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 .
DETAIL OFFICE ACTIONS
The United States Patent & Trademark Office appreciates the response filed for the current application that is submitted on 07/01/2026. The United States Patent & Trademark Office reviewed the following documents submitted and has made the following comments below.
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. AU2020900653, filed on 03/04/2020.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 09/06/2022 has been considered by the examiner. The submission is in compliance with the provisions of 37 CFR 1.97.
Amendments
Applicant submitted amendments on 07/01/2026. The examiner acknowledges the amendment and has reviewed the claims accordingly.
Status of Claims
Claims 1-7, 9-10, 13-14, 16-21, and 24-26 are pending.
Claims 8, 11-12, 15, and 22-23 are cancelled.
Applicant Arguments:
Regarding Argument 1, see remarks (page 12), filed 07/01/2026, Applicant/s state/s “The disclosure is objected to because of the following informalities. Amendments are made to the specification… All of the corrections are made as requested in the Office Action. Applicant respectfully requests that the objections to the specification be withdrawn.”
Regarding Argument 2, see remarks (pages 12-13), filed 07/01/2026, Applicant/s state/s “Claims 1-7, 9, 10, 13, 14, 16-21, and 24-26 are provisionally rejected on the ground of non- statutory double patenting as being unpatentable over claims 1-7, 9, 10, 13, 14, 16-21, and 24-26 of co-pending application 17/905,680. Applicant traverses this rejection based at least on the amendments made to the current claims. For example, independent claims 1, 16, and 26 are each amended to further recite, "wherein determining the placement of the implant component in the digital three-dimensional model comprises detecting one or more edges of the implant component in the two or more two-dimensional digital images using an edge detection method." As explained below, this recitation is not disclosed or suggested in the cited prior art nor in the claims of co- pending application 17/905,680. Therefore, the currently amended claims are patentably distinct from and not obvious over the claims of co-pending application 17//905,680. Applicant respectfully requests that the provisional double patenting rejection be withdrawn.”
Regarding Argument 3, see remarks (page 13), filed 07/01/2026, Applicant/s state/s “Claim 26 is rejected because the claimed invention is allegedly directed to non-statutory subject matter. Claim 26 is amended to recite "a non-transitory computer-readable storage medium," as suggested. Applicant respectfully submits that claim 26 is now directed to statutory subject matter and is now patent eligible, and requests that this rejection be withdrawn.”
Regarding Argument 4, see remarks (page 14), filed 07/01/2026, Applicant/s state/s “Accordingly, the cited prior art including Janna, Boddington, McKinnon, and de Souza, considered individually or collectively, does not disclose or suggest the newly-added limitation in amended claims 1, 16, and 26. Because that limitation is now required for the core "determining placement" step that underpins the intraoperative simulation and guidance, a prima facie case for obviousness of claims 1, 16, and 26 over the cited prior art cannot be made. Claims 1, 16, and 26 are therefore in condition for allowance over the cited prior art.”
Regarding Argument 5, see remarks (page 14), filed 07/01/2026, Applicant/s state/s “Dependent claims 2-7, 9, 10, 13, 14, 17-21, 24, and 25 are also in condition for allowance over the cited prior art as being dependent on an allowable base claim. Applicant respectfully requests withdrawal of the obviousness rejections of claims 1-7, 9, 10, 13, 14, 16-21, and 24-26.”
Examiner’s Responses:
In response to Argument 1, see remarks (page 12), filed 07/01/2026, with respect to the objections to the specification have been fully considered and are persuasive. Therefore, the objections to the specification have been withdrawn.
In response to Argument 2, see remarks (pages 12-13), filed 07/01/2026, with respect to the provisional non-statutory double-patenting rejection of claims 1-7, 9, 10, 13, 14, 16-21, and 24-26 over claims 1-7, 9, 10, 13, 14, 16-21, and 24-26 of co-pending application 17/905,680 have been fully considered but they are not persuasive. Therefore, the provisional non-statutory double-patenting rejection has been maintained.
Specifically, the Examiner finds the claims of the examined application are not patentably distinct from the claims of the co-pending application (17/905,680) because the examined application claim would have been obvious over the reference claims. Specifically, although the co-pending application (17/905,680) does not specifically recite the limitation: “wherein determining the placement of the implant component in the digital three- dimensional model comprises detecting one or more edges of the implant component in the two or more two-dimensional digital images using an edge detection method”, the co-pending application does however suggest determining placement of the implant component in the digital image by identifying edges of the implant component in the digital image. Claims 14 and 25 of co-pending application (17/905,680) recite “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.” See the details of the obviousness-type double-patenting rejection below.
In response to Argument 3, see remarks (page 13), filed 07/01/2026, with respect to the 35 U.S.C. 101 rejection on claim 26 has been fully considered and is persuasive. Therefore, the 35 U.S.C. 101 rejection to claim 26 has been withdrawn.
In response to Argument 4, see remarks (page 14), filed 07/01/2026, with respect to the 35 U.S.C. 103 rejections of claims 1, 16, and 26 have been fully considered but are moot in view of new ground(s) of rejection caused by the amendments. Therefore, the original rejection of Claims 1, 16, and 26 is withdrawn under 35 U.S.C 103. However, a new grounds of rejection is issued for Claims 1, 16, and 26 under 35 U.S.C. 103 in view of Janna et al. (U.S. Patent No. 11,931,107 B1, hereafter referred to as Janna) in view of Boddington et al. (U.S. Patent Pub. No. 2022/0265233 A1, hereafter referred to as Boddington) in further view of Giphart et al. (U.S. Patent Pub. No. 20180342315 A1, hereafter referred to as Giphart).
The Examiner finds that Giphart teaches the amended claim language “wherein determining the placement of the implant component in the digital three- dimensional model comprises detecting one or more edges of the implant component in the two or more two-dimensional digital images using an edge detection method”. Giphart teaches a medical imaging method for establishing implant configuration by measuring positions and orientations of its components constrained by defined kinematic relationship between them using stereo radiography images. The method allows for determination of a patient-specific implant configuration and enables accurate measurements of the pose of implant (Abstract). Specifically, Giphart teaches “wherein determining the placement of the implant component in the digital three- dimensional model” Giphart teaches the three-dimensional measurement of the position and orientation of the implant’s assembly components consists of establishing a geometric relationship between the implant’s representation in the stereo radiographic images and a 3D computer model of the implant’s assembly components. Methods for the 3D measurement involve fitting the projection of the 3D computer model to edge or gradient data of the implant’s assembly components visible in the radiographic images (Paragraph [0024], Fig. 3). Further, the Examiner finds Giphart teaches “detecting one or more edges of the implant component in the two or more two-dimensional digital images using an edge detection method”. Giphart teaches filtering the radiographic images using a Canny edge detection filter (Paragraph [0038]). The Examiner interprets Canny edge detection to be “an edge detection method”. The image information used to calculate the 3D position and orientation may be based on the use of edge detection of the radiographic images (Paragraph [0023]). Finally, the radiographic images are stereo radiography images, in which stereo radiography is a technique that uses two x-ray systems with intersecting beams and taking two x-ray images (x-rays are 2D images) simultaneously of an object placed in the beam intersection (Paragraph [0004], Fig. 3). Therefore, the Examiner interprets one or more edges of the implant component are detected in two or more (stereo pair) two-dimensional (x-ray) digital images. The Examiner will maintain prior art Janna and Boddington and the details of the rejection are below.
In response to Argument 5, see remarks (page 14), filed 07/01/2026, with respect to the 35 U.S.C. 103 rejections of dependent claims 2-7, 9, 10, 13, 14, 17-21, 24, and 25 as being dependent on an allowable base claim has been fully considered but are moot in view of new ground(s) of rejection caused by amendments. Therefore, the original rejections of Claims 2-7, 9, 10, 13, 14, 17-21, 24, and 25 are withdrawn under 35 U.S.C. 103.
However, a new ground(s) of rejection is issued for dependent Claims 2-4, 6, 9-10, 13, 17-19, 21, and 24 under 35 U.S.C. 103 in view of Janna et al. (U.S. Patent No. 11,931,107 B1, hereafter referred to as Janna) in view of Boddington et al. (U.S. Patent Pub. No. 20220265233 A1, hereafter referred to as Boddington) in further view of Giphart et al. (U.S. Patent Pub. No. 20180342315 A1, hereafter referred to as Giphart). The Examiner will maintain prior art Janna and Boddington and the details of the rejection are below.
A new ground(s) of rejection is issued for dependent Claims 5, 7, and 20 under 35 U.S.C. 103 in view of Janna et al. (U.S. Patent No. 11,931,107 B1, hereafter referred to as Janna) in view of Boddington et al. (U.S. Patent Pub. No. 20220265233 A1, hereafter referred to as Boddington) in further view of Giphart et al. (U.S. Patent Pub. No. 20180342315 A1, hereafter referred to as Giphart) in further view of McKinnon et al. (U.S. Patent Pub. No. 20200275976 A1, hereafter referred to as McKinnon). The Examiner will maintain prior art Janna, Boddington, and McKinnon and the details of the rejection are below.
