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 .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. AU2020900651, filed on 03/04/2020.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 09/06/2022 is being considered by the examiner. The submission is in compliance with the provisions of 37 CFR 1.97.
Specification
The disclosure is objected to because of the following informalities:
In paragraph [0048], lines 5 and 6, reference character 406 is used to refer to both “the implant component” and “the patient’s pelvis.” The patient’s pelvis was previously referenced as character 402 in line 2 of paragraph [0039].
In paragraph [0085], lines 2 and 7, reference character 406 is used to refer to both “the patient’s pelvis” and “the acetabular component.” The patient’s pelvis was previously referenced as character 402 in line 2 of paragraph [0039].
In paragraph [0130], line 26, “indication 9000” should read “indication 900.”
Appropriate correction is required.
Status of Claims
Claims 1-7, 9-10, 13-14, 16-21, and 24-26 are pending.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 26 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter as follows.
Claim 26 is directed to “a computer-readable storage medium.” The specification only states that the computer readable medium may be non-transitory and provides examples (Paragraphs [0045], [0060], and [0185] of Applicant’s specification), however, Applicant does not provide an assertive disavowal of the computer-readable medium being “non-transitory.” The broadest reasonable interpretation of a claim drawn to a “computer-readable storage medium” typically covers forms of non-transitory tangible media and transitory propagating signals per se in view of the ordinary and customary meaning of computer readable media, particularly when the specification is silent. See Subject Matter Eligibility of Computer Readable Media, 1351 OG 212 (26 Jan 2010). See MPEP 2111.01. Signals are nothing but the physical characteristics of a form of energy, and as such is non-statutory phenomena. See, e.g., In re Nuitjen, 500 F. 3d 1346, 1357 (Fed. Cir. 2007)(slip. op. at 18)(“A transitory, propagating signal like Nuitjen’s is not a process, machine, manufacture, or composition of matter.’ … Thus, such a signal cannot be patentable subject matter.”). Accordingly, Claim 26 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. It is suggested that Applicant amend the claim by inserting the term “non-transitory” before “computer-readable” in the preamble of the claim.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 4-6, 9, 13-14, 16, 19-21, and 24-26 are rejected under 35 U.S.C. 103 as being unpatentable over Boddington et al. (U.S. Patent Pub. No. 2022/0265233 A1, hereafter referred to as Boddington) in view of Hughes et al. (U.S. Patent Pub. No. 2013/0144392, hereafter referred to as Hughes).
Regarding Claim 1, Boddington teaches an intraoperative guidance system for total joint replacement of a joint of a patient by a surgeon (Paragraph [0004], Boddington teaches an intraoperative surgical guidance system in joint replacements and for providing recommendations to support the decision-making process of a surgeon to predict optimized implant and subject outcomes.), the guidance system comprising: an X-ray imaging device for single-shot application of X-ray radiation to the joint and for detecting X-ray radiation to create a digital image of the joint and an implant component during a total joint replacement surgery (Paragraphs [0063], [0075], [0187], Fig. 1A, Fig. 26B, Boddington teaches an imaging system (110), which receives subject image data such as radiographic images of the subject’s anatomy. Fig. 26B shows an intraoperative image of the anteroposterior pelvis along with an implant cup and stem.);
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and a computer system configured to: store a digital three-dimensional model of the joint (Paragraph [0099], Fig. 16, Boddington teaches 3D Shape Modeling Module for computing three-dimensional anatomical shape information. Fig. 16, as seen below, shows the output of the Shape Modeling Module.);
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receive the digital image of the joint and the implant component during the total joint replacement surgery (Fig. 27A, Paragraphs [0119-121], [0188], Boddington teaches preparing and positioning the patient for the surgery in a standard manner as indicated for the specific procedure, for example, a joint replacement surgery. A preoperative image is imported and a grid template is superimposed over the patient’s anatomical image. The grid templates contain may contain lines, geometrical patterns, numbers, letters, complex patterns of multiple lines and geometries corresponding to surgical variables and can be pre-designed or constructed intraoperatively. Next, the procedure specific information is extracted from the pre-operative image/data and mapped into the live intraoperative images. Fig. 27A, shown below, depicts use of a grid template in a hip total arthroplasty (THA). For example, if teardrops, symphysis pubis, ipsilateral teardrop, implant (cup) and stem (implant) and femoral head implant are detected, a functional pelvis grid/template is registered to the image.);
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and provide an indication to the surgeon of the intraoperative simulated performance metric as an assessment of a current placement of the implant component (Paragraph [0148], Boddington teaches providing surgical guidance via outputs such as implant selection recommendations, implant placement, performance predictions, probability of good outcomes, and failure risk scores. The surgeon is provided with a Failure Risk Score as a confidence percentage recommendation of a suboptimal or optimal performance metric. The output is presented to the user in the form of intelligent predictors and scores to support decisions encountered in a real-time surgical event.).
