DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Applicant's arguments, filed 4/7/2026, have been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
Applicants have amended their claims, filed 4/7/2026, and therefore rejections newly made in the instant office action have been necessitated by amendment.
Claims 1-24 and 37-41 are the currently pending claims . Claims 25-36 have previously been canceled; claim 41 has been newly added.
Claim Objections
Claims 37 and 41 are objected to because of the following informalities:
In claim 37, lines 7-8: "for placement of and prior to implanting of one or more implants" contains a grammatical informality, and should be revised to "for placement of one or more implants and prior to implanting the one or more implants”; and
In claim 41, line 2: "an intra-operative surgical plan" is inconsistent with the term "intraoperative" used in claim 37 and elsewhere, and should be revised to "an intraoperative surgical plan" for consistency.
Appropriate correction is required.
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.
Claims 1-4, 6-9, 11-13, 15, 17-18, 21-24, 37-38, and 40-41 are rejected under 35 U.S.C. 103 as being unpatentable over Schmidt et al. (US 20200261156 A1), hereto referred as Schmidt, in view of Nawana et al. (US-20140088990-A1), hereto referred as Nawana, and further in view of Galbusera et al. (Galbusera, Fabio et al. “Planning the Surgical Correction of Spinal Deformities: Toward the Identification of the Biomechanical Principles by Means of Numerical Simulation.” Frontiers in bioengineering and biotechnology 3 (2015): 178. Web.), hereto referred as Galbusera, and further in view of Anderson et al. (US-20100191071-A1), hereto referred as Anderson.
Regarding claim 1, Schmidt teaches a computer-implemented method for modeling a surgical correction for a patient (Schmidt, Abstract; ¶[0020]: "Disclosed are systems and methods for constructing a three dimensional simulation of the curvature of a boney structure, such as the spine", and using that model and medical data "to assist surgeons with determining the nature of a corrective procedure, predict postoperative changes in the curvature of the bony structure, the nature of the hardware necessary for use during the procedure and customizations of the hardware for the particular morphology of the patient", demonstrating computer-implemented modeling of a spine for planning a patient-specific surgical correction; ¶[0014]: "the computer system... construct[s] a three dimensional simulation of each vertebral body in the spine and morph[s] the three-dimensional simulation into a realistic visualization of the patient morphology by translating, angulating and rotating the models of the vertebral bodies, perform[s] predictive analysis on the three-dimensional simulation, and transmit[s] via the communications interface for review and user input", showing that the modeling is performed by a computer system and is used for predictive surgical analysis and user review).
Also regarding claim 1, Schmidt does not fully teach obtaining patient data intraoperatively during a surgical procedure, the patient data including image data of one or more regions of a spine of the patient. Schmidt teaches obtaining patient data including image data of one or more regions of the patient's spine because Schmidt teaches a model comprising "a set of spatial coordinates derived from images of the bony structure captured in at least two different planes" and teaches obtaining coronal and sagittal X-ray images for generating the spine model (Schmidt, Abstract; ¶[0020]; Figs. 3 and 5). However, Schmidt does not fully teach obtaining the patient data intraoperatively during a surgical procedure.
Nawana teaches obtaining patient data intraoperatively during a surgical procedure, wherein the patient data includes image data of one or more regions of a spine of the patient. Nawana teaches that the images used during the procedure can include "images gathered in real-time with the positioning, e.g., skin surface mapping, fluoroscopy, ultrasound, or intraoperative CT images" and that "[t]he patient can be imaged throughout the procedure in real time to help ensure that the patient is properly positioned during the procedure" (Nawana, ¶[0222], showing real-time intraoperative imaging of the patient during the procedure). Nawana additionally teaches that "the procedure analysis module 230 can be configured to analyze gathered images of a patient to generate a 3D model of the patient's anatomy based on the images" and that "[t]he images can include previously gathered images, e.g., fluoroscopy, MRI, or CT images stored in the diagnosis database 310, and/or images gathered in real-time, e.g., fluoroscopy, ultrasound, or intraoperative CT images" (Nawana, ¶[0245], showing generation of a patient anatomical model using intraoperative image data).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Schmidt in view of Nawana such that Schmidt's patient data, including image data of one or more regions of the spine, is obtained intraoperatively during a surgical procedure. This modification would have been possible because Schmidt already obtains patient image data and generates a patient-specific spine model from such image data, while Nawana provides a compatible intraoperative surgical support system that obtains real-time patient images, including fluoroscopy, ultrasound, or intraoperative CT images, and generates a 3D anatomical model from gathered patient images. The benefit of the combination would have been improved intraoperative accuracy and surgical decision support by allowing Schmidt's patient-specific correction model and surgical planning framework to be informed by current intraoperative image data and patient positioning information.