A new ground(s) of rejection is issued for dependent Claims 14 and 25 under 35 U.S.C. 103 in view of Janna et al. (U.S. Patent No. 11,931,107 B1, hereafter referred to as Janna) in view of Boddington et al. (U.S. Patent Pub. No. 2022/0265233 A1, hereafter referred to as Boddington) in further view of Giphart et al. (U.S. Patent Pub. No. 20180342315 A1, hereafter referred to as Giphart) in further view of Mahfouz et al. (NPL “A robust method for registration of three-dimensional knee implant models to two-dimensional fluoroscopy images”, 2003, hereafter referred to as Mahfouz). The Examiner will maintain prior art Janna and Boddington and the details of the rejection are below.
Claim Objections
Claim 26 is objected to because of the following informalities:
In Claim 26, on line 4, The Examiner suggests changing “the joint” to “a joint”.
Appropriate correction is required.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-7, 9-10, 13-14, 16-21, and 24-26 are provisionally rejected on the ground of non-statutory double patenting as being unpatentable over claims 1-7, 9-10, 13-14, 16-21, and 24-26 of co-pending application (Application No. 17/905,680) (reference application). Although the claims at issue are not identical, they are not patentably distinct from each other because the notion of the claims of the current application correspond with the claims in the reference application.
Below is a limitation mapping between the current application and the claims of the reference application.
Current Application (17/905,681)
Co-pending Application (17/905,680)
Claim 1:
An intraoperative guidance system for total joint replacement of a joint of a patient by a surgeon, the guidance system comprising:
an X-ray imaging device for application of X-ray radiation to the joint and for detecting X-ray radiation to create a two-dimensional digital image of the joint and an implant component; and
a computer system configured to: store an initial three-dimensional model of the joint and the implant component;
receive two or more two-dimensional digital images of the joint and the implant component captured from two or more respective directions by the X-ray imaging device;
create a digital three-dimensional model of the joint and the implant component based on the two or more two-dimensional digital images;
perform registration between the digital three-dimensional model and the initial three-dimensional model to determine a placement of the implant component in the digital three- dimensional model in relation to a placement of the implant component in the initial three- dimensional model;
wherein determining the placement of the implant component in the digital three- dimensional model comprises detecting one or more edges of the implant component in the two or more two-dimensional digital images using an edge detection method;
determine an intraoperative simulated performance metric by simulating movement of the digital three-dimensional model based on the placement of the implant component in the two or more two-dimensional digital images;
and provide an indication to the surgeon of the intraoperative simulated performance metric as an assessment of a current placement of the implant component.
Claim 16:
A computer-implemented method for assisting a surgeon in total joint replacement of a joint of a patient, the method comprising:
storing an initial three-dimensional model of the joint and an implant component;
receiving two or more two-dimensional digital images of the joint and the implant component during the total joint replacement surgery;
creating a digital three-dimensional model of the joint and the implant component based on the two or more two-dimensional digital images;
performing registration between the digital three-dimensional model and the initial three-dimensional model to determine a placement of the implant component in the digital three- dimensional model in relation to a placement of the implant component in the initial three- dimensional model;
wherein determining the placement of the implant component in the digital three- dimensional model comprises detecting one or more edges of the implant component in the two or more two-dimensional digital images using an edge detection method;
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 two or more two-dimensional digital images; and
providing an indication to the surgeon of the intraoperative simulated performance metric as an assessment of a current placement of the implant component.
Claim 26:
A non-transitory computer-readable storage medium storing instructions that, when executed by a computing device, cause the computing device to perform one or more operations, comprising:
storing an initial three-dimensional model of the joint and an implant component;
receiving two or more two-dimensional digital images of the joint and the implant component during the total joint replacement surgery;
creating a digital three-dimensional model of the joint and the implant component based on the two or more two-dimensional digital images;
performing registration between the digital three-dimensional model and the initial three-dimensional model to determine a placement of the implant component in the digital three- dimensional model in relation to a placement of the implant component in the initial three- dimensional model;
wherein determining the placement of the implant component in the digital three- dimensional model comprises detecting one or more edges of the implant component in the two or more two-dimensional digital images using an edge detection method;
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 two or more two-dimensional digital images; and
providing an indication to the surgeon of the intraoperative simulated performance metric as an assessment of a current placement of the implant component.
Claim 1:
An intraoperative guidance system for total joint replacement of a joint of a patient by a surgeon, 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; and
a computer system configured to: store a digital three-dimensional model of the joint;
receive the digital image of the joint and the implant component during the total joint replacement surgery;
perform 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;
wherein the registration comprises a three- dimensional to two-dimensional registration in which one or more three-dimensional model landmarks of the digital three-dimensional model are registered to one or more corresponding digital image landmarks of the digital image by iteratively adjusting a pose of the digital three-dimensional model, projecting the digital three- dimensional model into a two-dimensional space, and minimizing a distance between the one or more three-dimensional model landmarks and the one or more corresponding digital image landmarks;
update the digital three-dimensional model based on the placement of the implant component to reflect an actual implanted pose of the implant component;
determine an intraoperative simulated performance metric by performing a kinematic analysis on the updated digital three-dimensional model, comprising simulating movement of relevant portions of the digital three-dimensional model based on the placement of the implant component in the digital image to determine a postoperative range of motion;
and provide an indication to the surgeon of the intraoperative simulated performance metric as an assessment of a current placement of the implant component.
Claim 16:
A computer-implemented method for assisting a surgeon in total joint replacement of a joint of a patient, the method comprising:
storing a digital three-dimensional model of the joint;
receiving a digital image of the joint and an implant component during the total joint replacement surgery;
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;
wherein the registration comprises a three- dimensional to two-dimensional registration in which one or more three-dimensional model landmarks of the digital three-dimensional model are registered to one or more corresponding digital image landmarks of the digital image by iteratively adjusting a pose of the digital three-dimensional model, projecting the digital three- dimensional model into a two-dimensional space, and minimizing a distance between the one or more three-dimensional model landmarks and the one or more corresponding digital image landmarks;
updating the digital three-dimensional model based on the placement of the implant component to reflect an actual implanted pose of the implant component;
determining an intraoperative simulated performance metric by performing a kinematic analysis on the updated digital three-dimensional model, comprising simulating movement of relevant portions of the digital three- dimensional model based on the placement of the implant component in the digital image to determine a postoperative range of motion; and
providing an indication to the surgeon of the intraoperative simulated performance metric as an assessment of a current placement of the implant component.
Claim 26:
A non-transitory computer-readable storage medium storing instructions that, when executed by a computing device, cause the computing device to perform one or more operations comprising:
storing a digital three-dimensional model of a joint;
receiving a digital image of the joint and an implant component during a total joint replacement surgery;
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;
wherein the registration comprises a three-dimensional to two-dimensional registration in which one or more three-dimensional model landmarks of the digital three-dimensional model are registered to one or more corresponding digital image landmarks of the digital image by iteratively adjusting a pose of the digital three-dimensional model, projecting the digital three-dimensional model into a two- dimensional space, and minimizing a distance between the one or more three-dimensional model landmarks and the one or more corresponding digital image landmarks;
updating the digital three-dimensional model based on the placement of the implant component to reflect an actual implanted pose of the implant component;
determining an intraoperative simulated performance metric by performing a kinematic analysis on the updated digital three-dimensional model, comprising simulating movement of relevant portions of the digital three-dimensional model based on the placement of the implant component in the digital image to determine a postoperative range of motion; and
providing an indication to the surgeon of the intraoperative simulated performance metric as an assessment of a current placement of the implant component.
Co-pending application (No. 17/905,680) does not explicitly disclose wherein determining the placement of the implant component in the digital three- dimensional model comprises detecting one or more edges of the implant component in the two or more two-dimensional digital images using an edge detection method.
However, Giphart discloses wherein determining the placement of the implant component in the digital three- dimensional model (Paragraph [0024], Fig. 3, Giphart teaches the three-dimensional measurement of position and orientation of the implant’s assembly components consists of establishing a geometric relation between the implant’s representation in the stereo radiographic images and a 3D computer model of the implant’s assembly components.) comprises detecting one or more edges of the implant component (Paragraphs [0023-24], Fig. 3, Giphart teaches the image information used to calculate the 3D position and orientation may be based on the use of edge detection of the radiographic images. Methods for the 3D measurement of the position and orientation of the implant’s assembly components involve fitting the projection of the 3D computer model to edge or gradient data of the implant’s assembly components visible in the radiographic images. The position and orientation of the 3D computer model of the implant’s assembly components are derived from the radiographic images.)
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in the two or more two-dimensional digital images (Paragraphs [0021], [0004], [0013], Fig. 3, Giphart teaches the 3D computer models of the implant’s assembly components are obtained and their assembly and pose determined based on a pair of radiographic images of a patient’s implant. See Fig. 3 above, a pair of images.) using an edge detection method (Paragraph [0038], Giphart teaches the radiographic images were filtered using a Canny edge detection filter.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply and/or modify the co-pending application (17/905,680) claims by determining the placement of the implant component(s) in the 3D model based on the detection of one or more edges of the implant component(s) in two or more 2D images using a Canny edge detection method that is taught by Giphart, to make the invention that allows for the determination of a patient-specific implant configuration and enables accurate measurements of the pose of the implant based on edge detection. Thus, one of ordinary skilled in the art would be motivated to combine the references since there is a need for assessing and monitoring the position and orientation of the implant assembly’s components in order to measure metrics of interest such as settling of assembly components onto each other, benning in, creep, and wear in implants with liners and spaces, and migration of the implant within the bone into which it has been installed (Giphart, Paragraph [0019]). Further, performing edge detection can identify edges belonging to each respective implant assembly component (such as femoral stem, head, and acetabular cup) and therefore, each of the respective positions and orientations of the components may be determined (Giphart, Paragraphs [0038-39]) to build a realistic implant model for the patient. Therefore, identifying edges of implant components in the images allows precise spatial alignment between the implant’s physical position and its digital representation in the 3D model, thereby enabling accurate simulations to be performed using the model.