Boddington does not explicitly disclose perform(ing) registration between the digital image and the digital three-dimensional model to determine a placement of the implant component in the digital image in relation to the digital three-dimensional model; and determin
Hughes is in the same field of art of intra-operative implant placement optimization for joint arthroplasty procedures. Further, Hughes teaches perform(ing) registration between the digital image and the digital three-dimensional model to determine a placement of the implant component in the digital image in relation to the digital three-dimensional model (Paragraphs [0027-28], Fig. 4, Hughes teaches processing the image data to create a three-dimensional computer model of the knee joint incorporating the scanned image data. Processing the raw image data may include employing smoothing functions, interpolations, or other data processing techniques to coordinate the image data with the computer model of the knee joint. Models of the femur, tibia, and implant components can be combined to create a 3D model of the joint with simulated implant components (see arrow) as shown in Fig. 4 below. The Examiner interprets coordinating the 2D image data with the 3D computer model of the knee joint by employing smoothing functions, interpolations, etc., to be synonymous to performing registration between the 2D image and 3D model.);
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determin(Paragraph [0029], Hughes teaches using a simulation software to virtually model the movement of the knee in conjunction with implant components to analyze attributes of the implant and articular surfaces such as proper tibial rotation, femoral rollback, patellar alignment, and quadriceps efficiency. A wide range of parameters can be experimentally viewed and tested using the computer-generated simulation. The Examiner interprets proper tibial rotation, femoral rollback, patellar alignment, and quadriceps efficiency to be simulated intraoperative performance metrics.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Boddington by coordinating the 2D captured image of the joint to a three-dimensional (3D) model to perform proper placement of an implant component in the 3D model and analyze joint performance by simulating a variety of real-world movements such as tibial rotation, femoral rollback, patellar alignment, quadriceps efficiency, or alternative performance metric, that is taught by Hughes to make the invention that identifies the implant configuration that achieves a desired performance metric; thus, one of ordinary skill in the art would have been motivated to combine the references to enable the surgeon to select an optimal implant and determine the ideal positioning and orientation of the selected implant relative to the anatomical features in the intraoperative image (Abstract, Hughes).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
In regards to Claim 4, Boddington in view of Hughes discloses the system of claim 1, wherein the computer system is configured to update the digital three-dimensional model based on the determined placement of the implant component in the digital image in relation to the digital three-dimensional model, thereby determining an updated digital three-dimensional model (Paragraph [0032], Fig. 2, reference characters 210, 212, Hughes teaches selecting an optimal implant and creating a simulated 3D representation of the bone surfaces comprising the joint and selected implant components. Next, in step 212, ideal positioning and orientation of the selected implant component relative to the scanned anatomical features is determined.).
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In regards to Claim 5, Boddington in view of Hughes teaches the system of claim 4, wherein the intraoperative simulated performance metric is associated with the updated three-dimensional model (Paragraph [0032], Hughes teaches moving the three-dimensional representation of the joint and selected optimal implant components through a variety of positions and orientations to simulate real-world movements, loads, and stresses to account for patient-specific bone morphology and ligament attachment points. The Examiner interprets loads and stresses for each joint implant configuration to be intraoperative performance metrics.).
In regards to Claim 6, Boddington in view of Hughes teaches the system of claim 1, wherein the intraoperative simulated performance metric is an indication of a risk stratification (Paragraphs [0086], [0106], [0115], Boddington teaches calculating intra-operative surgical decision risks in the form of a “Failure Risk Score” and classifying intraoperative images of implant fixation into discrete categories that are predictive of surgical outcomes, such as “optimal” and “sub-optimal.” The Failure Risk Score is provided to the surgeon to support decisions that lead to optimal surgical outcomes and avoid suboptimal surgical outcomes.).