Also regarding claim 1, the modified Schmidt does not fully teach generating, using at least one computer modeling module, a virtual model of the spine in a corrected anatomical configuration, wherein the at least one computer modeling module is programmed to model soft tissue of the patient based on the patient data. Rather, the modified Schmidt teaches generating, using at least one computer modeling module, a virtual model of the spine in a corrected anatomical configuration because "[t]he process starts with a model of the spine, including each of the vertebral bodies of interest", "Morphing module 2204 uses a point cloud model for each vertebral body and can generate a simulation of a patient's morphology in a point cloud for the entire spine", and "[t]he three-dimensional model includes a preoperative curve 802 and a postoperative curve 804" where "the surgeon corrected the spine to put it in proper alignment" (Schmidt, ¶¶[0142], [0143], [0104]). Schmidt further teaches that its disclosed modeling and morphing techniques are not limited to bony vertebral bodies because "disc structures" and "other non-bony structures within the anatomy of a subject" "may similarly be modeled and morphed utilizing the system and techniques disclosed herein" (Schmidt, ¶[0173]). However, Schmidt does not fully teach that the computer modeling module is programmed to model soft tissue of the patient based on the patient data with an explicit soft-tissue representation in the simulation.
Galbusera teaches a patient-specific computer spine simulation in which soft tissues are explicitly represented within the model, including modeling spinal ligaments and intervertebral disks within the simulation framework. Galbusera discloses that "Six ligament groups are modeled as non-linear springs: anterior longitudinal ligament, posterior longitudinal ligament, flaval ligament, interspinous ligament, supraspinous ligament, and capsular ligaments" (Galbusera, p. 4, "Instrumented Spine Model"). Galbusera further discloses creating intervertebral disks as part of the model, stating that "[w]hen the volume meshes of two adjacent vertebrae have been generated, the intervertebral disk is automatically created" (Galbusera, p. 3, "Instrumented Spine Model").
Anderson further teaches creating a patient-specific anatomy model substantially based on imaging data and generating a three-dimensional model of the patient's spine from images, where the model includes layered anatomical features such as "ligaments, tendons, [and] muscles" (Anderson, ¶¶[0143], [0157]).
Nawana further teaches that the anatomical visualization may include "tissue (e.g., soft tissue), bone, nerves, intervertebral disc material" and that the visualization can be patient specific, "similar to that discussed above regarding modeling of the patient for pre-op electronic simulation" (Nawana, ¶[0242]). Nawana also teaches generating a 3D anatomical model based on gathered images, including real-time fluoroscopy, ultrasound, or intraoperative CT images (Nawana, ¶[0245]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the modified Schmidt in view of Galbusera, Anderson, and Nawana to program the at least one computer modeling module to model soft tissue of the patient based on the patient data. This modification would have been possible because Schmidt already employs computer-based three-dimensional spine simulation and expressly contemplates extending its modeling and morphing to "disc structures" and "other non-bony structures", Galbusera provides a known, implementable approach for explicitly representing soft-tissue structures within a spine simulation, including ligament groups and intervertebral disks, Anderson confirms that image-derived patient anatomy models may include soft tissue layers such as ligaments, tendons, and muscles, and Nawana teaches generating patient-specific anatomical models from gathered patient images, including real-time intraoperative images. The benefit of the combination would have been improved predictive accuracy and surgical planning reliability by enabling Schmidt's simulation to account for the biomechanical influence of patient soft tissue structures on spinal behavior during correction using patient-specific image data.
Also regarding claim 1, the modified Schmidt does not fully teach identifying one or more soft tissue surgical steps for adjusting intraoperative mobility of vertebrae of the spine to access a target site of the spine for spinal device placement to achieve the corrected anatomical configuration. Rather, the modified Schmidt teaches treating soft tissue surgical steps, including ligament resection and ligament cutting, as surgical data that affects predicted spinal movement and surgical outcome because Schmidt teaches that medical data may include "[t]he surgical approach" and "ligaments resected", and because Schmidt teaches that "if the transverse ligament is cut on the concave side (intraoperative data), the probability of success of the surgery for the new patient may drop to 73.5%" and that "some or all of the relevant medical data may be used to predict movement of the new patient's spine after surgery" (Schmidt, ¶¶[0122], [0128], showing that ligament resection and ligament cutting are soft tissue surgical steps used as surgical data tied to predicted spinal movement and outcome modeling). Schmidt also teaches hardware-related planning for proper alignment because computer 110 may analyze X-ray images and medical data "to determine an appropriate method of performing a spinal surgery and/or the parameters of the medical device to ensure that proper alignment is achieved", and material module 2205 guides the surgeon in choosing hardware capable of achieving the desired correction (Schmidt, ¶¶[0085], [0162], [0166]). However, Schmidt does not fully teach identifying soft tissue surgical steps that adjust intraoperative mobility of vertebrae to access a target site of the spine for spinal device placement.
