first bone. [0037] “at block 240, the system may determine a fracture risk based on the bone mineral density of the first bone”),
While Bianco teaches the physical characteristics as cortical bone tissue information and bone mineral density), it does not explicitly recite:
a cortical thickness, or a bone shape.
In the same field of endeavor, Tromans teaches:
a cortical thickness (Tromans, Fig.2, [0123] “the upper femur 106 all trabeculae 115, 116, 117, 118 visible and of normal thickness”; Tromans, [0124] “method of analysing medical images disclosed herein, the ratio of cortical to trabecular bone is used to determine one or more of the at least one bone parameters of bone mineral density (e.g. using cortical ratios), trabecular features (e.g. orientation, length, width, and like characteristics of trabeculae)”), or a bone shape (Tromans, [0139] “Measurement of the composition of the overall bone structure in terms of the underlying constituent bone types (cortical bone and trabecular bone), relative amounts of the two types, including thickness, density, and morphometry, for example size and shape”).
Bianco and Tromans are considered analogous art as they are reasonably pertinent to the same field of endeavor of medical image analysis. Therefore, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Bianco with the method of Tromans to make the invention that analyzes the cortical thickness and bone shape from the medical images; doing so can efficiently quantify medical images for one or more bone features that contribute to the bones overall biomechanical strength and identify clinically-actionable metrics such as predictions of post-operative outcomes and optimal therapeutic agents (Tromans, [0136]); thus, one of the ordinary skill in the art would have been motivated to combine the references.
Regarding Claim 10, Bianco in view of Tromans teaches the at least one non-transitory computer-readable medium of claim 9, wherein analyzing the medical image to obtain the physical characteristic of the bone comprises:
segment the bone to obtain a segmented image of the bone from the medical image (Tromans, [0031] Preferably, after the outer boundary of the cortical bone has been identified, performing a further segmentation step on the outer boundary”; Tromans, [0032] “the method further comprises the step of segmenting the region of cortical bone contained within the identified boundaries, within the region of interest”);
measure the cortical thickness of the bone using the segmented image of the bone (Tromans, [0139] “Measurement of the composition of the overall bone structure in terms of the underlying constituent bone types (cortical bone and trabecular bone), relative amounts of the two types, including thickness, density, and morphometry, for example size and shape”; Tromans, [0140] “Measurement of the segmentation of the trabeculae within the trabecular bone that contribute to the bones overall biomechanical strength”);
measure the cortical density of the bone using the segmented image of the bone (Tromans, [0139] “Measurement of the composition of the overall bone structure in terms of the underlying constituent bone types (cortical bone and trabecular bone), relative amounts of the two types, including thickness, density, and morphometry, for example size and shape”; Tromans, [0140] “Measurement of the segmentation of the trabeculae within the trabecular bone that contribute to the bones overall biomechanical strength”); and
determine the bone shape of the bone using the segmented image of the bone (Tromans, [0139] “Measurement of the composition of the overall bone structure in terms of the underlying constituent bone types (cortical bone and trabecular bone), relative amounts of the two types, including thickness, density, and morphometry, for example size and shape”; Tromans, [0140] “Measurement of the segmentation of the trabeculae within the trabecular bone that contribute to the bones overall biomechanical strength”).
The reasons for combining Bianco and Tromans are similar to that stated in the rejection of claim 9. In addition, this same reasoning is pertinent and applicable to the rejections of claims 11 and 12 below.
Regarding Claim 11, Bianco in view of Tromans teaches the at least one non-transitory computer-readable medium of claim 10, wherein the patient medical information includes a medical history report, and wherein the medical history report comprises any one of an age of the patient, a medical diagnosis affecting bone health, or an assigned sex of the patient (Tromans, [0133] “the actionable metric may be determined to take account of one or more of: age, sex, ethnicity, height, weight, BMI, smoking status, alcohol use, glucocorticoid use, prior fracture, age at menarche, age at menopause and family history”).