In regards to Claim 9, Boddington in view of Hughes discloses the system of claim 1, wherein the computer system comprises: at least one processor (Paragraph [0082], Fig. 2A, reference characters 100 and 101, Boddington teaches a computing platform (100) having at least one processor (101).);
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and at least one memory storing program code accessible by the at least one processor (Paragraphs [0081-82], Fig. 2A, reference character 102, Boddington teaches a memory device (102) having stored thereon computer executable instructions that when executed by the processor of a computer platform to perform the steps.), and configured to cause the at least one processor to: store the digital three-dimensional model of the joint (Paragraph [0099], Fig. 16, Boddington teaches 3D Shape Modeling Module for computing three-dimensional anatomical shape information. Fig. 16 shows output of the Shape Modeling Module.); receive the digital image of the joint and the implant component during the total joint replacement surgery (Fig. 27A, Paragraphs [0119-121], [0188], Boddington teaches preparing and positioning the patient for the surgery in a standard manner as indicated for the specific procedure, for example, a joint replacement surgery. A preoperative image is imported and a grid template is superimposed over the patient’s anatomical image. The grid templates contain may contain lines, geometrical patterns, numbers, letters, or a complex pattern of multiple lines and geometries corresponding to surgical variables and can be pre-designed or constructed intraoperatively. Next, the procedure specific information is extracted from the pre-operative image/data and mapped into the live intraoperative images. Fig. 27A, shown below, depicts use of a grid template in a hip total arthroplasty (THA). For example, if teardrops, symphysis pubis, ipsilateral teardrop, implant (cup) and stem (implant) and femoral head implant are detected, a functional pelvis grid/template is registered to the image.); perform registration between the digital image and the digital three-dimensional model to determine the placement of the implant component in the digital image in relation to the digital three-dimensional model (Paragraphs [0027-28], Fig. 4, Hughes teaches processing the image data to create a three-dimensional computer model of the knee joint incorporating the scanned image data. Processing the raw image data may include employing smoothing functions, interpolations, or other data processing techniques to coordinate the image data with the computer model of the knee joint. Models of the femur, tibia, and implant components can be combined to create a 3D model of the joint as shown in Fig. 4.); determine the intraoperative simulated performance metric by simulating movement of the digital three-dimensional model based on the placement of the implant component in the digital image (Paragraph [0029], Hughes teaches using a simulation software to virtually model the movement of the knee in conjunction with implant components to analyze attributes of the implant and articular surfaces such as proper tibial rotation, femoral rollback, patellar alignment, and quadriceps efficiency. A wide range of parameters can be experimentally viewed and tested using the computer-generated simulation. The Examiner interprets proper tibial rotation, femoral rollback, patellar alignment, and quadriceps efficiency to be intraoperative simulated performance metrics.); and provide the indication to the surgeon (Paragraph [0083], Boddington teaches providing the user with a Failure Risk Score with the output to the user as a confidence percentage recommendation of a suboptimal or optimal performance metric associated with an implant or anatomical alignment.).
In regards to Claim 13, Boddington in view of Hughes discloses the system of claim 1, wherein the system comprises a display (Paragraph [0076], Boddington teaches an electronic display device.), and wherein the intraoperative simulated performance metric is provided as a visual output using the display (Paragraphs [0007], [0073], [0076], Boddington teaches providing an intra-operative visual display to the user showing intra-operative surgical decision risks or a probability of a successful procedural outcome.).
In regards to Claim 14, Boddington in view of Hughes discloses the system of claim 1, wherein determining the placement of the implant component in the digital image comprises identifying one or more edges of the implant component in the digital image (Paragraph [0185], Fig. 23C, Boddington teaches registering the implant cup grid to the anatomical structures and fitting an ellipse to the implant cup. The ellipse is the outline of the edge of the cup. The Examiner interprets that fitting an ellipse to the edge of the implant cup is identifying an edge of the implant cup in the image since the claim is silent to how the implant component edge/ edges are detected. Under Broadest Reasonable Interpretation, the Examiner interprets the limitation “one or more edges” to mean only one edge is required to meet the claim limitation.).
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In regards to Claim 16, Boddington discloses a computer-implemented method for assisting a surgeon in total joint replacement of a joint of a patient (Paragraphs [0004-5], [0007], Boddington teaches a method for providing intraoperative automated intelligence guided surgical guidance in joint replacements, which is carried out by a computing platform.), the method comprising: storing a digital three-dimensional model of the joint (Paragraph [0099], Fig. 16, Boddington teaches 3D Shape Modeling Module for computing three-dimensional anatomical shape information. Fig. 16 shows output of the Shape Modeling Module.); receiving a digital image of the joint and an implant component during the total joint replacement surgery (Fig. 27A, Paragraphs [0119-121], [0188], Boddington teaches preparing and positioning the patient for the surgery in a standard manner as indicated for the specific procedure, for example, a joint replacement surgery. A preoperative image is imported and a grid template is superimposed over the patient’s anatomical image. The grid templates contain may contain lines, geometrical patterns, numbers, letters, or a complex pattern of multiple lines and geometries corresponding to surgical variables and can be pre-designed or constructed intraoperatively. Next, the procedure specific information is extracted from the pre-operative image/data and mapped into the live intraoperative images. Fig. 27A, shown below, depicts use of a grid template in a hip total arthroplasty (THA). For example, if teardrops, symphysis pubis, ipsilateral teardrop, implant (cup) and stem (implant) and femoral head implant are detected, a functional pelvis grid/template is registered to the image.); and providing an indication to the surgeon of the intraoperative simulated performance metric as an assessment of a current placement of the implant component (Paragraph [0148], Boddington teaches providing outputs related to surgical guidance such as implant selection recommendations, implant placement, performance predictions, probability of good outcomes, and failure risk scores. The user is provided with a Failure Risk Score as a confidence percentage recommendation of a suboptimal or optimal performance metric. The output is presented to the user in the form of intelligent predictors and scores to support decisions encountered in a real-time event.).