Galbusera teaches soft tissue release or removal steps used to facilitate spinal correction. Galbusera teaches that a user may "simulate discectomies at selected levels, as commonly done in scoliosis surgery to facilitate the correction of the curves" and that, in such case, "the intervertebral disk is completely removed at the chosen levels, as well as the anterior and posterior longitudinal ligaments" (Galbusera, p. 5, "Planning of the Deformity Correction Surgery"). Thus, Galbusera teaches that removal of soft tissue structures, including intervertebral disk tissue and longitudinal ligaments, is used to facilitate spinal correction by increasing or adjusting the ability of the spinal segments to move toward the corrected configuration.
Nawana teaches spinal surgical planning and intraoperative tracking for accessing a target spinal site and placing spinal devices. Nawana teaches that "a trajectory of lateral approach can be very precisely determined so as to access a target vertebra while avoiding nerve damage" and identifies "implantation of one or more percutaneous screws" as a spinal surgical procedure in which precise patient positioning is important (Nawana, ¶[0221]). Nawana further teaches that "[a] vertebra is circled in the display 42 for ease of identification of a Surgical target 44" (Nawana, ¶[0181]). Nawana also teaches that aspects of a selected surgical procedure that can be simulated include "an access point on the patient", "a path through and/or retraction of tissue and nervous structures", "soft tissue removal", "tissue and structure movement", "correction", "movement due to indirect decompression", and "placement of all implants" (Nawana, ¶[0183]). Nawana further teaches tracking actions of instruments in the actual surgical space, including "removal of bone, movement of tissue, insertion of material (e.g., a bone screw, interbody cage, biologic, combination treatment, etc.)" (Nawana, ¶[0237]).
The Examiner is not relying on Nawana's access trajectory alone as the claimed soft tissue surgical step. Rather, Schmidt teaches soft tissue surgical steps such as ligament cutting and ligament resection that affect predicted spinal movement, Galbusera teaches discectomy with removal of intervertebral disk and longitudinal ligaments to facilitate correction, and Nawana teaches simulation of a procedure including tissue retraction, soft tissue removal, tissue and structure movement, correction, indirect decompression movement, and implant placement. Thus, in the proposed combination, the soft tissue surgical step is the release, resection, removal, or retraction of soft tissue that changes the mobility or relative movement of the vertebrae. Nawana's target-vertebra access and implant-placement teachings are relied upon to show the surgical context in which that adjusted mobility and tissue movement are used to access the target spinal site and place or insert the spinal device.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the modified Schmidt in view of Galbusera and Nawana such that the one or more soft tissue surgical steps are selected or identified to adjust intraoperative mobility of vertebrae of the spine to access a target site of the spine for spinal device placement. This modification would have been possible because Schmidt already treats soft tissue surgical steps, such as ligament cutting and resection, as variables affecting predicted spinal movement and as surgical data tied to movement toward a corrected anatomical configuration; Galbusera teaches that soft tissue removal, including discectomy and removal of longitudinal ligaments, facilitates correction of spinal curves; and Nawana provides a compatible surgical planning and intraoperative tracking framework involving target vertebra access, access points, soft tissue removal, tissue retraction, tissue and structure movement, correction, implant placement, and insertion of spinal materials such as bone screws and interbody cages. A person of ordinary skill in the art would have recognized that combining these teachings would allow the surgical plan to identify a soft tissue release, resection, removal, or retraction step that changes vertebral mobility or relative vertebral movement, uses the changed mobility or tissue movement to establish or improve access to the target spinal site, and permits placement or insertion of a spinal device at that site. The benefit of the combination would have been improved surgical planning and intraoperative decision support by linking soft tissue release or removal to predicted vertebral mobility, using that predicted mobility to assess access and device-placement feasibility, and allowing the surgeon to select or update soft tissue surgical steps based on whether the resulting vertebral mobility and tissue movement provide appropriate access to a target spinal site for spinal device placement.
Also regarding claim 1, the modified Schmidt does not fully teach predicting the intraoperative mobility of vertebrae of the spine attributable to the one or more soft tissue surgical steps based on a simulation performed using the virtual model and the modeled soft tissue of the patient. Rather, the modified Schmidt teaches prediction of spinal movement based on soft tissue surgical step data because Schmidt teaches that "if the transverse ligament is cut on the concave side (intraoperative data), the probability of success of the surgery for the new patient may drop to 73.5%" and that "some or all of the relevant medical data may be used to predict movement of the new patient's spine after surgery" (Schmidt, ¶[0128]). Further, Galbusera and Anderson teach modeled soft tissue of the patient, as discussed above. However, the modified Schmidt does not fully teach predicting intraoperative mobility of vertebrae attributable to the one or more soft tissue surgical steps based on a simulation performed using the virtual model and the modeled soft tissue of the patient.