Regarding Claim 12, Bianco in view of Tromans teaches the at least one non-transitory computer-readable medium of claim 11, wherein determining a fracture risk comprises:
analyze the cortical thickness of the bone (Tromans, [0138] “extract and quantify one or more features of bone (including features of bone quantity, quality and morphometry) that are independently associated with bone strength, including: [0139] “Measurement of the composition of the overall bone structure in terms of the underlying constituent bone types (cortical bone and trabecular bone), relative amounts of the two types, including thickness, density, and morphometry, for example size and shape”);
analyze the cortical density of the bone (Bianco, [0035] “referring to FIG. 2, at block 230, the system may determine a Z-score value based on the bone mineral density of the first bone”; Bianco, [0037] “at block 240, the system may determine a fracture risk based on the bone mineral density of the first bone”);
analyze the bone shape of the bone (Tromans, [0139] “at block 205, the orthopedic surgical planning system 120 of the cloud analysis server 110 may obtain image data including information relating to cortical bone tissue of at least a part of a first bone, e.g., from the picture archiving an communication system 130”); and
analyze the age of the patient, the medical diagnosis affecting bone health, and the assigned sex (Tromans, [0057] “the system and method of analyzing medical images, the actionable metric may be determined to take account of one or more of: age, sex, ethnicity, height, weight, BMI, smoking status, alcohol use, glucocorticoid use, prior fracture, age at menarche, age at menopause and family history. Further preferably, the actionable metric further comprises a set of individual bone health metrics from imaging examinations acquired at different points in time”).
Regarding Claim 14, Bianco teaches the at least one non-transitory computer-readable medium of claim 13, wherein the fracture risk summary includes a predicted risk level for the planned implant type and the planned implant procedure, and wherein the fracture risk summary includes a surgical plan (Bianco, [0015] “in some implementations, the system may be used as a diagnostic and treatment tool to identify osteoporosis and provide a treatment plan to strengthen bone and/or prevent secondary fractures during or after surgery. In some implementations, the treatment plan may include pre-surgical treatment (e.g., injections to strengthen bone prior to surgery) and post-surgical treatment, as well as a determination of implant type and/or size and/or other treatments or techniques to be used during surgery”; Bianco, [0030] “the orthopedic surgical planning system 120 of the cloud analysis server 110 may obtain image data including information relating to cortical bone tissue of at least a part of a first bone, e.g., from the picture archiving an communication system 130. In an example, responsive to a request from one of the clients 150-1, . . . , 150-n to perform a BMD analysis and/or fracture risk assessment for a particular patient having an electronic patient record in the HIS/RIS/EPR 140, the orthopedic surgical planning system 120 may obtain portions of the electronic patient record for the patient from the HIS/RIS/EPR 140 ).
However, Bianco does not explicitly recite:
a predicted risk level for the planned implant type and the planned implant procedure,
In the same field of endeavor, Tromans teaches:
a predicted risk level for the planned implant type and the planned implant procedure (Tromans, [0051] “Preferably, the one or more bone parameters are used to determine one or more actionable metrics. The actionable metrics may comprise at least one of: [0052] “an indication of the presence of osteoporosis/osteopenia”; Tromans, [0054] “a risk of fracture in a given period”; Tromans, [0055] “a prediction of intra-operative fracture; [0056] a proposal of a suitable bone implant type including a prediction of surgical outcomes, such as peri-prosthetic fracture and aseptic loosening following insertion of a bone implant”; Tromans, [0136] “the cortical and trabecular features are used in a multi-variate statistical model to predict pathology states and other clinically-actionable metrics, e.g. the prediction of bone disease, peri-prosthetic fracture”; Tromans, [0103] “the classification and its likelihood can be thought of as an outcome prediction and a confidence level of that prediction…The classification and Failure Risk Score can thus be used by the surgeon to support decisions that lead to optimal outcomes and avoid suboptimal outcomes”).
Bianco and Tromans are considered analogous art as they are reasonably pertinent to the same field of endeavor of medical image analysis. Therefore, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Bianco with the method of Tromans to make the invention that includes a predicted risk level for the planned implant type and the planned implant procedure; doing so can efficiently analyze medical images and identify clinically-actionable metrics such as predictions of post-operative outcomes and optimal therapeutic agents (Tromans, [0136]); thus, one of the ordinary skill in the art would have been motivated to combine the references.
Regarding Claim 17, Bianco teaches the, wherein the physical characteristic of the bone can be one or more of a cortical thickness, a cortical density, or a bone shape (Bianco, [0030] “at block 205, the orthopedic surgical planning system 120 of the cloud analysis server 110 may obtain image data including information relating to cortical bone tissue of at least a part of a first bone, e.g., from the picture archiving an communication system 130”; Bianco, [0035] Still referring to FIG. 2, at block 230, the system may determine a Z-score value based on the bone mineral density of the first bone”; Bianco, [0037] “at block 240, the system may determine a fracture risk based on the bone mineral density of the first bone”),
However, Bianco does not explicitly recite:
the physical characteristic of the bone can be one or more of a cortical thickness or a bone shape,
wherein the patient medical information includes a medical history report of the patient, and wherein the medical history report comprises any one of an age of the patient, a medical diagnosis affect the bone of the patient, or an assigned sex of the patient, wherein analyzing the medical image to obtain the physical characteristic of the bone comprises the instructions configuring the computing apparatus to perform any one of these operations:
segment the bone to obtain a segmented image of the bone from the medical image;
measure the cortical thickness of the bone using the segmented image of the bone;
measure the cortical density of the bone using the segmented image of the bone; or
determine the bone shape of the bone using the segmented image of the bone.