The computer-implemented method and non-transitory computer-readable storage medium claims of Claims 16 and 26 have similar limitations to the system of Claim 1 and are therefore rejected under the same rationale.
Dependent claims 2-3, 6-7, 9-10, 13-14, 17-18, 21, and 24-25 of the current application recite the same limitations in different language to claims 2-3, 6-7, 9-10, 13-14, 17-18, 21, and 24-25 in the co-pending application. Accordingly, although the conflicting claims of the current application and the co-pending application are not identical, they are not patentably distinct from each other.
This is a provisional non-statutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
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, 9-10, 13, 16, 17-19, 21, 24, and 26 are rejected under 35 U.S.C. 103(a) as being unpatentable over Janna et al. (U.S. Patent No. 11,931,107 B1, hereafter referred to as Janna) in view of Boddington et al. (U.S. Patent Pub. No. 2022/0265233 A1, hereafter referred to as Boddington) in further view of Giphart et al. (U.S. Patent Pub. No. 20180342315 A1, hereafter referred to as Giphart).
Regarding Claim 1, Janna teaches an intraoperative guidance system for total joint replacement of a joint of a patient by a surgeon (Col. 3, lines 54-67 and Col. 4, lines 1-3, Fig. 1, Janna teaches a computer-assisted surgical system (CASS) (100), which uses computers, robotics, and imaging technology to aid surgeons in performing orthopedic surgery procedures such as total knee arthroplasty (TKA) or total hip arthroplasty (THA). The CASS allows surgeons to more accurately plan, track, and navigate the placement of instruments and implants relative to the body of a patient, as well as conduct intra-operative body imaging.),
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the guidance system comprising:
an X-ray imaging device for application of X-ray radiation to the joint (Col. 35, lines 1-17, Col. 33, lines 39-42, Figs. 1 & 8A, Janna teaches a CASS (100) which positions a robotic arm (105A), to which an x-ray source is attached. Two-dimensional images may be captured of both the tracking fiducials and the patient’s anatomy as shown in Fig. 8A.)
a computer system configured to:
store an initial three-dimensional model of the joint and the implant component (Col. 15, lines 10-27, Col. 11, lines 1-24, Janna teaches preoperatively developing a proposed surgical plan based on a three-dimensional model of the joint and can provide a recommended optimal implant size and implant position and orientation based on the three-dimensional model of the joint and patient-specific information. All the data collected over the episode of care at the Surgical Computer as a complete dataset. For each episode of care, a dataset exists that comprises all of the data collected pre-operatively about the patient, all of the data stored by the CASS intra-operatively, and any post-operative data provided by the patient.);
create a digital three-dimensional model of the joint and the implant component based on the two or more two-dimensional digital images (Col. 38, lines 45-65, Col. 11, lines 1-24, Janna teaches a surgical plan which identifies an optimal implant position relative to the 3D anatomical model based on the patient’s anatomy. The planned implants are superimposed onto the joint in the 3D model. Generating the 3D model is intraoperative and effectively real-time or on the order of seconds subsequent to the receipt of the 2D images. The Examiner interprets that “images” means at least two images are captured.);
perform registration between the digital three-dimensional model and the initial three-dimensional model (Col. 17, lines 58-67 and Col. 18, lines 1-6, Col. 28, lines 16-41, Col. 11, lines 18-30, Janna teaches during the registration process, a preoperatively constructed 3D bone model can be displayed to the surgeon. The display is an interactive interface that can dynamically update and display how changes to the surgical plan would impact the procedure and the final position and orientation of implants installed on bone. If the surgical system is robotically assisted, bone removal and bone morphology during the surgery can be monitored in real-time. If the resections made during surgery differ from the surgical plan, the processor optimizes the subsequent placement of additional components to take into account the actual resections that have been made. The Examiner interprets the initial generated preoperative 3D model to be the “initial model” and the intraoperatively updated/changed model to be the “digital 3D model.”) to determine a placement of the implant component in the digital three- dimensional model in relation to a placement of the implant component in the initial three- dimensional model (Col. 11, lines 1-17, Col. 15, lines 28-55, Col. 28, lines 16-41, Janna teaches developing a preoperative proposed surgical plan based on a three-dimensional model of the joint and patient-specific information. The surgical plan provides a recommended implant size, position, and orientation. The high-level pre-operative plan is refined intraoperatively as data is collected during surgery. For example, if the surgeon decides to deviate from the surgical case plan, the altered size, position, and/or orientation of the components are locked, and the global optimization is refreshed based on the new size, position, and/or orientation of the components to find the new ideal position of the other components and the corresponding resections needed to be performed to achieve the newly optimized size, position, and/or orientation of the components. For example, a surgeon may choose to update the size, position, and/or orientation of the femoral implant in TKA. The femoral implant position is locked relative to the anatomy, and the new optimal position of the tibia will be calculated based on the surgeon’s changes to the femoral implant size, position, and/or orientation.);
determine an intraoperative simulated performance metric by simulating movement of the digital three-dimensional model based on the placement of the implant component in the two or more two-dimensional digital images (Col. 19, lines 31-43, Col. 27, lines 25-32, Janna teaches a surgical planning model, which is a biomechanics performance software that simulates the anatomy under various scenarios to determine the optimal way to perform the surgery. For example, for knee replacement surgeries, the surgical planning model measures parameters for functional activities, such as deep knee bends, gait, etc., and selects cut locations on the knee to optimize implant placement. Simulation inputs include implant size, position, and orientation.); and
Janna does not explicitly disclose detecting X-ray radiation to create a two-dimensional digital image of the joint and an implant component; receiv
Boddington is in the same field of art of using intraoperative surgical guidance systems for joint replacement surgeries. Further, Boddington teaches detecting X-ray radiation to create a two-dimensional digital image of the joint and an implant component (Paragraphs [0186], [0078], Fig. 24, Boddington teaches acquiring a fluoroscopic/x-ray intraoperative image where the anteroposterior pelvis implant cup (1001) and stem (1004) are shown as implanted at the hip joint.);
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receiv(Paragraphs [0157-158], Fig. 19A, Boddington teaches tracking anatomical, implant, and instrument considerations in different views as fluoroscopic images are acquired. Fig. 19A shows two different views of the intertrochanteric nail fixed at the hip joint. The nail is tracked in real-time using images and is guided to the correct depth of the lag-screw configuration. The Examiner interprets that the images shown below in Fig. 19A include both an implant component (intertrochanteric nail) which is fixed to the hip joint, and imaged in two different angles/directions.);
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(Paragraphs [0148], [0164], Boddington teaches providing surgical guidance to the surgeon via outputs including implant selection recommendations, implant placement, performance predictions, probability of good outcomes, and failure risk scores. A failure risk score is a confidence percentage recommendation of a suboptimal or optimal performance metric. The output is provided to the surgeon/user in the form of intelligent predictors and scores to support surgical decisions.).
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 Janna by capturing at least 2 two-dimensional images of the joint and the implant component from two different directions and providing an indication to the surgeon regarding the implant’s current placement and the probability of a successful surgical outcome that is taught by Boddington, to make the invention that provides real-time guidance to the surgeon during joint replacement surgery, enabling the surgeon to achieve the optimal implant configuration for the patient’s joint and the best possible biomechanical outcome; thus, one of ordinary skilled in the art would be motivated to combine the references since even with intraoperative fluoroscopic guidance, the placement of an implant during surgery or the reduction of the bone fragment can still be inaccurate. In addition, improper positioning of the acetabular component during hip replacement surgery can lead to problems. For the acetabular component to be positioned and inserted properly relative to the pelvis, it requires the surgeon to continuously know the position of the pelvis during surgery. Unfortunately, the position of the pelvis varies widely during surgery and changes from patient to patient. Therefore, by taking images during surgery and providing real-time information to the surgeon indicating the expected performance, risks and errors can be identified in real-time rather than post-operatively, decreasing the likelihood of requiring revision surgery (Boddington, Paragraph [0005]).
Janna in view of Boddington does not explicitly disclose wherein determining the placement of the implant component in the digital three- dimensional model comprises detecting one or more edges of the implant component in the two or more two-dimensional digital images using an edge detection method.
Giphart is in the same field of art of capturing images of implanted joint replacement components (implants). Further, Giphart teaches wherein determining the placement of the implant component in the digital three- dimensional model (Paragraph [0024], Fig. 3, Giphart teaches the three-dimensional measurement of position and orientation of the implant’s assembly components consists of establishing a geometric relation between the implant’s representation in the stereo radiographic images and a 3D computer model of the implant’s assembly components.)
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comprises detecting one or more edges of the implant component (Paragraphs [0023-24], Fig. 3, Giphart teaches the image information used to calculate the 3D position and orientation may be based on the use of edge detection of the radiographic images. Methods for the 3D measurement of the position and orientation of the implant’s assembly components involve fitting the projection of the 3D computer model to edge or gradient data of the implant’s assembly components visible in the radiographic images. The position and orientation of the 3D computer model of the implant’s assembly components are derived from the radiographic images.) in the two or more two-dimensional digital images (Paragraphs [0021], [0004], [0013], Fig. 3, Giphart teaches the 3D computer models of the implant’s assembly components are obtained and their assembly and pose determined based on a pair of radiographic images of a patient’s implant. See Fig. 3 above, a pair of images.) using an edge detection method (Paragraph [0038], Giphart teaches the radiographic images were filtered using a Canny edge detection filter.).