Nawana teaches predicting movement of tissues and structures attributable to surgical steps based on simulation with modeled soft tissue. Nawana teaches that a simulated surgery may include "soft tissue removal, tissue and structure movement, correction, movement due to indirect decompression" and "placement of all implants" (Nawana, ¶[0183]). Nawana further teaches running a simulation that predicts movement attributable to procedural steps using modeled soft tissue, stating that the system can "perform predictive volumetric modeling of soft tissue movement, stretch, removal (e.g., of a herniated disc), and change based on each step of the simulated procedure" and that the user can "see in real time with the simulation how tissue and other structures will move based on each step of the procedure" (Nawana, ¶[0184]).
Galbusera further supports that the simulation can be performed using a virtual spine model with modeled soft tissue structures and can output vertebral mobility metrics based on the simulation because Galbusera teaches that "the finite element simulation is performed" and that simulation results include "nodal displacements" and "global orientations of the vertebrae before and after correction" extracted from the simulation (Galbusera, Fig. 6; p. 6, "Postprocessing and Data Analysis"). Galbusera also teaches simulating discectomies with removal of intervertebral disk tissue and longitudinal ligaments to facilitate correction of the spinal curves, as discussed above (Galbusera, p. 5, "Planning of the Deformity Correction Surgery").
Anderson also supports accounting for soft tissue surgical steps in modeled motion because Anderson teaches that when supporting tissues "will be cut or resected", the model "takes this into account in modeling the resultant motion sequences" (Anderson, ¶[0078]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the modified Schmidt in view of Nawana, Galbusera, and Anderson to predict the intraoperative mobility of vertebrae of the spine attributable to the one or more soft tissue surgical steps based on a simulation performed using the virtual model and the modeled soft tissue of the patient. This modification would have been possible because Schmidt already uses a virtual spine modeling framework and already treats a soft tissue surgical step, ligament cutting, as an input tied to predicted spine movement, Galbusera provides an implementable method for representing soft tissue within the simulation model and simulating soft tissue removal to facilitate correction, Anderson confirms that the model may account for supporting tissues that will be cut or resected when modeling resultant motion sequences, and Nawana provides an implementable simulation workflow that predicts how tissues and structures move attributable to each step of a procedure using predictive volumetric modeling of soft tissue behavior. The benefit of the combination would have been reducing complication risk and mechanical failure by enabling the planned correction to be evaluated using numerical simulation that predicts loads and stresses in the instrumentation and biological tissues, while also allowing step-based simulation of soft-tissue change and movement that affects the correction, access pathway, and device-placement feasibility, so that the surgeon can select safer strategies and hardware choices during the procedure before actual performance of the relevant surgical step or delivery of the spinal device.
Also regarding claim 1, the modified Schmidt does not fully teach updating a surgical plan intraoperatively for achieving the corrected anatomical configuration, wherein the surgical plan includes at least one of the one or more soft tissue surgical steps that facilitates movement of the vertebrae to deliver a spinal device to the target site to achieve the corrected anatomical configuration. Rather, it teaches generating a surgical plan for achieving a corrected anatomical configuration because the three-dimensional model may be analyzed "to determine an appropriate treatment plan", computer 110 may analyze X-ray images and medical data "to determine an appropriate method of performing a spinal surgery and/or the parameters of the medical device to ensure that proper alignment is achieved", and material module 2205 is a planning tool that guides the surgeon in choosing hardware capable of achieving the desired correction (Schmidt, ¶¶[0083], [0085], [0162], [0166]). Schmidt also teaches that soft tissue surgical steps, such as ligament cutting or resection, affect predicted spinal movement (Schmidt, ¶¶[0122], [0128]). Further, Galbusera and Anderson teach modeled soft tissue of the patient, Galbusera teaches discectomy and longitudinal ligament removal to facilitate spinal correction, and Nawana teaches target vertebra access, access points, soft tissue removal, tissue and structure movement, correction, placement of implants, and insertion of spinal materials such as bone screws and interbody cages, as discussed above. However, the modified Schmidt does not fully teach the intraoperative updating aspect of this limitation.
Nawana teaches intraoperative plan tracking and modification in the context of tissue movement, target-site access, and spinal device placement. Nawana teaches that the simulated surgery can include "an access point on the patient", "a path through and/or retraction of tissue and nervous structures", "soft tissue removal", "tissue and structure movement", "correction", and "placement of all implants" (Nawana, ¶[0183]). Nawana further teaches that the user can save simulated procedures at various points throughout the simulation, repeat aspects of the procedure more than once, test different surgical products, and test the suitability of different access points (Nawana, ¶[0183]). Nawana also teaches that actual surgical tracking may include "movement of tissue" and "insertion of material (e.g., a bone screw, interbody cage, biologic, combination treatment, etc.)" (Nawana, ¶[0237]). Further, Nawana teaches that the plan tracking module provides feedback "throughout actual performance the surgical procedure as measured against at least one model, e.g., a saved simulated procedure and/or a pre-programmed procedure" and allows personnel "to continually validate and confirm that the steps being taken in the surgery line up with a saved pre-op plan" (Nawana, ¶[0238]). Nawana further teaches triggering alerts when deviations occur, including "not enough tissue and/or bone removed", "too much tissue and/or bone removed", or "an instrument has entered an undesirable area of the anatomy based on the pre-op plan" (Nawana, ¶[0238]). In response, Nawana teaches that "the system 10 can allow a user, e.g., the Surgeon, to access the Surgical procedure planning module 218 to modify the saved simulation for the surgical procedure" and that "[i]n this way, the Surgeon can prepare a plan on the fly with consideration to unexpected circumstances that arise during the procedure and/or to test different surgical techniques and/or medical devices prior to actually performing the techniques and/or actually using the medical devices" (Nawana, ¶[0239]). Thus, Nawana teaches modifying the surgical plan intraoperatively in response to surgical progress or deviations, where the modified plan can account for tissue movement, soft tissue removal, access-point suitability, surgical product or device selection, and implant/device placement at the surgical target.