In the same field of endeavor, Tromans teaches:
a cortical thickness (Tromans, Fig.2, [0123] “the upper femur 106 all trabeculae 115, 116, 117, 118 visible and of normal thickness”; Tromans, [0124] “method of analyzing medical images disclosed herein, the ratio of cortical to trabecular bone is used to determine one or more of the at least one bone parameters of bone mineral density (e.g. using cortical ratios), trabecular features (e.g. orientation, length, width, and like characteristics of trabeculae)”), or
a bone shape (Tromans, [0139] “Measurement of the composition of the overall bone structure in terms of the underlying constituent bone types (cortical bone and trabecular bone), relative amounts of the two types, including thickness, density, and morphometry, for example size and shape”),
wherein the patient medical information includes a medical history report of the patient, and wherein the medical history report comprises any one of an age of the patient, a medical diagnosis affect the bone of the patient, or an assigned sex of the patient, wherein analyzing the medical image to obtain the physical characteristic of the bone (Tromans, [0133] “the actionable metric may be determined to take account of one or more of: age, sex, ethnicity, height, weight, BMI, smoking status, alcohol use, glucocorticoid use, prior fracture, age at menarche, age at menopause and family history”) comprises the instructions configuring the computing apparatus to perform any one of these operations:
segment the bone to obtain a segmented image of the bone from the medical image (Tromans, [0031] “Preferably, after the outer boundary of the cortical bone has been identified, performing a further segmentation step on the outer boundary”; Tromans, [0032] “the method further comprises the step of segmenting the region of cortical bone contained within the identified boundaries, within the region of interest”);
measure the cortical thickness of the bone using the segmented image of the bone (Tromans, [0139] “Measurement of the composition of the overall bone structure in terms of the underlying constituent bone types (cortical bone and trabecular bone), relative amounts of the two types, including thickness, density, and morphometry, for example size and shape”; Tromans, [0140] “Measurement of the segmentation of the trabeculae within the trabecular bone that contribute to the bones overall biomechanical strength”);
measure the cortical density of the bone using the segmented image of the bone (Tromans, [0139] “Measurement of the composition of the overall bone structure in terms of the underlying constituent bone types (cortical bone and trabecular bone), relative amounts of the two types, including thickness, density, and morphometry, for example size and shape”; Tromans, [0140] “Measurement of the segmentation of the trabeculae within the trabecular bone that contribute to the bones overall biomechanical strength”); and
determine the bone shape of the bone using the segmented image of the bone (Tromans, [0139] “Measurement of the composition of the overall bone structure in terms of the underlying constituent bone types (cortical bone and trabecular bone), relative amounts of the two types, including thickness, density, and morphometry, for example size and shape”; Tromans, [0140] “Measurement of the segmentation of the trabeculae within the trabecular bone that contribute to the bones overall biomechanical strength”).
Bianco and Tromans are considered analogous art as they are reasonably pertinent to the same field of endeavor of medical image analysis. Therefore, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Bianco with the method of Tromans to make the invention that analyzes the cortical thickness and bone shape from the medical images; doing so can efficiently quantify medical images for one or more bone features that contribute to the bones overall biomechanical strength and identify clinically-actionable metrics such as predictions of post-operative outcomes and optimal therapeutic agents (Tromans, [0136]); thus, one of the ordinary skill in the art would have been motivated to combine the references.