Boddington does not explicitly disclose performing registration between the digital image and the digital three-dimensional model to determine a placement of the implant component in the digital image in relation to the digital three-dimensional model; and determining an intraoperative simulated performance metric by simulating movement of the digital three-dimensional model based on the placement of the implant component in the digital image.
Hughes is in the same field of art of intra-operative implant placement optimization for joint arthroplasty procedures. Further, Hughes teaches performing registration between the digital image and the digital three-dimensional model to determine a placement of the implant component in the digital image in relation to the digital three-dimensional model (Paragraphs [0027-28], Fig. 4, Hughes teaches processing the image data to create a three-dimensional computer model of the knee joint incorporating the scanned image data. Processing the raw image data may include employing smoothing functions, interpolations, or other data processing techniques to coordinate the image data with the computer model of the knee joint. Models of the femur, tibia, and implant components can be combined to create a 3D model of the joint as shown in Fig. 4.); and determining an intraoperative simulated performance metric by simulating movement of the digital three-dimensional model based on the placement of the implant component in the digital image (Paragraph [0029], Hughes teaches using a simulation software to virtually model the movement of the knee in conjunction with implant components to analyze attributes of the implant and articular surfaces such as proper tibial rotation, femoral rollback, patellar alignment, and quadriceps efficiency. A wide range of parameters can be experimentally viewed and tested using the computer-generated simulation. The Examiner interprets proper tibial rotation, femoral rollback, patellar alignment, and quadriceps efficiency to be simulated intraoperative performance metrics.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Boddington by coordinating the intraoperative image of the joint with the three-dimensional (3D) computer model of the joint to determine a placement of the implant component in relation to the generated 3D model and simulating movement of the 3D model in conjunction with the implant to determine performance for a variety of movements such as tibial rotation, femoral rollback, patellar alignment, quadriceps efficiency, or alternative movements, that is taught by Hughes to make the invention that determines an optimal implant attribute and selects an optimal implant to determine position and orientation; thus, one of ordinary skill in the art would have been motivated to combine the references to obtain a proper position and orientation of the selected implant to ensure success of the joint arthroplasty procedure (Hughes, Paragraph [0004]).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
In regards to Claim 19, Boddington in view of Hughes teaches the method of claim 16, wherein the digital three-dimensional model is updated based on the determined placement of the implant component in the digital image in relation to the digital three-dimensional model, thereby determining an updated digital three-dimensional model (Paragraph [0032], Fig. 2, reference characters 210, 212, Hughes teaches selecting an optimal implant and creating a simulated 3D representation of the bone surfaces comprising the joint and selected implant components. Next, in step 212, ideal positioning and orientation of the selected implant component relative to the scanned anatomical features is determined.).
In regards to Claim 20, Boddington in view of Hughes teaches the method of claim 19, wherein the intraoperative simulated performance metric is associated with the updated digital three-dimensional model (Paragraph [0032], Hughes teaches moving the three-dimensional representation of the joint and selected optimal implant components through a variety of positions and orientations to simulate real-world movements, loads, and stresses to account for patient-specific bone morphology and ligament attachment points. The Examiner interprets loads and stresses for each joint implant configuration to be intraoperative performance metrics.).
In regards to Claim 21, Boddington in view of Hughes teaches the method of claim 16, wherein the intraoperative performance metric is an indication of a risk stratification (Paragraphs [0086], [0106], [0115], Boddington teaches calculating intra-operative surgical decision risks in the form of a “Failure Risk Score” and classifying intraoperative images of implant fixation into discrete categories that are predictive of surgical outcomes, such as “optimal” and “sub-optimal.” The Failure Risk Score is provided to the surgeon to support decisions that lead to optimal surgical outcomes and avoid suboptimal surgical outcomes.).
In regards to Claim 24, Boddington in view of Hughes teaches the method of claim 16, wherein the intraoperative simulated performance metric is provided as a visual output on a display (Paragraphs [0007], [0073], [0076], Boddington teaches providing an intra-operative visual display to the user showing surgical guidance such as intra-operative surgical decision risks or a probability of a successful procedural outcome.).