These Nawana teachings are relied upon as part of the same surgical simulation and tracking workflow. Nawana describes a selected simulated procedure that can include an access point, a path through or retraction of tissue and nervous structures, soft tissue removal, tissue and structure movement, correction, and placement of implants; actual surgical tracking that includes movement of tissue and insertion of spinal material; comparison of the actual procedure against a saved simulated or pre-programmed procedure; and modification of the saved simulation on the fly when intraoperative circumstances or deviations arise. Thus, Nawana is not being relied upon for isolated, unrelated disclosures, but for an integrated workflow in which soft tissue movement or removal, target-site access, device placement, intraoperative tracking, deviation feedback, and plan modification operate together.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the modified Schmidt in view of Nawana to update the surgical plan intraoperatively for achieving the corrected anatomical configuration, wherein the surgical plan includes at least one soft tissue surgical step that facilitates movement of the vertebrae to deliver a spinal device to the target site to achieve the corrected anatomical configuration. This modification would have been possible because Schmidt already provides a patient-specific spine correction model, a correction-planning framework, predictive use of ligament cutting or resection as variables affecting spinal movement, and hardware-related planning for achieving proper alignment; Galbusera teaches that discectomy and removal of longitudinal ligaments facilitate correction by increasing the ability to correct the spinal curve; and Nawana provides a compatible intraoperative surgical support framework that simulates tissue retraction, soft tissue removal, tissue and structure movement, correction, access-point suitability, implant placement, and insertion of spinal materials, while also allowing the surgeon to modify the saved simulation on the fly during the procedure. A person of ordinary skill in the art would have had reason to combine these teachings so that, when intraoperative imaging or tracking indicates that the planned release, resection, removal, or retraction has produced too little or too much tissue movement or vertebral mobility for the intended access path or device placement, the surgeon can update the plan before delivery of the spinal device. The benefit of the combination would have been improved intraoperative decision support by linking soft tissue release or removal to predicted vertebral mobility, using that predicted mobility to assess access and device-placement feasibility, and revising the plan intraoperatively when the actual surgical progress deviates from the predicted access or placement conditions.
Regarding claim 2, the modified Schmidt teaches that method further comprises: simulating the intraoperative mobility using the virtual model for viewing by a user(Schmidt, ¶[0033]: “…the method further includes obtaining at least one four-dimensional model for a similar spine, analyzing the three-dimensional model … to predict movement of the spine”, shows simulating mobility by using a model of motion over time to predict spine movement; ¶[0105]: “FIG. 9 … illustrating a three-dimensional model of a spine over a fourth dimension, e.g. time … FIG. 10 … a four-dimensional model of the movement of a head … These models … may be used to predict the change in curvature of a spine …”, explains that Schmidt’s simulation uses time-based modeling to predict spine movement during correction; ¶[0083]: “The resulting three-dimensional model of the curvature of the spine may also be used to morph a pre-existing model of a normal spine to simulate the morphology of the patient for pre-operative visualization and to further simulate the predictive outcomes visually of multiple degrees of corrective surgery”, shows the simulation is performed for visual review of predicted correction outcomes; ¶[0136]: “Computer 11 using display 12 may display … resulting in a three-dimensional simulation of the vertebral bodies in a patient spine”, confirms the simulation is viewable by a user).
Regarding claim 3, the modified Schmidt does not fully teach that the method further comprises: receiving user selection of at least one of the one or more soft tissue surgical steps; and updating the simulation to represent the intraoperative mobility attributable to the selected one or more soft tissue surgical steps. The modified Schmidt teaches receiving surgeon inputs to modify a three-dimensional spine simulation to enable prediction of surgical results (Schmidt, ¶[0005], ¶[0122], ¶[0128], ¶[0136], ¶[0138], ¶[0140], ¶[0163]). The modified Schmidt also teaches that soft tissue surgical steps are relevant to its predictive framework, including that historical medical data can include whether “ligaments [were] resected” (Schmidt, ¶[0122]). However, the modified Schmidt does not fully teach receiving user selection of at least one of the one or more soft tissue surgical steps and updating the simulation to represent the intraoperative mobility attributable to the selected one or more soft tissue surgical steps.