Regarding Claim 18, Bianco in view of Tromans teaches the computing apparatus of claim 17, wherein determining a fracture risk comprises:
analyze the cortical thickness of the bone (Tromans, [0138] extract and quantify one or more features of bone (including features of bone quantity, quality and morphometry) that are independently associated with bone strength, including: [0139] Measurement of the composition of the overall bone structure in terms of the underlying constituent bone types (cortical bone and trabecular bone), relative amounts of the two types, including thickness, density, and morphometry, for example size and shape”);
analyze the cortical density of the bone (Bianco, [0035] “referring to FIG. 2, at block 230, the system may determine a Z-score value based on the bone mineral density of the first bone”; Bianco, [0037] “at block 240, the system may determine a fracture risk based on the bone mineral density of the first bone”);
analyze the bone shape of the bone (Tromans, [0139] “at block 205, the orthopedic surgical planning system 120 of the cloud analysis server 110 may obtain image data including information relating to cortical bone tissue of at least a part of a first bone, e.g., from the picture archiving an communication system 130”); and
analyze the age of the patient, the medical diagnosis affecting bone health, and the assigned sex (Tromans, [0057] “the system and method of analyzing medical images, the actionable metric may be determined to take account of one or more of: age, sex, ethnicity, height, weight, BMI, smoking status, alcohol use, glucocorticoid use, prior fracture, age at menarche, age at menopause and family history. Further preferably, the actionable metric further comprises a set of individual bone health metrics from imaging examinations acquired at different points in time”).
The reasons for combining Bianco and Tromans are similar to that stated in the rejection of claim 17.
Regarding Claim 19, Bianco teaches the computing apparatus of claim 16, wherein the patient medical information comprises at least one of:
a planned implant type, the planned implant type preoperatively selected by the medical professional (Bianco, [0040] “FIG. 2, at block 255, the system may provide, on a user interface, an output based on the recommended surgical implant type. In implementations, at block 255, the orthopedic surgical planning system 120 of the cloud analysis server 110 may provide, on a user interface of the client 150-1, . . . , 150-n that requested the BMD analysis and/or fracture risk assessment for the particular patient, an output based on the recommended surgical implant type determined at block 250”; [0026] “ the clients 150-1, . . . , 150-n may be user computing devices associated with an individual or an entity or organization such as a hospital, doctor's office, clinic, etc. or any other organization that uses an orthopedic surgical planning application. For example, a surgeon may operate an orthopedic surgical planning application to determine a patient's BMD score, to perform a fracture risk assessment, and/or to determine an appropriate treatment and treat a patient”); or
a planned implant procedure, the planned implant procedure preoperatively selected by the medical professional, the planned implant procedure includes one or more of an attachment mechanism to the bone, a maximum force planned for preparation of the bone, or a maximum force planned for impaction of the prosthetic implant within the bone (Bianco, [0042] “In response to determining that a femur or other bone has a T-score that satisfies (e.g., is greater than) both the first threshold and the second threshold (e.g., has a T-score that is greater than −1), the orthopedic surgical planning system 120 may recommend no change to surgical protocol, and standard implant selection. In response to determining that a femur or other bone has a T-score that satisfies the first threshold but does not satisfy the second threshold (e.g., has a T-score that is in the range of −1 to −3), the orthopedic surgical planning system 120 may recommend considering implant selection and prophylactic treatment for osteopenia”); and
wherein the fracture risk summary includes a predicted risk level for the planned implant type and the planned implant procedure, and wherein the fracture risk summary includes a surgical plan (Bianco, [0015] “in some implementations, the system may be used as a diagnostic and treatment tool to identify osteoporosis and provide a treatment plan to strengthen bone and/or prevent secondary fractures during or after surgery. In some implementations, the treatment plan may include pre-surgical treatment (e.g., injections to strengthen bone prior to surgery) and post-surgical treatment, as well as a determination of implant type and/or size and/or other treatments or techniques to be used during surgery”; Bianco, [0030] “the orthopedic surgical planning system 120 of the cloud analysis server 110 may obtain image data including information relating to cortical bone tissue of at least a part of a first bone, e.g., from the picture archiving an communication system 130. In an example, responsive to a request from one of the clients 150-1, . . . , 150-n to perform a BMD analysis and/or fracture risk assessment for a particular patient having an electronic patient record in the HIS/RIS/EPR 140, the orthopedic surgical planning system 120 may obtain portions of the electronic patient record for the patient from the HIS/RIS/EPR 140 ).
However, Bianco does not explicitly recite:
a predicted risk level for the planned implant type and the planned implant procedure,
In the same field of endeavor, Tromans teaches:
a predicted risk level for the planned implant type and the planned implant procedure (Tromans, [0051] “Preferably, the one or more bone parameters are used to determine one or more actionable metrics. The actionable metrics may comprise at least one of: [0052] “an indication of the presence of osteoporosis/osteopenia”; Tromans, [0054] “a risk of fracture in a given period”; Tromans, [0055] “a prediction of intra-operative fracture; [0056] a proposal of a suitable bone implant type including a prediction of surgical outcomes, such as peri-prosthetic fracture and aseptic loosening following insertion of a bone implant”; Tromans, [0136] “the cortical and trabecular features are used in a multi-variate statistical model to predict pathology states and other clinically-actionable metrics, e.g. the prediction of bone disease, peri-prosthetic fracture”).