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 Janna in view of Boddington by detecting edges in a pair of stereo radiography images using Canny edge detection in order to determine the correct placement of the implant component in the three-dimensional model that is taught by Giphart, to make the invention that allows the determination of a patient-specific implant configuration and enables accurate measurements of the pose of the implant based on edge detection; thus, one of ordinary skilled in the art would be motivated to combine the references since there is a need for assessing and monitoring the position and orientation of the implant assembly’s components in order to measure metrics of interest such as settling of assembly components onto each other, benning in, creep, and wear in implants with liners and spaces, and migration of the implant within the bone into which it has been installed (Giphart, Paragraph [0019]). Further, performing edge detection can identify edges belonging to each respective implant assembly component (such as femoral stem, head, and acetabular cup) and therefore, each of the respective positions and orientations of the components may be determined (Giphart, Paragraphs [0038-39]) to build a realistic implant model. Therefore, identifying edges of implant components in the images allows precise spatial alignment between the implant’s physical position and its digital representation in the 3D model, thereby enabling accurate simulations to be performed using the model.
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 2, Janna in view of Boddington in further view of Giphart discloses the system of claim 1, wherein the computer system is configured to determine a preoperative simulated performance metric by simulating movement of the initial three-dimensional model according to a surgical plan (Col. 11, lines 1-17, Col. 15, lines 51-55, Col. 19, lines 28-47, Janna teaches a preoperative “proposed” surgical plan based on a three-dimensional model of the hip joint and patient-specific information, such as the mechanical and anatomical axes of the leg bones, epicondylar axis, femoral neck axis, the dimensions of the femur and hip, the midline axis of the hip joint, etc. The surgical plan can provide a recommended optimal implant size, position, and orientation based on the 3D model and patient-specific information. During model development, the CASS is provided with simulation data for the biomechanics-based model, such as measured parameters for functional activities (deep knee bends and gaits for TKA) to optimize implant performance outcomes for the patient.), the surgical plan comprising a planned placement of the implant component in the initial three-dimensional model (Col. 11, lines 1-17, Janna teaches a surgical plan developed preoperatively based on the 3D model of the patient’s hip and patient-specific information. The surgical plan can provide a recommended optimal implant position and implant orientation based on the 3D model and patient-specific information.)
In regards to Claim 3, Janna in view of Boddington in further view of Giphart 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 [0162-165], [0169-173], Boddington teaches acquiring a radiographic pre-op (reference) image of the subject, either an anteroposterior hip view or an anteroposterior pelvis view. Next, a reference metric is defined by the user, such as 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. Next, during surgery, an anteroposterior radiographic image is obtained (anteroposterior hip or anteroposterior pelvis). The reference image is compared to the intraoperative image and the differences in the images for pelvic tilt and pelvic rotation provide a visual reference for ipsilateral center of rotation for the reaming process during a THA.).
In regards to Claim 4, Janna in view of Boddington in further view of Giphart discloses the system of claim 1, wherein the computer system is configured to update the initial three-dimensional model based on the determined placement of the implant component in the digital three-dimensional model in relation to the initial three-dimensional model (Col. 28, lines 16-33, Janna teaches altering the original surgical case plan during the procedure. The altered size, position, and/or orientation of the components are locked and the global optimization is refreshed based on the new size, position, and/or orientation of the components to find the new ideal position of the other components and the corresponding resections needed to be performed to achieve the newly optimized size, position, and/or orientation of the components. For example, if a surgeon wants to update the size, position, or orientation of the femoral implant in a total knee arthroplasty (TKA), the new optimal position of the tibia will be calculated based on the surgeon’s changes.), thereby determining an updated digital three- dimensional model (Col. 18, lines 2-6, Janna teaches updating and displaying how changes to the surgical plan would impact the final procedure and the final position and orientation of implants installed on bone.).
In regards to Claim 6, Janna in view of Boddington in further view of Giphart discloses the system of claim 1, wherein the intraoperative simulated performance metric is an indication of a risk stratification (Paragraphs [0007], [0083], [0147-149] Fig. 17A, Boddington teaches providing an intra-operative visual display to the user showing surgical guidance, such as intra-operative surgical decision risks. For example, if implant placement and/or alignment does not match the data pattern, it will provide a hazard alert to the user. Fig. 17A shows an example of a varus reduction of the femoral head during a procedure and provides the user with a warning indicating a high risk of failure.).
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In regards to Claim 9, Janna in view of Boddington in further view of Giphart discloses the system of claim 1, wherein the computer system comprises: at least one memory storing program code (Col. 40, lines 24-32, Fig. 13, Janna teaches a main memory (1304) storing computer usable code.) accessible by the at least one processor (Col. 40, lines 24-32, Fig. 13, Janna teaches a processing unit (1303) using computer usable code located in memory, such as the main memory (1304).),
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and configured to cause the at least one processor to: store the initial three-dimensional model of the joint and the implant component (Col. 15, lines 10-27, Col. 11, lines 1-24, Janna teaches preoperatively developing a proposed surgical plan based on a three-dimensional model of the joint and can provide a recommended optimal implant size and implant position and orientation based on the three-dimensional model of the joint and patient-specific information. All the data collected over the episode of care at the Surgical Computer as a complete dataset. For each episode of care, a dataset exists that comprises all of the data collected pre-operatively about the patient, all of the data stored by the CASS intra-operatively, and any post-operative data provided by the patient.); receive the two or more two-dimensional digital images of the joint (Figs. 8B, 9A, 9B, Janna teaches capturing one 2D image (e.g., a second 2D image) substantially orthogonal with respect to at least one other obtained 2D image (e.g., a first 2D image). Fig. 9A depicts a 2D scan of an anterior-posterior view of the knee and Fig. 9B depicts a 2D scan of a lateral view of the knee. The imaging device may be an x-ray emitter.)
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and the implant component captured from two or more respective directions by the X-ray imaging device (Paragraphs [0157-158], Fig. 19A, Boddington teaches tracking anatomical, implant, and instrument considerations in different views as fluoroscopic images are acquired. Fig. 19A shows two different views of the intertrochanteric nail of the implant. The nail is tracked in real-time using images and is guided to the correct depth of the lag-screw configuration.); create the digital three-dimensional model of the joint and the implant component based on the two or more two-dimensional digital images (Col. 11, lines 1-24, Col. 38, lines 45-65, Janna teaches a surgical plan which identifies implant position relative to the 3D anatomical model based on the patient’s anatomy. Generating the 3D model is intraoperative and effectively real-time or on the order of seconds subsequent to the receipt of the 2D images.); perform registration between the digital three-dimensional model and the initial three-dimensional model (Col. 17, lines 58-67 and Col. 18, lines 1-6, Col. 28, lines 16-41, Col. 11, lines 18-30, Janna teaches during the registration process, a preoperatively constructed 3D bone model can be displayed to the surgeon. The display is an interactive interface that can dynamically update and display how changes to the surgical plan would impact the procedure and the final position and orientation of implants installed on bone. If the surgical system is robotically assisted, bone removal and bone morphology during the surgery can be monitored in real-time. If the resections made during surgery differ from the surgical plan, the processor optimizes the subsequent placement of additional components to take into account the actual resections that have been made. The Examiner interprets the initial generated preoperative 3D model to be the “initial model” and the intraoperatively updated/changed model to be the “digital 3D model.”) to determine the location of the implant component in the digital three- dimensional model in relation to the placement of the implant component in the initial three- dimensional model (Col. 11, lines 1-17, Col. 15, lines 28-55, Col. 28, lines 16-41, Janna teaches developing a preoperative “proposed” surgical plan based on a three-dimensional model of the joint and patient-specific information. The surgical plan provides a recommended implant size, position, and orientation. The high-level pre-operative plan is refined intraoperatively as data is collected during surgery. For example, if the surgeon decides to deviate from the surgical case plan, the altered size, position, and/or orientation of the components are locked, and the global optimization is refreshed based on the new size, position, and/or orientation of the components to find the new ideal position of the other components and the corresponding resections needed to be performed to achieve the newly optimized size, position, and/or orientation of the components. For example, a surgeon may choose to update the size, position, and/or orientation of the femoral implant in TKA. The femoral implant position is locked relative to the anatomy, and the new optimal position of the tibia will be calculated based on the surgeon’s changes to the femoral implant size, position, and/or orientation.); 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 two-dimensional digital images (Col. 19, lines 31-43, Col. 27, lines 25-32, Janna teaches a surgical planning model, a biomechanics performance software that simulates the patient’s anatomy under various scenarios to determine the optimal way to perform the surgery. For example, for knee replacement surgeries, the surgical planning model measures parameters for functional activities, such as deep knee bends, gait, etc., and selects cut locations on the knee to optimize implant placement. Inputs to the simulation include implant size, position, and orientation.); and provide the indication to the surgeon (Paragraphs [0154], [0164], Boddington teaches providing surgical guidance via outputs such as implant selection recommendations, implant placement, performance predictions, probability of good outcomes, and failure risk scores. A failure risk score is a confidence percentage recommendation of 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.).