In regards to Claim 25, Boddington in view of Hughes teaches the method of claim 16, wherein determining the placement of the implant component in the digital image comprises identifying one or more edges of the implant component in the digital image (Paragraph [0185], Fig. 23C, Boddington teaches registering the implant cup grid to the anatomical structures and fitting an ellipse to the implant cup. The ellipse is the outline of the edge of the cup. The Examiner interprets that fitting an ellipse to the edge of the implant cup is identifying an edge of the implant cup in the image since the claim is silent to how the implant component edges are detected. Under Broadest Reasonable Interpretation, the limitation “one or more edges” requires only one edge to be identified to meet the claim limitation.).
In regards to Claim 26, Boddington discloses a computer-readable storage medium storing instructions that, when executed by a computing device, cause the computing device to perform the method of one or more operations comprising (Paragraph [0009], Boddington teaches a non-transitory computer-readable storage medium encoded with computer-readable instructions which form a software module and a processor to process the instructions.): storing a digital three-dimensional model of the joint (Paragraph [0099], Fig. 16, Boddington teaches 3D Shape Modeling Module for computing three-dimensional anatomical shape information. Fig. 16 shows output of the Shape Modeling Module.); receiving a digital image of the joint and an implant component during the total joint replacement surgery (Fig. 27A, Paragraphs [0119-121], [0188], Boddington teaches preparing and positioning the patient for the surgery in a standard manner as indicated for the specific procedure, for example, a joint replacement surgery. A preoperative image is imported and a grid template is superimposed over the patient’s anatomical image. The grid templates contain may contain lines, geometrical patterns, numbers, letters, or a complex pattern of multiple lines and geometries corresponding to surgical variables and can be pre-designed or constructed intraoperatively. Next, the procedure specific information is extracted from the pre-operative image/data and mapped into the live intraoperative images. Fig. 27A, shown below, depicts use of a grid template in a hip total arthroplasty (THA). For example, if teardrops, symphysis pubis, ipsilateral teardrop, implant (cup) and stem (implant) and femoral head implant are detected, a functional pelvis grid/template is registered to the image.); and providing an indication to the surgeon of the intraoperative simulated performance metric as an assessment of a current placement of the implant component (Paragraph [0148], Boddington teaches outputs related to surgical guidance such as implant selection recommendations, implant placement, performance predictions, probability of good outcomes, and failure risk scores. The user is provided with a Failure Risk Score as a confidence percentage recommendation of a suboptimal or optimal performance metric. The output is presented to the user in the form of intelligent predictors and scores to support decisions encountered in a real-time event.).
Boddington does not explicitly disclose performing registration between the digital image and the digital three-dimensional model to determine a placement of the implant component in the digital image in relation to the digital three-dimensional model; and determining an intraoperative simulated performance metric by simulating movement of the digital three-dimensional model based on the placement of the implant component in the digital image.
Hughes is in the same field of art of determining an ideal positioning and orientation of an implant component during a joint replacement surgery. Further, Hughes teaches performing registration between the digital image and the digital three-dimensional model to determine a placement of the implant component in the digital image in relation to the digital three-dimensional model (Paragraphs [0027-28], Fig. 4, Hughes teaches processing the image data to create a three-dimensional computer model of the knee joint incorporating the scanned image data. Processing the raw image data may include employing smoothing functions, interpolations, or other data processing techniques to coordinate the image data with the computer model of the knee joint. Models of the femur, tibia, and implant components can be combined to create a 3D model of the joint with simulated implant components (see arrow below) as shown in Fig. 4. The Examiner interprets coordinating the 2D image data with the three-dimensional computer model of the knee joint by employing smoothing functions, interpolations, etc., to be synonymous to performing registration.); and determining an intraoperative simulated performance metric by simulating movement of the digital three-dimensional model based on the placement of the implant component in the digital image (Paragraph [0029], Hughes teaches using a simulation software to virtually model the movement of the knee in conjunction with implant components to analyze attributes of the implant and articular surfaces such as proper tibial rotation, femoral rollback, patellar alignment, and quadriceps efficiency. A wide range of parameters can be experimentally viewed and tested using the computer-generated simulation. The Examiner interprets proper tibial rotation, femoral rollback, patellar alignment, and quadriceps efficiency to be simulated intraoperative performance metrics.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Boddington by coordinating the image of the joint with the three-dimensional (3D) joint model to generate a combined 3D model and performing simulations to model the movement of the joint in conjunction with the implant to analyze the joint’s simulated performance for a range of movements that is taught by Hughes to make the invention that identifies optimal implant attributes; thus, one of ordinary skill in the art would have been motivated to combine the references to obtain a proper position and orientation of the implant to ensure success of the joint arthroplasty procedure (Hughes, Paragraph [0003]).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
Claims 2-3, 7, 10 and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Boddington et al. (U.S. Patent Pub. No. 2022/0265233 A1, hereafter referred to as Boddington) in view of Hughes et al. (U.S. Patent Pub. No. 2013/0144392, hereafter referred to as Hughes) in further view of McKinnon (U.S. Patent Pub. No. 2020/0275976 A1, hereafter referred to as McKinnon).