Bianco and Tromans are considered analogous art as they are reasonably pertinent to the same field of endeavor of medical image analysis. Therefore, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Bianco with the method of Tromans to make the invention that includes a predicted risk level for the planned implant type and the planned implant procedure; doing so can efficiently analyze medical images and identify clinically-actionable metrics such as predictions of post-operative outcomes and optimal therapeutic agents (Tromans, [0136]); thus, one of the ordinary skill in the art would have been motivated to combine the references.
Claims 7, 15 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Bianco et al. (US 20230169655 A1; hereafter referred to as Bianco) in view of Tromans (US 20260228886 A1; hereafter referred to as Tromans) further in view of Liarno et al. (US 20230377714 A1; hereafter referred to as Liarno).
Regarding Claim 7, Bianco in view of Tromans teaches the method of claim 6, wherein upon receiving a negative signal indicative of the medical professional rejecting the surgical plan, the method comprises:
identifying one or more alternative implant types or one or more alternative implant procedures for use in the bone of the patient (Bianco, [0010] “By obtaining patient-specific osteoporosis related fracture risk assessment prior to the actual surgery, the surgeon can assess the need to alter surgical technique, implant selection, and post-operative patient management and rehabilitation based on the severity of the patient's BMD status”; Bianco, [0039] “the system may determine a recommended surgical implant type based on the bone mineral density of the first bone or the T-score value”);
determining an updated risk summary, the updated risk summary including an updated predicted risk score for each combination of any of the one or more alternative implant types and any of the one or more alternative implant procedures (Bianco, [0026] “a surgeon may operate an orthopedic surgical planning application to determine a patient's BMD score, to perform a fracture risk assessment, and/or to determine an appropriate treatment and treat a patient”; Bianco, [0028] “the environment 100 may include hospital information system (HIS)/radiology information system (RIS)/electronic patient records (EPR) 140, which may store patient records that may be obtained, utilized, and updated by the orthopedic surgical planning system 120”; [0039] “the system may determine a recommended surgical implant type based on the bone mineral density of the first bone or the T-score value. In implementations, at block 250, the orthopedic surgical planning system 120 of the cloud analysis server 110 may determine a recommended surgical implant type based on the bone mineral density of the first bone determined based on the output of the trained machine learning model at block 215 or the T-score value determined at block 220”); and
transmitting an updated surgical plan based on a combination of the one or more alternative implant types and the one or more alternative implant procedures having a lowest risk score (Bianco, [0028] “the environment 100 may include hospital information system (HIS)/radiology information system (RIS)/electronic patient records (EPR) 140, which may store patient records that may be obtained, utilized, and updated by the orthopedic surgical planning system 120. The HIS/RIS/EPR 140 may be implemented using one or more server computing devices that form what is sometimes referred to as a “cloud infrastructure,” although this is not required. The orthopedic surgical planning system 120 and the HIS/RIS/EPR 140 may be in communication via the computer network 160”).
However, Bianco in view of Tromans does not explicitly recite:
the updated risk summary including an updated predicted risk score for each combination of any of the one or more alternative implant types; and
updated surgical plan based on a combination of the one or more alternative implant types and the one or more alternative implant procedures having a lowest risk score.