Galbusera teaches receiving user selection of soft tissue surgical steps and updating a simulation to represent the resulting vertebral movement outcomes, stating that “the user has the possibility to simulate discectomies at selected levels” and that “the intervertebral disk is completely removed at the chosen levels, as well as the anterior and posterior longitudinal ligaments” (Galbusera, p.5, 'Planning of the Deformity Correction Surgery'). Galbusera further explains that after this selected configuration is applied, “The simulation of the correction maneuver is then performed” and that “nodal displacements are obtained and used to deform the mesh in the 3D viewer” while vertebral orientations are calculated “based on the original and deformed coordinates” (Galbusera, p.5, 'Planning of the Deformity Correction Surgery'; p. 6, 'Postprocessing and Data Analysis'). This directly evidences updating the simulation, after user selection of a soft tissue surgical step, to represent mobility-relevant outcomes produced by the simulation.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the modified Schmidt in view of Galbusera to include receiving user selection of at least one of the one or more soft tissue surgical steps and updating the simulation to represent the intraoperative mobility attributable to the selected one or more soft tissue surgical steps. This would have been feasible because the modified Schmidt already receives surgeon inputs to alter its patient-specific simulation for predictive planning, and Galbusera provides a directly compatible simulation implementation in the same field where the user selects soft tissue surgical steps (discectomy and ligament removal at selected levels) and the simulation is updated by modifying the modeled disk and ligaments at the selected levels. The benefit of the combination would have been reducing surgical planning uncertainty and complication risk by enabling the modified Schmidt system to evaluate alternative correction strategies while accounting for mobility-relevant soft tissue procedures that change flexibility and loading during the correction maneuver.
Regarding claim 4, the modified Schmidt teaches that the method further comprises: generating one or more surgical steps for the surgical plan; and virtually simulating the one or more surgical steps for viewing by a physician (Schmidt, [0083]: "The resulting three-dimensional model of the curvature of the spine may be compared to three-dimensional models of the curvature of other spines and analyzed in view of medical data related to the spine to determine an appropriate treatment plan... and to further simulate the predictive outcomes visually of multiple degrees of corrective surgery", shows generating a treatment plan (i.e., surgical plan) that includes multiple degrees of corrective surgery (i.e., surgical steps) and virtually simulating those surgical steps for viewing by the physician; [0136]: "The computer 11 may then analyze the X-ray images and the medical data to determine instructions for constructing a simulation of the spinal morphology of a patient's vertebral body for pre-operative visualization and to further simulate the predictive outcomes visually of multiple degrees of corrective surgery", shows determining instructions as surgical steps for the surgical plan and virtually simulating those surgical steps for pre-operative visualization by the physician).
Regarding claim 6, the modified Schmidt teaches that the method further comprises: predicting post-operative spinal mobility based on the one or more soft tissue surgical steps being performed (Schmidt, ¶[0105]: “FIG . 9 is an exemplary graph illustrating a three dimensional model of a spine over a fourth dimension , e.g. time , from a preoperative state to a postoperative state at times 901 , 903 , 905 , 907 , 909 , and FIG . 10 is an example graph illustrating a four - dimensional model of the movement of a head from a preoperative state to a postoperative state… these models of the curvature of the spine over time may be used to predict the change in curvature of a spine of a similarly situated patient who is being prepared for spinal - alignment surgery”, shows predicting post-operative spinal mobility; Schmidt, ¶[0128]: “But if the transverse ligament is cut on the concave side ( intraoperative data ) , the probability of success of the surgery for the new patient may drop to 73.5 % … some or all of the relevant medical data may be used to predict movement of the new patient's spine after surgery”, shows a soft tissue surgical step is used as relevant medical data for predicting post-operative spine movement).
Regarding claim 7, the modified Schmidt teaches that the method further comprises: providing a physician viewing of the intraoperative simulation (Schmidt, ¶[0136]: “Computer 11 using display 12 may display the X-ray images and the medical data to assist a clinician in planning for and performing a spinal surgery”, shows providing viewing to a clinician on a display); and receiving input, from the physician, wherein the input is used to generate the surgical plan (Schmidt, ¶[0005]: “a systems and methods for constructing a three dimensional simulation of the curvature of a patient spine… further modified based on data input from a surgeon to enable better prediction of post-surgical results”, shows receiving surgeon input used to modify the simulation for predictive planning; Schmidt, ¶[0136]: “During this process, the computer 11 may interact with a surgeon mobile device 15”, shows interaction with a surgeon device during simulation and planning; Schmidt, ¶[0140]: “materials module 2205 enables the surgeon to input patient specific data which can be used to modify the three-dimensional simulation”, shows receiving physician input to modify the simulation used to generate the plan).