In regards to Claim 10, Janna in view of Boddington in further view of Giphart discloses the system of claim 1, wherein the computer system comprises: a first computing device (Paragraph [0076], Fig. 1A, Boddington teaches an automated intraoperative surgical guidance system (1) having a computing platform (100).)
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comprising: at least one first processor (Paragraph [0078], Fig. 2A, reference character 101, Boddington teaches a computing platform having at least one processor (101).);
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and at least one first memory storing program code accessible by the at least one first processor (Paragraphs [0078], [0099], Fig. 2A, reference character 102, Boddington teaches a computing platform having at least one memory (102). The memory is encoded with computer-readable instructions that implement functionalities of a plurality of modules for the intraoperative surgical guidance system.), and configured to cause the at least one first processor to: store the digital three-dimensional model of the joint and the implant component (Col. 15, lines 10-27, Col. 11, lines 1-24, Janna teaches preoperatively developing a proposed surgical plan based on a three-dimensional model of the joint and can provide a recommended optimal implant size and implant position and orientation based on the three-dimensional model of the joint and patient-specific information. All the data collected over the episode of care at the Surgical Computer as a complete dataset. For each episode of care, a dataset exists that comprises all of the data collected pre-operatively about the patient, all of the data stored by the CASS intra-operatively, and any post-operative data provided by the patient.); receive the two or more two-dimensional digital images of the joint (Figs. 8B, 9A, 9B, Janna teaches capturing one 2D image (e.g., a second 2D image) substantially orthogonal with respect to at least one other obtained 2D image (e.g., a first 2D image). Fig. 9A depicts a 2D scan of an anterior-posterior view of the knee and Fig. 9B depicts a 2D scan of a lateral view of the knee. The imaging device may be an x-ray emitter.) and the implant component captured from two or more respective directions by the X-ray imaging device (Paragraphs [0157-158], Fig. 19A, Boddington teaches tracking anatomical, implant, and instrument considerations in different views as fluoroscopic images are acquired. Fig. 19A shows two different views of the nail (implant) fixed in the hip joint. The nail is tracked in real-time using images and is guided to the correct depth of the lag-screw configuration.); and perform registration between the digital three-dimensional model and the initial three-dimensional model (Col. 17, lines 58-67 and Col. 18, lines 1-6, Col. 28, lines 16-41, Col. 11, lines 18-30, Janna teaches during the registration process, a preoperatively constructed 3D bone model can be displayed to the surgeon. The display is an interactive interface that can dynamically update and display how changes to the surgical plan would impact the procedure and the final position and orientation of implants installed on bone. If the surgical system is robotically assisted, bone removal and bone morphology during the surgery can be monitored in real-time. If the resections made during surgery differ from the surgical plan, the processor optimizes the subsequent placement of additional components to take into account the actual resections that have been made. The Examiner interprets the initial generated preoperative 3D model to be the “initial model” and the intraoperatively updated/changed model to be the “digital 3D model.”) to determine the location of the implant component in the digital three-dimensional model in relation to the placement of the implant component in the initial three-dimensional model (Col. 11, lines 1-17, Col. 15, lines 28-55, Col. 28, lines 16-41, Janna teaches developing a preoperative proposed surgical plan based on a three-dimensional model of the joint and patient-specific information. The surgical plan provides a recommended implant size, position, and orientation. The high-level pre-operative plan is refined intraoperatively as data is collected during surgery. For example, if the surgeon decides to deviate from the surgical case plan, the altered size, position, and/or orientation of the components are locked, and the global optimization is refreshed based on the new size, position, and/or orientation of the components to find the new ideal position of the other components and the corresponding resections needed to be performed to achieve the newly optimized size, position, and/or orientation of the components. For example, a surgeon may choose to update the size, position, and/or orientation of the femoral implant in TKA. The femoral implant position is locked relative to the anatomy, and the new optimal position of the tibia will be calculated based on the surgeon’s changes to the femoral implant size, position, and/or orientation.); and 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 two-dimensional digital images (Col. 19, lines 31-43, Col. 27, lines 25-32, Janna teaches a surgical planning model, which is a biomechanics performance software that simulates anatomy under various scenarios to determine the optimal way to perform the surgery. For example, for TKA, the surgical planning model can measure parameters for functional activities, such as deep knee bends, gait, etc., and select cut locations on the knee to optimize implant placement. Inputs to the simulation software include implant size, position, and orientation.); and a second computing device (Col. 9, lines 11-14, Fig. 1, reference character 150, Janna teaches a surgical computer (150) which provides control instructions to various components of the CASS.)
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comprising: at least one second processor (Col. 9, lines 14-19, Fig. 13, reference characters 1303 and 1305, Janna teaches the surgical computer may be a parallel computing platform that uses multiple central processing units (CPUs) or graphics processing units (GPU) to perform processing.); and at least one second memory storing program code accessible by the at least one second processor (Col. 40, lines 28-34, Fig. 13, reference character 1304, Janna teaches the processes can be performed by the processing unit using computer usable program code, which can be located in memory, such as the main memory (1304).), and configured to cause the at least one second processor to: provide the indication to the surgeon (Col. 10, lines 57-63, Col. 9, lines 11-14, Janna teaches the CASS, which is controlled by the surgical computer, can cause the position and orientation of the trial and final implants vis-à-vis the bone and be displayed to inform the surgeon as to how the trial and final implants orientation and position compare to the surgical plan, and the display can show the implant’s position and orientation as the surgeon manipulates the leg and hip. The Examiner interprets that any information displayed to the surgeon as an “indication” since the claim is silent to the specific definition of “indication.”).
In regards to Claim 13, Janna in view of Boddington in further view of Giphart discloses the system of claim 1, wherein the system comprises a display (Col. 10, lines 8-12, Fig. 1, reference character 125, Janna teaches a CASS with a display (125).),
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and wherein the intraoperative simulated performance metric is provided as a visual output using the display (Col. 17, lines 52-54, Col. 18, lines 20-48, Janna teaches a display which provides any visualization that is needed by the surgeon during surgery. The display provides information about the anatomy of the surgical target region including the location of landmarks, the current state of the anatomy, and future states of the anatomy as the surgical plan progresses. For a TKA, the display provides additional relevant information about the knee joint such as data about the joint’s tension (e.g. ligament laxity) and information concerning rotation and alignment of the joint. The display can depict how the planned implants’ locations and positions will affect the patient as the knee joint is flexed.).
In regards to Claim 16, Janna teaches a computer-implemented method for assisting a surgeon in total joint replacement of a joint of a patient, the method comprising (Col. 3, lines 54-67, Col. 4, lines 1-3, Janna teaches a CASS which uses computers, robotics, and imaging technology to aid surgeons in performing orthopedic surgery procedures such as a TKA or THA.):
storing an initial three-dimensional model of the joint and an implant component (Col. 15, lines 10-27, Col. 11, lines 1-24, Janna teaches preoperatively developing a proposed surgical plan based on a three-dimensional model of the joint and can provide a recommended optimal implant size and implant position and orientation based on the three-dimensional model of the joint and patient-specific information. All the data collected over the episode of care at the Surgical Computer as a complete dataset. For each episode of care, a dataset exists that comprises all of the data collected pre-operatively about the patient, all of the data stored by the CASS intra-operatively, and any post-operative data provided by the patient.);
creating a digital three-dimensional model of the joint and the implant component based on the two or more two-dimensional digital images (Col. 38, lines 45-65, Janna teaches a surgical plan which identifies implant position relative to the 3D anatomical model based on the patient’s anatomy. Generating the 3D model is intraoperative and effectively real-time or on the order of seconds subsequent to the receipt of the 2D images.);
performing registration between the digital three-dimensional model and the initial three-dimensional model (Col. 17, lines 58-67 and Col. 18, lines 1-6, Col. 28, lines 16-41, Col. 11, lines 18-30, Janna teaches during the registration process, a preoperatively constructed 3D bone model can be displayed to the surgeon. The display is an interactive interface that can dynamically update and display how changes to the surgical plan would impact the procedure and the final position and orientation of implants installed on bone. If the surgical system is robotically assisted, bone removal and bone morphology during the surgery can be monitored in real-time. If the resections made during surgery differ from the surgical plan, the processor optimizes the subsequent placement of additional components to take into account the actual resections that have been made. The Examiner interprets the initial generated preoperative 3D model to be the “initial model” and the intraoperatively updated/changed model to be the “digital 3D model.”) to determine a placement of the implant component in the digital three- dimensional model in relation to a placement of the implant component in the initial three- dimensional model (Col. 11, lines 1-17, Col. 15, lines 28-55, Col. 28, lines 16-41, Janna teaches developing a preoperative proposed surgical plan based on a three-dimensional model of the joint and other patient-specific information. The surgical plan provides a recommended implant size, position, and orientation. The high-level pre-operative plan is refined intraoperatively as data is collected during surgery. For example, if the surgeon decides to deviate from the surgical case plan, the altered size, position, and/or orientation of the components are locked, and the global optimization is refreshed based on the new size, position, and/or orientation of the components to find the new ideal position of the other components and the corresponding resections needed to be performed to achieve the newly optimized size, position, and/or orientation of the components. For example, a surgeon may choose to update the size, position, and/or orientation of the femoral implant in TKA. The femoral implant position is locked relative to the anatomy, and the new optimal position of the tibia will be calculated based on the surgeon’s changes to the femoral implant size, position, and/or orientation.);
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 two or more two-dimensional digital images (Col. 19, lines 31-43, Col. 27, lines 25-32, Janna teaches a surgical planning model, which is a biomechanics performance software that simulates the anatomy under various scenarios to determine the optimal way to perform the surgery. For example, for TKA, the surgical planning model can measure parameters for functional activities (deep knee bends, gait, etc.), and select cut locations on the knee to optimize implant placement. Simulation inputs include implant size, position, and orientation.);
Janna does not explicitly disclose receiving two or more two-dimensional digital images of the joint and the implant component during the total joint replacement surgery; wherein determining the placement of the implant component in the digital three- dimensional model comprises detecting one or more edges of the implant component in the two or more two-dimensional digital images using an edge detection method; and providing an indication to the surgeon of the intraoperative simulated performance metric as an assessment of a current placement of the implant component.