In the same field of endeavor, Liarno teaches:
the updated risk summary including an updated predicted risk score for each combination of any of the one or more alternative implant types (Liarno, [0096] “The procedure plan 7020 may also include predictive or target outcomes and/or parameters, such as target postoperative range of motion and alignment parameters, target fall risk or fracture scores, activity quality scores, and joint stiffness scores”; Liarno, [0156] “Medical history 3120 may include updated and/or new medical history 3120 (as compared to preoperative medical history 1030) and may include both immediate and long term information such as new utilization of orthotics, care information in a supervised environment such as a skilled nursing facility or SNF, infection information, etc.”) and
updated surgical plan based on a combination of the one or more alternative implant types and the one or more alternative implant procedures having a lowest risk score (Liarno, [0100] “Like the prehabilitation plan 7010 and procedure plan 7020, the postoperative plan 7030 may be based on other preoperative outputs 7000. For example, the postoperative plan 7030 may include an exercise program configured to target muscles based on the patient's lifestyle 1020, the fall risk score 7050, and/or the fracture score 7140….The procedure plan 7020 may be updated and/or modified based on intraoperative information 2000 and postoperative information 3000”; Liarno, [0102] “the fall risk score 7050 may be calculated on a mobile device 108, be updated based on information sensed by the mobile device 108, and be displayed on the mobile device 108 (e.g., in a fall risk tracking app)…. A higher fall risk score 7050 may indicate a higher likelihood that a patient will fall or lose balance, or a higher frailty of the patient”; Liarno, [0142] “The intraoperative outputs 8000 may include an updated or new procedure plan 8020, an updated or new postoperative plan 8030, an updated or new bone density score 8040, an updated or new fall risk or stability score 8050, an updated or new activity quality score 8060, an updated or new joint stiffness score 8070, a patient readiness score 8080, an updated or new B-score 8100, and an updated or new fracture risk score 8140”; Liarno, [0123], [0167]).
Bianco, Tromans and Liarno are considered analogous art as they are reasonably pertinent to the same field of endeavor of medical image analysis. Therefore, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Bianco with the method of Tromans to make the invention that includes updated predicted risk score for each combination of any of the one or more alternative implant types and updated surgical plan based on the alternative implant procedures having a lowest risk score; doing so can efficiently analyze medical images and assist in surgery as desired (Liarno [0003]); thus, one of the ordinary skill in the art would have been motivated to combine the references.
Regarding Claim 15, Bianco in view of Tromans teaches the at least one non-transitory computer-readable medium of claim 14, wherein upon receiving a negative signal indicative of the medical professional reject the surgical plan, the instructions cause the processing circuitry to perform operations comprising:
identify one or more alternative implant types for use in the bone of the patient (Bianco, [0010] “By obtaining patient-specific osteoporosis related fracture risk assessment prior to the actual surgery, the surgeon can assess the need to alter surgical technique, implant selection, and post-operative patient management and rehabilitation based on the severity of the patient's BMD status”; Bianco, [0039] “the system may determine a recommended surgical implant type based on the bone mineral density of the first bone or the T-score value”);
identify one or more alternative implant procedures for use in the bone of the patient (Bianco, [0026] “a surgeon may operate an orthopedic surgical planning application to determine a patient's BMD score, to perform a fracture risk assessment, and/or to determine an appropriate treatment and treat a patient”; Bianco, [0041] “the system may determine a recommended treatment based on the bone mineral density of the first bone or the T-score value”);
determine an updated risk summary, the updated risk summary including an updated predicted risk score for each combination of any of the one or more alternative implant types and any of the one or more alternative implant procedures (Bianco, [0026] “a surgeon may operate an orthopedic surgical planning application to determine a patient's BMD score, to perform a fracture risk assessment, and/or to determine an appropriate treatment and treat a patient”; Bianco, [0028] “the environment 100 may include hospital information system (HIS)/radiology information system (RIS)/electronic patient records (EPR) 140, which may store patient records that may be obtained, utilized, and updated by the orthopedic surgical planning system 120”; [0039] “the system may determine a recommended surgical implant type based on the bone mineral density of the first bone or the T-score value. In implementations, at block 250, the orthopedic surgical planning system 120 of the cloud analysis server 110 may determine a recommended surgical implant type based on the bone mineral density of the first bone determined based on the output of the trained machine learning model at block 215 or the T-score value determined at block 220”); and
transmit an updated surgical plan based on a combination of the one or more alternative implant types and the one or more alternative implant procedures having a lowest risk score (Bianco, [0028] “the environment 100 may include hospital information system (HIS)/radiology information system (RIS)/electronic patient records (EPR) 140, which may store patient records that may be obtained, utilized, and updated by the orthopedic surgical planning system 120. The HIS/RIS/EPR 140 may be implemented using one or more server computing devices that form what is sometimes referred to as a “cloud infrastructure,” although this is not required. The orthopedic surgical planning system 120 and the HIS/RIS/EPR 140 may be in communication via the computer network 160”).
However, Bianco in view of Tromans does not explicitly recite:
the updated risk summary including an updated predicted risk score for each combination of any of the one or more alternative implant types; and
updated surgical plan based on a combination of the one or more alternative implant types and the one or more alternative implant procedures having a lowest risk score.