Regarding Claim 2, Boddington in view of Hughes discloses the system of claim 1.
Boddington in view of Hughes does not explicitly disclose wherein the computer system is configured to determine a preoperative simulated performance metric by simulating movement of the digital three-dimensional model according to a surgical plan, the surgical plan comprising a planned placement of the implant component in the digital three-dimensional model.
McKinnon is in the same field of art of optimizing arthroplasty surgical procedures by determining patient-specific kinematic and kinetic response values to determine the optimal orientation and position of a joint replacement implant. Further, McKinnon teaches wherein the computer system is configured to determine a preoperative simulated performance metric by simulating movement of the digital three-dimensional model according to a surgical plan (Paragraphs [0234-237], Figs. 12A-C, McKinnon teaches an anatomical modeling software for developing a pre-operative plan to guide surgery. In the context of knee surgery, the software can determine how changes in the position and orientation of the implant components can affect the mechanics of the replacement knee. For example, the software can incorporate these variables throughout a range of motion and exemplary forces for a given patient activity to model the implant performance. Figs. 12A-C show outputs of the software to visually depict the results. Figs. 12A and 12B show hip range of motion (ROM) plots. Fig. 12 C shows a graph that represent a recommendation for a desirable or “safe” range of positions for seating a hip implant in the acetabulum.), the surgical plan comprising a planned placement of the implant component in the digital three-dimensional model (Paragraphs [0099-100], McKinnon teaches a surgical plan providing recommended implant position and orientation based on the three-dimensional model of the joint. The surgical plan can display the planned resection to the joint and superimpose the planned implants onto the joint.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Boddington in view of Hughes by determining a preoperative performance measure such as hip range of motion (ROM) based on the planned placement of the implant in the surgical plan that is taught by McKinnon to make the invention that plans the orientation and position of the joint replacement based on the surgical plan prior to commencing surgery; thus, one of ordinary skill in the art would have been motivated to combine the references to improve and adjust the surgical plan intraoperatively as additional information is gathered about the patient’s joint (McKinnon, Paragraph [0003]).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
In regards to Claim 3, Boddington in view of Hughes in further view of McKinnon discloses the system of claim 2, wherein the indication comprises a comparison between the intraoperative simulated performance metric and the preoperative simulated performance metric (Paragraphs [0162-0163], [0173], Boddington teaches obtaining a pre-operative anteroposterior radiographic reference image (anteroposterior hip view or anteroposterior pelvis view) and defining at least one reference image metric. The metrics can include leg length and offset, ipsilateral, leg length and offset, contralateral, pelvic tilt, pelvic rotation, femoral abduction (ipsil & contra), femoral rotation (ipsil & contra) and femoral head center of rotation. During surgery, an intra-operative anteroposterior radiographic image (anteroposterior hip view or anteroposterior pelvis view) is obtained. Next, the reference image is compared to the intraoperative image. The differences in the images look at: pelvic tilt, pelvic rotation, and contralateral femoral rotation/abduction in an alternative embodiment, taken from the ipsilateral side: anteroposterior Hip (detected when limited points available).)
In regards to Claim 7, Boddington in view of Hughes discloses the system of claim 6.
Boddington in view of Hughes does not explicitly disclose wherein the risk stratification is indicative of a risk associated with multiple predicted postoperative movements by the patient.