Boddington is in the same field of art of using intraoperative surgical guidance for joint replacement surgeries. Further, Boddington teaches receiving two or more two-dimensional digital images of the joint and the implant component during the total joint replacement surgery (Paragraphs [0157-158], Fig. 19A, Boddington teaches tracking anatomical, implant, and instrument considerations in different views as fluoroscopic images are acquired. Fig. 19A shows two different views of the intertrochanteric nail of the implant. The nail is tracked in real-time using images and is guided to the correct depth of the lag-screw configuration.) (Paragraphs [0148], [0164], Boddington teaches providing surgical guidance via outputs such as implant selection recommendations, implant placement, performance predictions, probability of good outcomes, and failure risk scores. A failure risk score is a confidence percentage recommendation of 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.).
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 Janna by capturing two or more intraoperative images of the joint and implant component and providing an alert to the surgeon indicating a risk associated with the implants current placement and/or reduction of the bones that is taught by Boddington, to make the invention that creates an awareness in a specific situation and provides a hazard alert to the user; thus, one of ordinary skilled in the art would be motivated to combine the references since an error at any stage will increase the potential for a sub-optimal outcome and potential surgical failure and identifying these risks in real-time can help achieve an optimal outcome and avoid the need for future revision surgery (Boddington, Paragraph [0005]).
Janna in view of Boddington does not explicitly disclose wherein determining the placement of the implant component in the digital three- dimensional model comprises detecting one or more edges of the implant component in the two or more two-dimensional digital images using an edge detection method.
Giphart is in the same field of art of capturing images of implanted joint replacement components (implants). Further, Giphart teaches wherein determining the placement of the implant component in the digital three- dimensional model (Paragraph [0024], Fig. 3, Giphart teaches the three-dimensional measurement of position and orientation of the implant’s assembly components consists of establishing a geometric relation between the implant’s representation in the stereo radiographic images and a 3D computer model of the implant’s assembly components.) comprises detecting one or more edges of the implant component (Paragraphs [0023-24], Fig. 3, Giphart teaches the image information used to calculate the 3D position and orientation may be based on the use of edge detection of the radiographic images. Methods for the 3D measurement of the position and orientation of the implant’s assembly components involve fitting the projection of the 3D computer model to edge or gradient data of the implant’s assembly components visible in the radiographic images. The position and orientation of the 3D computer model of the implant’s assembly components are derived from the radiographic images.) in the two or more two-dimensional digital images (Paragraphs [0021], [0004], [0013], Fig. 3, Giphart teaches the 3D computer models of the implant’s assembly components are obtained and their assembly and pose determined based on a pair of radiographic images of a patient’s implant.) using an edge detection method (Paragraph [0038], Giphart teaches the radiographic images were filtered using a Canny edge detection filter.).
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 Janna in view of Boddington by detecting edges using Canny edge detection in a pair of stereo radiography images in order to determine the placement of the implant component in the three-dimensional model that is taught by Giphart, to make the invention that allows the determination of a patient-specific implant configuration and enables accurate measurements of the pose of the implant based on edge detection; thus, one of ordinary skilled in the art would be motivated to combine the references since there is a need for assessing and monitoring the position and orientation of the implant assembly’s components in order to measure metrics of interest such as settling of assembly components onto each other, benning in, creep, and wear in implants with liners and spaces, and migration of the implant within the bone into which it has been installed (Giphart, Paragraph [0019]). Further, performing edge detection can identify respective edges belonging to each implant assembly component (such as femoral stem, head, and acetabular cup) and therefore, each of the respective positions and orientations of the components may be determined (Giphart, Paragraphs [0038-39]). Therefore, identifying edges of implant components in the images allows precise spatial alignment between the implant’s physical position and its digital representation in the 3D model, thereby enabling accurate simulations.
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, Janna in view of Boddington in further view of Giphart discloses the method of claim 16, comprising determining a preoperative simulated performance metric by simulating movement of the initial three-dimensional model according to a surgical plan (Col. 11, lines 1-17, Col. 15, lines 51-55, Col. 19, lines 28-47, Janna teaches a preoperative proposed surgical plan based on a three-dimensional model of the hip joint and other patient-specific information, such as the mechanical and anatomical axes of the leg bones, epicondylar axis, femoral neck axis, the dimensions of the femur and hip, the midline axis of the hip joint, etc. The surgical plan can provide a recommended optimal implant size, position, and orientation based on the 3D model and patient-specific information. A biomechanics-based model of patient anatomy then generates simulation data, such as measured parameters for functional activities (deep knee bends and gaits for TKA), to be considered by the CASS in developing preoperative procedures to optimize implant performance outcomes for the patient.), the surgical plan comprising a planned placement of the implant component in the initial three-dimensional model (Col. 11, lines 1-17, Janna teaches a surgical plan developed preoperatively based on the 3D model of the patient’s hip and patient-specific information. The surgical plan can provide a recommended optimal implant position and implant orientation based on the 3D model and patient-specific information.).
In regards to Claim 18, Janna in view of Boddington in further view of Giphart 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 [0162-165], [0169-173], Boddington teaches acquiring a radiographic pre-op (reference) image of the subject, either an anteroposterior hip view or an anteroposterior pelvis view. Next, a reference metric is defined by the user such as 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 (intraoperatively), an anteroposterior radiographic image is obtained which can be either anteroposterior hip or anteroposterior pelvis. For the reaming process during THA, the reference image is compared to the intraoperative image and the differences in the images for pelvic tilt and pelvic rotation provide a visual reference for ipsilateral center of rotation.).
In regards to Claim 19, Janna in view of Boddington in further view of Giphart discloses the method of claim 16, wherein the initial three-dimensional model is updated based on the determined placement of the implant component in the digital three-dimensional model in relation to the initial three-dimensional model (Col. 28, lines 16-41, Janna teaches the surgeon altering the surgical case plan at any time prior to or during the procedure. For example, if a surgeon decides the size, position, and/or orientation of the femoral implant in a TKA needs to be updated intraoperatively, the new optimal position of the tibia will be calculated considering the surgeon’s changes to the femoral implant size, position, and/or orientation), thereby determining an updated digital three-dimensional model (Col. 18, lines 2-6, Janna teaches updating and displaying how changes to the surgical plan would impact the final procedure and the final position and orientation of implants installed on bone.).
In regards to Claim 21, Janna in view of Boddington in further view of Giphart discloses the method of claim 16, wherein the intraoperative performance metric is an indication of a risk stratification (Paragraphs [0007], [0083], [0147-149] Fig. 17A, Boddington teaches providing an intra-operative visual display to the user showing surgical guidance, such as intra-operative surgical decision risks. For example, if implant placement and/or alignment does not match the data pattern, it will provide a hazard alert to the user. Fig. 17A shows an example of a varus reduction of the femoral head during a procedure and provides the user with a warning indicating a high risk of failure.).
In regards to Claim 24, Janna in view of Boddington in further view of Giphart discloses the method of claim 16, wherein the intraoperative simulated performance metric is provided as a visual output on a display (Col. 17, lines 52-54, Col. 18, lines 20-48, Janna teaches a display which provides any visualization that is needed by the Surgeon during surgery. The display provides the surgeon with information about the anatomy of the surgical target region including the location of landmarks, the current state of the anatomy, and future states of the anatomy as the surgical plan progresses. For a TKA, the display provides information about the knee joint such as data about the joint’s tension (e.g. ligament laxity), rotation, and alignment. The display can depict how the planned implants’ locations and positions will affect the patient as the knee joint is flexed.).