In the same field of endeavor, Liarno teaches:
the updated risk summary including an updated predicted risk score for each combination of any of the one or more alternative implant types (Liarno, [0096] “The procedure plan 7020 may also include predictive or target outcomes and/or parameters, such as target postoperative range of motion and alignment parameters, target fall risk or fracture scores, activity quality scores, and joint stiffness scores”; Liarno, [0156] “Medical history 3120 may include updated and/or new medical history 3120 (as compared to preoperative medical history 1030) and may include both immediate and long term information such as new utilization of orthotics, care information in a supervised environment such as a skilled nursing facility or SNF, infection information, etc.”) and
updated surgical plan based on a combination of the one or more alternative implant types and the one or more alternative implant procedures having a lowest risk score (Liarno, [0100] “Like the prehabilitation plan 7010 and procedure plan 7020, the postoperative plan 7030 may be based on other preoperative outputs 7000. For example, the postoperative plan 7030 may include an exercise program configured to target muscles based on the patient's lifestyle 1020, the fall risk score 7050, and/or the fracture score 7140….The procedure plan 7020 may be updated and/or modified based on intraoperative information 2000 and postoperative information 3000”; Liarno, [0102] “the fall risk score 7050 may be calculated on a mobile device 108, be updated based on information sensed by the mobile device 108, and be displayed on the mobile device 108 (e.g., in a fall risk tracking app)…. A higher fall risk score 7050 may indicate a higher likelihood that a patient will fall or lose balance, or a higher frailty of the patient”; Liarno, [0142] “The intraoperative outputs 8000 may include an updated or new procedure plan 8020, an updated or new postoperative plan 8030, an updated or new bone density score 8040, an updated or new fall risk or stability score 8050, an updated or new activity quality score 8060, an updated or new joint stiffness score 8070, a patient readiness score 8080, an updated or new B-score 8100, and an updated or new fracture risk score 8140”; Liarno, [0123], [0167]).
Bianco, Tromans and Liarno are considered analogous art as they are reasonably pertinent to the same field of endeavor of medical image analysis. Therefore, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Bianco with the method of Tromans to make the invention that includes updated predicted risk score for each combination of any of the one or more alternative implant types and updated surgical plan based on the alternative implant procedures having a lowest risk score; doing so can efficiently analyze medical images and assist in surgery as desired (Liarno [0003]); thus, one of the ordinary skill in the art would have been motivated to combine the references.
Regarding Claim 20, Bianco in view of Tromans teaches the computing apparatus of claim 19, wherein upon receiving a negative signal indicative of the medical professional rejecting the surgical plan, the instructions configure the computing apparatus to perform operations comprising:
identify one or more alternative implant types for use in the bone of the patient (Bianco, [0010] “By obtaining patient-specific osteoporosis related fracture risk assessment prior to the actual surgery, the surgeon can assess the need to alter surgical technique, implant selection, and post-operative patient management and rehabilitation based on the severity of the patient's BMD status”; Bianco, [0039] “the system may determine a recommended surgical implant type based on the bone mineral density of the first bone or the T-score value”);
identify one or more alternative implant procedures for use in the bone of the patient (Bianco, [0026] “a surgeon may operate an orthopedic surgical planning application to determine a patient's BMD score, to perform a fracture risk assessment, and/or to determine an appropriate treatment and treat a patient”; Bianco, [0041] “the system may determine a recommended treatment based on the bone mineral density of the first bone or the T-score value”);
determine an updated risk summary, the updated risk summary including an updated predicted risk score for each combination of any of the one or more alternative implant types and any of the one or more alternative implant procedures (Bianco, [0026] “a surgeon may operate an orthopedic surgical planning application to determine a patient's BMD score, to perform a fracture risk assessment, and/or to determine an appropriate treatment and treat a patient”; Bianco, [0028] “the environment 100 may include hospital information system (HIS)/radiology information system (RIS)/electronic patient records (EPR) 140, which may store patient records that may be obtained, utilized, and updated by the orthopedic surgical planning system 120”; [0039] “the system may determine a recommended surgical implant type based on the bone mineral density of the first bone or the T-score value. In implementations, at block 250, the orthopedic surgical planning system 120 of the cloud analysis server 110 may determine a recommended surgical implant type based on the bone mineral density of the first bone determined based on the output of the trained machine learning model at block 215 or the T-score value determined at block 220”); and
transmit an updated surgical plan based on a combination of the one or more alternative implant types and the one or more alternative implant procedures having a lowest risk score (Bianco, [0028] “the environment 100 may include hospital information system (HIS)/radiology information system (RIS)/electronic patient records (EPR) 140, which may store patient records that may be obtained, utilized, and updated by the orthopedic surgical planning system 120. The HIS/RIS/EPR 140 may be implemented using one or more server computing devices that form what is sometimes referred to as a “cloud infrastructure,” although this is not required. The orthopedic surgical planning system 120 and the HIS/RIS/EPR 140 may be in communication via the computer network 160”).