McKinnon is in the same field of art of optimizing arthroplasty surgical procedures by determining patient-specific kinematic and kinetic response values to determine the optimal orientation and position of a joint replacement implant. Further, McKinnon teaches wherein the risk stratification is indicative of a risk associated with multiple predicted postoperative movements by the patient (Paragraph [0236], Figs. 12A-C, McKinnon teaches simulating the positions and orientations of implants in relation to bony anatomy throughout a variety of activities that a patient may experience post-surgery such as activities that pose a high risk for impingement and dislocation such as crossing legs while seated, deep flexion while sitting, hyperextension while standing, etc. Fig. 12C shows a 2D graph that demonstrates a recommendation for a “safe” range of positions for seating a hip implant in the acetabulum. For each possible implant position, the software tests whether a position creates a failure of the anatomy or implant under normal functional activities.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Boddington in view of Hughes by virtually simulating the positions and orientations of the implants in relation to bony anatomy throughout a variety of post-surgery exercises/activities such as crossing legs while seated, deep flexion while sitting, and hyperextension while standing, and identifying any impinged range of motion where abnormal and wearing contact exists between the joint and the implant as well as identifying a safe range of positions for the hip implant in the acetabulum that is taught by McKinnon, to make the invention that visually depicts the results of the hip modeling simulation for a variety of post-operative movements to determine for each implant position, whether the position creates failure of the anatomy or implant under normal functional activities; thus, one of ordinary skilled in the art would be motivated to combine the references to better determine how changes in the size and pose of the implant components can affect the mechanics of the replacement joint and predict the optimal implant positions and orientations for each patient (McKinnon, Paragraph [0235]).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
In regards to Claim 10, Boddington discloses the system of claim 1, wherein the computer system comprises: a first computing device (Paragraph [0075], Boddington teaches an intraoperative surgical guidance system having a computing platform.) comprising: at least one first processor (Paragraph [0081], Boddington teaches the computer platform includes at least one processor.); and at least one first memory storing program code accessible by the at least one first processor (Paragraph [0081], Boddington teaches the computing platform having a memory.), and configured to cause the at least one first processor to: store the digital three-dimensional model of the joint (Paragraph [0099], Fig. 16, Boddington teaches 3D Shape Modeling Module for computing three-dimensional anatomical shape information. Fig. 16 shows output of the Shape Modeling Module.); receive the digital image of the joint and the implant component during the total joint replacement surgery (Fig. 27A, Paragraphs [0119-121], [0188], Boddington teaches preparing and positioning the patient for the surgery in a standard manner as indicated for the specific procedure, for example, a joint replacement surgery. A preoperative image is imported and a grid template is superimposed over the patient’s anatomical image. The grid templates contain may contain lines, geometrical patterns, numbers, letters, or a complex pattern of multiple lines and geometries corresponding to surgical variables and can be pre-designed or constructed intraoperatively. Next, the procedure specific information is extracted from the pre-operative image/data and mapped into the live intraoperative images. Fig. 27A, shown below, depicts use of a grid template in a hip total arthroplasty (THA). For example, if teardrops, symphysis pubis, ipsilateral teardrop, implant (cup) and stem (implant) and femoral head implant are detected, a functional pelvis grid/template is registered to the image.).
Boddington does not explicitly disclose perform(ing) registration between the digital image and the digital three- dimensional model to determine the placement of the implant component in the digital image in relation to the digital three-dimensional model; determin
Hughes is in the same field of art of intra-operative implant placement optimization for joint arthroplasty procedures. Further, Hughes teaches perform(ing) registration between the digital image and the digital three- dimensional model to determine the placement of the implant component in the digital image in relation to the digital three-dimensional model (Paragraphs [0027-28], Fig. 4, Hughes teaches processing the image data to create a three-dimensional computer model of the knee joint incorporating the scanned image data. Processing the raw image data may include employing smoothing functions, interpolations, or other data processing techniques to coordinate the image data with the computer model of the knee joint. Models of the femur, tibia, and implant components can be combined to create a 3D model of the joint as shown in Fig. 4.); and determin(Paragraph [0029], Hughes teaches using a simulation software to virtually model the movement of the knee in conjunction with implant components to analyze attributes of the implant and articular surfaces such as proper tibial rotation, femoral rollback, patellar alignment, and quadriceps efficiency. A wide range of parameters can be experimentally viewed and tested using the computer-generated simulation. The Examiner interprets proper tibial rotation, femoral rollback, patellar alignment, and quadriceps efficiency to be simulated performance metrics.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Boddington by coordinating the image of the joint to a three-dimensional (3D) model to perform proper placement of an implant component in the 3D model and determine implant performance by simulating a variety of real-world movements such as tibial rotation, femoral rollback, patellar alignment, quadriceps efficiency, or alternative performance metric., that is taught by Hughes to make the invention that identifies which implant configuration best achieves a desired performance metric; thus, one of ordinary skill in the art would have been motivated to combine the references to enable the surgeon to select an optimal implant as well as determine the ideal positioning and orientation of the selected implant relative to the anatomical features in the intraoperative image (Abstract, Hughes).
Boddington in view of Hughes does not explicitly disclose a second computing device comprising: at least one second processor; and at least one second memory storing program code accessible by the at least one second processor, and configured to cause the at least one second processor to: provide the indication to the surgeon.