In regards to Claim 26, Janna discloses a non-transitory computer-readable storage medium storing instructions that when executed by a computing device (Claim 7, Janna teaches a non-transitory computer readable medium having stored thereon instructions comprising executable code, executed by one or more processors.), cause the computing device to perform one or more operations (The Examiner interprets “one or more” operations to mean only one of the following operations is required in order to meet the claim limitation. For example, a reference disclosing only one of the listed operations, such as “storing an initial three-dimensional model of the joint and an implant component” would be sufficient to reject the claim. However, citations have been included for each of the claim limitations for completeness.), comprising:
storing an initial three-dimensional model of the joint and an implant component (Col. 15, lines 10-27, Col. 11, lines 1-24, Janna teaches preoperatively developing a proposed surgical plan based on a three-dimensional model of the joint and can provide a recommended optimal implant size and implant position and orientation based on the three-dimensional model of the joint and patient-specific information. All the data collected over the episode of care at the Surgical Computer as a complete dataset. For each episode of care, a dataset exists that comprises all of the data collected pre-operatively about the patient, all of the data stored by the CASS intra-operatively, and any post-operative data provided by the patient.);
creating a digital three-dimensional model of the joint and the implant component based on the two or more two-dimensional digital images (Col. 38, lines 45-65, Janna teaches a surgical plan which identifies implant position relative to the 3D anatomical model based on the patient’s anatomy. Generating the 3D model is intraoperative and effectively real-time or on the order of seconds subsequent to the receipt of the 2D images.);
performing registration between the digital three-dimensional model and the initial three-dimensional model (Col. 17, lines 58-67 and Col. 18, lines 1-6, Col. 28, lines 16-41, Col. 11, lines 18-30, Janna teaches during the registration process, a preoperatively constructed 3D bone model can be displayed to the surgeon. The display is an interactive interface that can dynamically update and display how changes to the surgical plan would impact the procedure and the final position and orientation of implants installed on bone. If the surgical system is robotically assisted, bone removal and bone morphology during the surgery can be monitored in real-time. If the resections made during surgery differ from the surgical plan, the processor optimizes the subsequent placement of additional components to take into account the actual resections that have been made. The Examiner interprets the initial generated preoperative 3D model to be the “initial model” and the intraoperatively updated/changed model to be the “digital 3D model.”) to determine a placement of the implant component in the digital three- dimensional model in relation to a placement of the implant component in the initial three- dimensional model (Col. 11, lines 1-17, Col. 15, lines 28-55, Col. 28, lines 16-41, Janna teaches developing a preoperative proposed surgical plan based on a three-dimensional model of the joint and patient-specific information. The surgical plan provides a recommended implant size, position, and orientation. The high-level pre-operative plan is refined intraoperatively as data is collected during surgery. For example, if the surgeon decides to deviate from the surgical case plan, the altered size, position, and/or orientation of the components are locked, and the global optimization is refreshed based on the new size, position, and/or orientation of the components to find the new ideal position of the other components and the corresponding resections needed to be performed to achieve the newly optimized size, position, and/or orientation of the components. For example, a surgeon may choose to update the size, position, and/or orientation of the femoral implant in TKA. The femoral implant position is locked relative to the anatomy, and the new optimal position of the tibia will be calculated based on the surgeon’s changes to the femoral implant size, position, and/or orientation.);
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 two or more two-dimensional digital images (Col. 19, lines 31-43, Col. 27, lines 25-32, Janna teaches a surgical planning model, a biomechanics performance software that simulates the anatomy under various scenarios to determine the optimal way to perform the surgery. For example, for TKA, the surgical planning model can measure parameters for functional activities, such as deep knee bends, gait, etc., and select cut locations on the knee to optimize implant placement. Simulation inputs include implant size, position, and orientation.); and
Janna does not explicitly disclose receiving two or more two-dimensional digital images of the joint and the implant component during the total joint replacement surgery; wherein determining the placement of the implant component in the digital three- dimensional model comprises detecting one or more edges of the implant component in the two or more two-dimensional digital images using an edge detection method; and providing an indication to the surgeon of the intraoperative simulated performance metric as an assessment of a current placement of the implant component.
Boddington is in the same field of art of intraoperative surgical guidance for joint replacement surgeries. Further, Boddington teaches receiving two or more two-dimensional digital images of the joint and the implant component during the total joint replacement surgery (Paragraphs [0157-158], Fig. 19A, Boddington teaches tracking anatomical, implant, and instrument considerations in different views as fluoroscopic images are acquired. Fig. 19A shows two different views of the nail (implant) fixed in the hip joint. The nail is tracked in real-time using images and is guided to the correct depth of the lag-screw configuration.); (Paragraphs [0148], [0164], Boddington teaches providing surgical guidance via outputs such as implant selection recommendations, implant placement, performance predictions, probability of good outcomes, and failure risk scores. A failure risk score is a confidence percentage recommendation of 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.).
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 Janna by capturing two or more x-ray images of the joint and implant component and providing a risk associated with the current implant component placement to the surgeon that is taught by Boddington, to make the invention that creates awareness in a specific situation and provides a hazard alert to the user to avoid a suboptimal or poor outcome; thus, one of ordinary skilled in the art would be motivated to combine the references since an error at any stage increases the potential for a sub-optimal outcome and potential surgical failure and identifying errors in real-time can promote a successful procedure and subsequent positive outcome (Boddington, Paragraph [0005]).
Janna in view of Boddington does not explicitly disclose wherein determining the placement of the implant component in the digital three- dimensional model comprises detecting one or more edges of the implant component in the two or more two-dimensional digital images using an edge detection method.
Giphart is in the same field of art of capturing images of implanted joint replacement components (implants). Further, Giphart teaches wherein determining the placement of the implant component in the digital three- dimensional model (Paragraph [0024], Fig. 3, Giphart teaches the three-dimensional measurement of position and orientation of the implant’s assembly components consists of establishing a geometric relation between the implant’s representation in the stereo radiographic images and a 3D computer model of the implant’s assembly components.) comprises detecting one or more edges of the implant component (Paragraphs [0023-24], Fig. 3, Giphart teaches the image information used to calculate the 3D position and orientation may be based on the use of edge detection of the radiographic images. Methods for the 3D measurement of the position and orientation of the implant’s assembly components involve fitting the projection of the 3D computer model to edge or gradient data of the implant’s assembly components visible in the radiographic images. The position and orientation of the 3D computer model of the implant’s assembly components are derived from the radiographic images.) in the two or more two-dimensional digital images (Paragraphs [0021], [0004], [0013], Fig. 3, Giphart teaches the 3D computer models of the implant’s assembly components are obtained and their assembly and pose determined based on a pair of radiographic images of a patient’s implant.) using an edge detection method (Paragraph [0038], Giphart teaches the radiographic images were filtered using a Canny edge detection filter.).
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 Janna in view of Boddington by detecting edges using Canny edge detection in a pair of stereo radiography images in order to determine the placement of the implant component in the three-dimensional model that is taught by Giphart, to make the invention that allows the determination of patient-specific implant configuration and enables accurate measurements of the pose of the implant based on edge detection; thus, one of ordinary skilled in the art would be motivated to combine the references since there is a need for assessing and monitoring the position and orientation of the implant assembly’s components in order to measure metrics of interest such as settling of assembly components onto each other, benning in, creep, and wear in implants with liners and spaces, and migration of the implant within the bone into which it has been installed (Giphart, Paragraph [0019]). Further, performing edge detection can identify edges belonging to each implant assembly component (such as femoral stem, head, and acetabular cup) and therefore, each of the respective positions and orientations of the components may be determined (Giphatt, Paragraphs [0038-39]). Therefore, identifying edges of implant components in the images allows precise spatial alignment between the implant’s physical position and its digital representation in the 3D model, thereby enabling accurate simulations.
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 5, 7, and 20 are rejected under 35 U.S.C. 103(a) as being unpatentable over Janna et al. (U.S. Patent No. 11,931,107 B1, hereafter referred to as Janna) in view of Boddington et al. (U.S. Patent Pub. No. 20220265233 A1, hereafter referred to as Boddington) in further view of Giphart et al. (U.S. Patent Pub. No. 20180342315 A1, hereafter referred to as Giphart) in further view of McKinnon et al. (U.S. Patent Pub. No. 2020/0275976 A1, hereafter referred to as McKinnon).
Regarding Claim 5, Janna in view of Boddington in further view of Giphart teaches the system of claim 1.
Janna in view of Boddington in further view of Giphart does not explicitly disclose wherein the intraoperative simulated performance metric is associated with the digital three-dimensional model.
McKinnon is in the same field of art of optimizing joint arthroplasty procedures by developing a surgical plan with planned implantation orientation and position (pose) of a knee or hip implant/replacement joint. Further, McKinnon teaches wherein the intraoperative simulated performance metric is associated with the digital three-dimensional model (Paragraphs [0177-178], [0180], Fig. 3E, McKinnon teaches a Response and Rationale Interface (375) which provides an animation of the anatomy of interest during the performance measurement activity (e.g. deep knee bend). This animation may be provided as an output of the anatomical modeling software performing the optimization. The optimization can be performed intraoperatively. The Response and Rationale Interface (375) also includes a response screen (385) that displays plots for various performance or condition measures (e.g., measure v flexion angle).).
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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 Janna in view of Boddington in further view of Giphart by generating intraoperative simulation performance metrics that is taught by McKinnon, to make the invention that provides simulated performance data to the surgeon to assist them in determining the optimal position and orientation for the joint implant component; thus, one of ordinary skilled in the art would be motivated to combine the references since providing radiographical/x-ray images to a 3D biomechanical simulation can help better predict the optimal implant positions and orientations and can better determine how changes in the position and orientation of the implant can affect the mechanics of the replacement knee (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 7, Janna in view of Boddington in further view of Giphart discloses the system of claim 6.