However, Bianco in view of Tromans does not explicitly recite:
the updated risk summary including an updated predicted risk score for each combination of any of the one or more alternative implant types; and
updated surgical plan based on a combination of the one or more alternative implant types and the one or more alternative implant procedures having a lowest risk score.
In the same field of endeavor, Liarno teaches:
the updated risk summary including an updated predicted risk score for each combination of any of the one or more alternative implant types (Liarno, [0096] “The procedure plan 7020 may also include predictive or target outcomes and/or parameters, such as target postoperative range of motion and alignment parameters, target fall risk or fracture scores, activity quality scores, and joint stiffness scores”; Liarno, [0156] “Medical history 3120 may include updated and/or new medical history 3120 (as compared to preoperative medical history 1030) and may include both immediate and long term information such as new utilization of orthotics, care information in a supervised environment such as a skilled nursing facility or SNF, infection information, etc.”) and
updated surgical plan based on a combination of the one or more alternative implant types and the one or more alternative implant procedures having a lowest risk score (Liarno, [0100] “Like the prehabilitation plan 7010 and procedure plan 7020, the postoperative plan 7030 may be based on other preoperative outputs 7000. For example, the postoperative plan 7030 may include an exercise program configured to target muscles based on the patient's lifestyle 1020, the fall risk score 7050, and/or the fracture score 7140….The procedure plan 7020 may be updated and/or modified based on intraoperative information 2000 and postoperative information 3000”; Liarno, [0102] “the fall risk score 7050 may be calculated on a mobile device 108, be updated based on information sensed by the mobile device 108, and be displayed on the mobile device 108 (e.g., in a fall risk tracking app)…. A higher fall risk score 7050 may indicate a higher likelihood that a patient will fall or lose balance, or a higher frailty of the patient”; Liarno, [0142] “The intraoperative outputs 8000 may include an updated or new procedure plan 8020, an updated or new postoperative plan 8030, an updated or new bone density score 8040, an updated or new fall risk or stability score 8050, an updated or new activity quality score 8060, an updated or new joint stiffness score 8070, a patient readiness score 8080, an updated or new B-score 8100, and an updated or new fracture risk score 8140”; Liarno, [0123], [0167]).
Bianco, Tromans and Liarno are considered analogous art as they are reasonably pertinent to the same field of endeavor of medical image analysis. Therefore, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Bianco with the method of Tromans to make the invention that includes updated predicted risk score for each combination of any of the one or more alternative implant types and updated surgical plan based on the alternative implant procedures having a lowest risk score; doing so can efficiently analyze medical images and assist in surgery as desired (Liarno [0003]); thus, one of the ordinary skill in the art would have been motivated to combine the references.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20230157765 A1 ARTIFICIAL INTELLIGENCE INTRA-OPERATIVE SURGICAL GUIDANCE SYSTEM The inventive subject matter is directed to an artificial intelligence intra-operative surgical guidance system and method of use. The artificial intelligence intra-operative surgical guidance system is made of a computer executing one or more automated artificial intelligence models trained on data layer datasets collections to calculate surgical decision risks, and provide intra-operative surgical guidance; and a display configured to provide visual guidance to a user.
US 20220047400 A1 BONE DENSITY MODELING AND ORTHOPEDIC SURGICAL PLANNING SYSTEM A surgical planning system for use in surgical procedures to repair an anatomy of interest includes a preplanning system to generate a virtual surgical plan and a mixed reality system that includes a visualization device wearable by a user to view the virtual surgical plan projected in a real environment. The virtual surgical plan includes a 3D virtual model of the anatomy of interest. When wearing the visualization device, the user can align the 3D virtual model with the real anatomy of interest, thereby achieving a registration between details of the virtual surgical plan and the real anatomy of interest. The registration enables a surgeon to implement the virtual surgical plan on the real anatomy of interest without the use of tracking markers.
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VAISALI RAO. KOPPOLU
Examiner
Art Unit 2664
/VAISALI RAO KOPPOLU/Examiner of Art Unit 2664
Prosecution Insights