Also regarding claim 7, the modified Schmidt does not fully teach generating an intraoperative simulation of the intraoperative mobility of vertebrae of the spine attributable to the one or more soft tissue surgical steps. Rather, the modified Schmidt teaches constructing a patient-specific simulation of the spine (including vertebral bodies) and simulating predictive outcomes of corrective surgery based on patient images and medical data (Schmidt, ¶[0136]), but it does not expressly teach that the simulation is an intraoperative simulation whose intraoperative mobility outputs are attributable to the one or more soft tissue surgical steps.
Nawana teaches a surgical-procedure simulation that performs predictive volumetric modeling of soft tissue behavior “based on each step of the simulated procedure” and allows the user to see “in real time with the simulation how tissue and other structures will move based on each step of the procedure” (Nawana, ¶[0184]). Nawana further teaches making the simulation “visible and/or accessible in an OR” by allowing the user to pull up a saved simulation during an actual surgical procedure (Nawana, ¶[0219]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the modified Schmidt in view of Nawana to generate an intraoperative simulation of the intraoperative mobility of vertebrae of the spine attributable to the one or more soft tissue surgical steps. It would have been obvious and feasible to combine because the modified Schmidt already provides the spine-modeling and simulation framework for corrective surgery planning, and Nawana provides a compatible simulation approach that models soft tissue movement and removal on a per-step basis and makes the simulation accessible in the operating room, such that the modified Schmidt’s simulated mobility outcomes could be produced and presented intraoperatively and attributed to the selected soft tissue steps. The benefit of the combination would have been improved intraoperative decision support by enabling the surgeon to visualize, during surgery, predicted vertebral and surrounding-structure movement associated with particular soft tissue step selections, thereby supporting selection and sequencing of soft tissue steps to achieve the intended correction with reduced trial-and-error during the procedure.
Regarding claim 8, the modified Schmidt does not fully teach that the method further comprises: receiving physician input for an ancillary surgical procedure, wherein the one or more soft tissue surgical steps are selected based on the physician input, wherein the ancillary surgical procedure is part of the surgical plan. Rather, the modified Schmidt teaches receiving surgeon input that can be used to modify a three-dimensional simulation used for planning spinal correction (Schmidt, ¶[0122], ¶[0128], ¶[0136], ¶[0138], ¶[0140], ¶[0163] ), but the modified Schmidt does not expressly disclose receiving physician input for an ancillary surgical procedure and selecting one or more soft tissue surgical steps based on that ancillary-procedure input as part of the surgical plan.
Galbusera teaches receiving user (physician) input for an ancillary surgical procedure by disclosing that “the user has the possibility to simulate discectomies at selected levels, as commonly done in scoliosis surgery to facilitate the correction of the curves” (Galbusera, p. 5, 'Planning of the Deformity Correction Surgery'). Galbusera further teaches that, once that ancillary procedure is selected, the simulation correspondingly applies associated soft tissue surgical steps, stating that “the intervertebral disk is completely removed at the chosen levels, as well as the anterior and posterior longitudinal ligaments” (Galbusera, p. 5, 'Planning of the Deformity Correction Surgery'), thereby evidencing that the soft tissue surgical steps are selected/applied based on the physician’s ancillary-procedure input. Galbusera also teaches that “the desired surgical correction of the deformity is planned manually with a dedicated graphical user interface” (Galbusera, p. 5, 'Planning of the Deformity Correction Surgery'), demonstrating that the ancillary procedure is part of the surgical plan.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the modified Schmidt in view of Galbusera to receive physician input for an ancillary surgical procedure, select one or more soft tissue surgical steps based on the physician input, and include the ancillary surgical procedure as part of the surgical plan. This would have been feasible because the modified Schmidt already provides a computer-implemented planning workflow in which surgeon input is received and used to modify a three-dimensional simulation used for planning spinal correction (Schmidt, ¶[0140]), and Galbusera provides a directly compatible surgical planning and simulation approach in which the physician selects an ancillary procedure (discectomy) and the simulation applies the associated soft tissue surgical steps (disk and ligament removal) at the selected levels within the correction planning workflow (Galbusera, p. 5. 'Planning of the Deformity Correction Surgery'). The benefit of the combination would have been improving surgical planning completeness and usability by enabling the planning workflow to incorporate surgeon-selected ancillary procedures that increase spinal flexibility for correction, along with the associated soft tissue surgical steps needed to implement those procedures during the planned correction.