Further, McKinnon is in the same field of art of optimizing arthroplasty surgical procedures by determining patient-specific kinematic and kinetic response values to determine the optimal orientation and position of a joint replacement implant. Further, McKinnon teaches a second computing device (Paragraph [0091], McKinnon teaches a Surgical Computer which provides control instructions to various components of the Computer Assisted Surgical System (CASS).) comprising: at least one second processor (Paragraph [0091], McKinnon teaches the Surgical Computer may be a parallel computing platform that uses multiple central processing units (CPUs) or graphics processing units (GPUs) to perform processing.); and at least one second memory storing program code accessible by the at least one second processor (Paragraph [0303], Fig. 20, McKinnon teaches the Surgical Computer having a device memory.), and configured to cause the at least one second processor to: provide the indication to the surgeon (Paragraph [0132], McKinnon teaches the Surgical Computer provides the Display with any visualization that is needed by the Surgeon during surgery. For example, the display is an interactive interface that can dynamically update and display how changes in the surgical plan would impact the procedure and the final position and orientation of implants installed on bone.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Boddington in view of McKinnon by adding a second computing device into the intraoperative surgical guidance system comprising at least one processor and at least one memory for providing the indication to the surgeon during surgery, that is taught by McKinnon to make the invention that iteratively updates and displays how the current position and orientation of an implant can impact the joint’s expected performance; thus, one of ordinary skill in the art would have been motivated to combine the references to accurately model anatomical response and guide the surgical plan to improve the existing approach (McKinnon, Paragraph [0206]).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
In regards to Claim 17, Boddington in view of Hughes discloses the method of claim 16.
Boddington in view of Hughes does not explicitly disclose determining a preoperative simulated performance metric by simulating movement of the digital three-dimensional model according to a surgical plan.
Further, McKinnon discloses determining a preoperative simulated performance metric by simulating movement of the digital three-dimensional model according to a surgical plan (Paragraphs [0234-237], Figs. 12A-C, McKinnon teaches an anatomical modeling software for developing a pre-operative plan to guide surgery. In the context of hip surgery, if the software has knowledge of the relationship between the spine and pelvis throughout a variety of activities, the software can better predict an optimal implant position. In the context of knee surgery, the software can determine how changes in the position and orientation of the implant components can affect the mechanics of the replacement knee. For example, the software can incorporate these variables throughout a range of motion and exemplary forces for a given patient activity to model the implant performance. Figs. 12A-C show outputs of the software to visually depict the results. Figs. 12A and 12B show hip range of motion (ROM) plots. Fig. 12 C shows graphs that represent a recommendation for a desirable or “safe” range of positions for seating a hip implant in the acetabulum.), the surgical plan comprising a planned placement of the implant component in the digital three-dimensional model (Paragraphs [0099-100], McKinnon teaches a surgical plan providing recommended implant position and orientation based on the three-dimensional model of the joint. The surgical plan can display the planned resection to the joint and superimpose the planned implants onto the joint.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Boddington in view of Hughes by using anatomical modeling software to develop a pre-operative surgical plan by performing a range-of-motion (ROM) “exam” and generating an ROM plot to identify any impinged ROM, that is taught by McKinnon, to make the invention that simulates movement of the joint in a variety of positions to determine an unimpinged ROM for safe positioning of the implant; thus, one of ordinary skilled in the art would be motivated to combine the references to better predict the optimal implant positions and orientations by incorporating the relationship between the complex joint anatomy throughout the range of motion and exemplary forces for a given patient activity/movement (McKinnon, Paragraph [0235]).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
In regards to Claim 18, Boddington in view of Hughes in further view of McKinnon discloses the method of claim 17, wherein the indication comprises a comparison between the intraoperative simulated performance metric and the preoperative simulated performance metric (Paragraphs [0162-0163], [0173], Boddington teaches obtaining a pre-operative anteroposterior radiographic reference image (anteroposterior hip view or anteroposterior pelvis view) and defining at least one reference image metric. The metrics can include leg length and offset, ipsilateral, leg length and offset, contralateral, pelvic tilt, pelvic rotation, femoral abduction (ipsil & contra), femoral rotation (ipsil & contra) and femoral head center of rotation. During surgery, an intra-operative anteroposterior radiographic image (anteroposterior hip view or anteroposterior pelvis view) is obtained. Next, the reference image is compared to the intraoperative image. The differences in the images look at: pelvic tilt, pelvic rotation, and contralateral femoral rotation/abduction in an alternative embodiment, taken from the ipsilateral side: anteroposterior Hip (detected when limited points available).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SYDNEY L BLACKSTEN whose telephone number is (571)-272-7651. The examiner can normally be reached 8:30am-5pm.
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/SYDNEY L BLACKSTEN/Examiner, Art Unit 2674
/ONEAL R MISTRY/Supervisory Patent Examiner, Art Unit 2674