Janna in view of Boddington in further view of Giphart 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 joint arthroplasty procedures by developing a surgical plan with planned implantation orientation and position (pose) of a knee or hip implant/replacement joint. Further, McKinnon teaches wherein the risk stratification is indicative of a risk associated with multiple predicted postoperative movements by the patient (Paragraphs [0236-0237], Figs. 12A-12C, McKinnon teaches an anatomical modeling software for virtually simulating the positions and orientations of implants in relation to bony anatomy throughout a variety of activities that a patient may experience post-surgery. For example, standard stability checks or activities that pose a high risk for impingement and dislocation such as crossing legs while seated, deep flexion while sitting, and hyperextension while standing. Following the simulated “exam” of activities, the collected range of motion (ROM) data can be represented by a ROM plot as shown in Fig. 12A. The software may also determine an impinged ROM where abnormal and wearing contact exists between the patient’s anatomy and the implant components as shown in Fig. 12B. Fig. 12C demonstrates a recommendation for a “safe” range of positions for seating a hip implant in an acetabulum.).
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 Janna in view of Boddington in further view of Giphart by using the 3D model biomechanical simulation software to simulate multiple predicted post-operative movements that is taught by McKinnon, to make the invention that virtually simulates the position and orientation of the implants in relation to the patient’s bony anatomy throughout a variety of activities that the patient may experience post-surgery to determine a safe range of positions/locations for placing an implant (for example, seating a hip implant in the acetabulum); 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 (position and orientation) of the implant components affect the mechanics of the replacement joint by incorporating the relationship between multiple variables throughout the joint’s range of motion and exemplary forces of a given activity (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 20, Janna in view of Boddington in further view of Giphart teaches the method of claim 16.
Janna in view of Boddington in further view of Giphart does not explicitly disclose wherein the intraoperative simulated performance metric is associated with the digital three-dimensional model.
McKinnon is in the same field of art of art of optimizing joint arthroplasty procedures by developing a surgical plan with planned implantation orientation and position (pose) of a knee or hip implant/replacement joint. Further, McKinnon teaches wherein the intraoperative simulated performance metric is associated with the digital three-dimensional model (Paragraph [0177-178], Fig. 3E, McKinnon teaches a Response and Rationale Interface (375) that provides an animation of the anatomy of interest during the performance measurement activity (e.g. deep knee bend). This animation may be provided as an output of the anatomical modeling software performing the optimization.).
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 Janna in view of Boddington in further view of Giphart by generating intraoperative simulation performance metrics that is taught by McKinnon, to make the invention that provides performance data to the surgeon to help them determine the optimal position and orientation for the implant component; thus, one of ordinary skilled in the art would be motivated to combine the references since providing radiographical/x-ray images into a 3D biomechanical simulation can help better predict the optimal implant positions and orientations and can better determine how changes in the position and orientation of the implant can affect the mechanics of the replacement knee (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.
Claims 14 and 25 are rejected under 35 U.S.C. 103(a) as being unpatentable over Janna et al. (U.S. Patent No. 11,931,107 B1, hereafter referred to as Janna) in view of Boddington et al. (U.S. Patent Pub. No. 2022/0265233 A1, hereafter referred to as Boddington) in further view of Giphart et al. (U.S. Patent Pub. No. 20180342315 A1, hereafter referred to as Giphart) in further view of Mahfouz et al. (NPL “A robust method for registration of three-dimensional knee implant models to two-dimensional fluoroscopy images”, 2003, hereafter referred to as Mahfouz).
Rgearding Claim 14, Janna in view of Boddington in further view of Giphart teaches the system of claim 1, wherein determining the placement of the implant component in the digital three-dimensional model (Paragraph [0024], Fig. 3, Giphart teaches the three-dimensional measurement of position and orientation of the implant’s assembly components consists of establishing a geometric relation between the implant’s representation in the stereo radiographic images and a 3D computer model of the implant’s assembly components.) comprises detecting one or more edges of the implant component (Paragraphs [0023-24], Fig. 3, Giphart teaches the image information used to calculate the 3D position and orientation may be based on the use of edge detection of the radiographic images. Methods for the 3D measurement of the position and orientation of the implant’s assembly components involve fitting the projection of the 3D computer model to edge or gradient data of the implant’s assembly components visible in the radiographic images. The position and orientation of the 3D computer model of the implant’s assembly components are derived from the radiographic images.) in the two or more two-dimensional digital images (Paragraphs [0021], [0004], [0013], Fig. 3, Giphart teaches the 3D computer models of the implant’s assembly components are obtained and their assembly and pose determined based on a pair of radiographic images of a patient’s implant.) using a (Paragraph [0038], Giphart teaches the radiographic images were filtered using a Canny edge detection filter.) applied to the two or more two-dimensional digital images (Paragraph [0023], Fig. 3, Giphart teaches edge detection of the radiographic images (pair of stereo images).).
Janna in view of Boddington in further view of Giphart does not explicitly disclose a Sobel edge detection operator.
Mahfouz is in the same field of art of determining the correct position/pose of an implant in a 3D model based on 2D captured images. Further, Mahfouz teaches a Sobel edge detection operator (B. Matching Algorithm, Fig. 8 (gradient image), Mahfouz teaches an edge enhancement operation (Sobel) is performed to estimate the norm of the local image gradient. See Fig. 8 (right), gradient image, shows enhanced edges for the x-ray image.).
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 Janna in view of Boddington in further view of Giphart by replacing the Canny edge detector with a Sobel edge detector that is taught by Mahfouz, to make the invention that identifies the edges of implant component’s using a Sobel edge detector in order to determine the pose of the implant in the captured image; thus, one of ordinary skilled in the art would be motivated to combine the references since Sobel edge detectors are known to be simpler, more time-efficient, and less computationally expensive than Canny edge detectors. Therefore, by replacing the Canny edge detector with a Sobel edge detector to detect one or more images of the implant component, time-efficiency may be improved and computational expenses may be reduced.
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 25, Janna in view of Boddington in further view of Giphart teaches the method of claim 16, wherein determining the placement of the implant component in the digital three-dimensional model (Paragraph [0024], Fig. 3, Giphart teaches the three-dimensional measurement of position and orientation of the implant’s assembly components consists of establishing a geometric relation between the implant’s representation in the stereo radiographic images and a 3D computer model of the implant’s assembly components.) comprises detecting one or more edges of the implant component (Paragraphs [0023-24], Fig. 3, Giphart teaches the image information used to calculate the 3D position and orientation may be based on the use of edge detection of the radiographic images. Methods for the 3D measurement of the position and orientation of the implant’s assembly components involve fitting the projection of the 3D computer model to edge or gradient data of the implant’s assembly components visible in the radiographic images. The position and orientation of the 3D computer model of the implant’s assembly components are derived from the radiographic images.) in the two or more two-dimensional digital images (Paragraphs [0021], [0004], [0013], Fig. 3, Giphart teaches the 3D computer models of the implant’s assembly components are obtained and their assembly and pose determined based on a pair of radiographic images of a patient’s implant.) using a (Paragraph [0038], Giphart teaches the radiographic images were filtered using a Canny edge detection filter.) applied to the two or more two-dimensional digital images (Paragraph [0023], Fig. 3, Giphart teaches edge detection of the radiographic images (pair of stereo images).).
Janna in view of Boddington in further view of Giphart does not explicitly disclose a Sobel edge detection operator.
Mahfouz is in the same field of art of determining the correct position/pose of an implant in a 3D model based on 2D captured images. Further, Mahfouz teaches a Sobel edge detection operator (B. Matching Algorithm, Fig. 8 (gradient image), Mahfouz teaches an edge enhancement operation (Sobel) is performed to estimate the norm of the local image gradient. See Fig. 8 (right), gradient image, shows enhanced edges for the x-ray image.).
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 Janna in view of Boddington in further view of Giphart by replacing the Canny edge detector with a Sobel edge detector that is taught by Mahfouz, to make the invention that identifies the edges of implant component’s using a Sobel edge detector in order to determine the pose of the implant in the captured image; thus, one of ordinary skilled in the art would be motivated to combine the references since Sobel edge detectors are known to be simpler, more time-efficient, and less computationally expensive than Canny edge detectors. Therefore, by replacing the Canny edge detector with a Sobel edge detector to detect one or more images of the implant component, time-efficiency may be improved and computational expenses may be reduced.
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.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Otto et al. (U.S. Patent Pub. No. 20170340389 A1) teaches a method of generating implant position orientation data for use in planning an arthroplasty procedure on a patient bone including a lateral femur area, proximal femur area, and a posterior femur area. The method includes obtaining patient data associated with at least a portion of the patient bone, generating a 3D femur model from the patient data and obtaining a 3D femoral implant model including an anterior flange portion having a superior edge and an anterior bone resection contact surface being planar and adjacent to the superior edge, and determining a position and orientation of the femoral implant model relative to the patient femur model. Implant component position and orientation data is generated based on the determined position and orientation of the femoral implant model relative to the patient femur model, and the implant component position and orientation data can be utilized by a navigation system during the arthroplasty procedure.
Schipper et al. (U.S. Patent Pub. No. 20220249248 A1) teaches planning tools for surgery, particularly for total hip arthroplasty. Images of musculoskeletal structure of a patient may be displayed together and via co-registration and spatial transformations, 3D implants or other objects may be rendered and overlaid in the same position correctly with respect to each image. The 3D implant may be fit to an existing implant in the patient and moved to other positions to measure an existing position or plan for an initial or new position.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SYDNEY L BLACKSTEN whose telephone number is (571)272-7120. The examiner can normally be reached 8:30am-4:30pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Oneal Mistry can be reached at 313-446-4912. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/SYDNEY L BLACKSTEN/Examiner, Art Unit 2674
/ONEAL R MISTRY/Supervisory Patent Examiner, Art Unit 2674
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