Regarding claim 9, the modified Schmidt teaches that the method further comprises: simulating a joint mobility of the patient's spine (Schmidt, ¶[0083]: “The resulting three-dimensional model of the curvature of the spine may be compared to three-dimensional models of the curvature of other spines and analyzed in view of medical data related to the spine to determine an appropriate treatment plan… The resulting three-dimensional model of the curvature of the spine may also be used to morph a pre-existing model of a normal spine to simulate the morphology of the patient for pre-operative visualization and to further simulate the predictive outcomes visually of multiple degrees of corrective surgery”, which teaches simulating spinal motion and deformation behavior that inherently reflects joint mobility; ¶[0136]: “The computer 11 may then analyze the X-ray images and the medical data to determine instructions for constructing a simulation of the spinal morphology of a patient's vertebral body for pre-operative visualization and to further simulate the predictive outcomes visually of multiple degrees of corrective surgery”, further confirming simulation of spinal morphology and movement); however, the modified Schmidt does not fully teach: selecting one or more of the one or more soft tissue surgical steps based on the simulated joint mobility; and predicting post-operative joint mobility associated with the selected one or more soft tissue surgical steps. Rather, the modified Schmidt teaches simulating spinal morphology and motion for planning corrective surgery, including simulations that reflect changes in curvature and spinal movement over time (Schmidt, ¶[0083], ¶[0105], ¶[0136]). The modified Schmidt further teaches that soft tissue surgical steps such as ligament cutting are relevant variables that affect predicted spinal movement and post-operative outcomes (Schmidt, ¶[0122], ¶[0128]). However, the modified Schmidt does not expressly link the prediction to user-selected steps.
Galbusera teaches a computer-based spinal simulation system in which the user explicitly selects soft tissue surgical steps (such as discectomies and ligament removal) at selected levels, and the simulation is then performed to evaluate the resulting spinal mobility and correction behavior (Galbusera, p. 5, “Planning of the Deformity Correction Surgery”). By allowing the user to simulate these soft tissue procedures at specific joints and levels, Galbusera teaches selection of soft tissue surgical steps based on simulated joint mobility and further teaches that mobility outcomes can be evaluated following those selections.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the modified Schmidt in view of Galbusera to select one or more of the soft tissue surgical steps based on simulated joint mobility and to predict post-operative joint mobility associated with the selected soft tissue surgical steps. This modification would have been feasible because the modified Schmidt already provides a patient-specific spinal simulation framework that predicts spinal movement and post-operative mobility, and Galbusera provides a compatible and well-known approach for interactively selecting soft tissue surgical steps within a spinal simulation and evaluating the resulting mobility changes at specific joints. The benefit of the combination would have been enabling more precise and patient-specific surgical planning by allowing the surgeon to evaluate how different soft tissue surgical step selections affect joint-level mobility and post-operative motion outcomes before surgery.
Regarding claim 11, the modified Schmidt does not expressly teach that the one or more soft tissue surgical steps includes a decompression procedure wherein the one or more soft tissue surgical steps include a decompression procedure. Rather, the modified Schmidt teaches a surgical planning framework for spinal procedures detailing preoperative simulation of surgeries, tissue changes, and soft tissue adjustments (Schmidt, ¶[0122]-[0128]), but it does not expressly describe decompression as one of the soft tissue surgical steps
Nawana teaches decompression within the simulation workflow by disclosing that simulated aspects can include “movement due to indirect decompression” (Nawana, ¶[0183]) and that the simulation can “perform predictive Volumetric modeling of soft tissue movement, stretch, removal (e.g., of a herniated disc)” and “predict neural responses and/or changes based upon a predicted amount of retraction and/or decompression preformed” (Nawana, ¶[0184]), which provides decompression procedures as explicit modeled surgical steps
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the modified Schmidt in view of Nawana to include a decompression procedure as one of the one or more soft tissue surgical steps because the modified Schmidt already contemplates soft tissue surgical steps as variables in its surgical planning framework and Nawana provides explicit decompression procedure modeling within a simulation-based planning workflow. The combination would have been feasible because both references are directed to computer-based surgical planning and simulation for spinal procedures and incorporate procedural step modeling within the simulation, such that incorporating Nawana’s decompression modeling into the modified Schmidt’s planning framework would have been a routine software integration choice for one of ordinary skill in the art. The benefit of the combination would have been improved surgical planning and outcome prediction by enabling Schmidt’s framework to explicitly model decompression-related mobility changes and neural-response effects during planning, thereby supporting more informed selection of soft tissue steps and improved patient outcomes.
Regarding claim 12, the modified Schmidt does not fully teach that the method further comprises predicting a nerve decompression score for the decompression procedure. Rather, the modified Schmidt teaches the broad framework of surgical planning for spinal procedures, including simulation of surgeries, tissue changes, and soft tissue adjustments including nerve decompression, as shown above in claim 11, Additionally, Schmidt’s system does already have a built in scoring system to assess potential plans (Schmidt, ¶[0115]), but does not disclose predicting a nerve decompression score.
Nawana not only frames “inadequate decompression of a nerve” as a surgical quality issue (Nawana, ¶[0016]) but also operationalizes this concern through its outcome tracking. Specifically, Nawana describes that the system can assess and track patient pain scores in relation to surgical treatments and normalize those scores against historical patient populations and outcomes (Nawana, ¶[0032]). This demonstrates that decompression sufficiency is not treated as an abstract variable but directly tied to a quantitative, patient-reported metric. When coupled with its simulation capability, “the SPP module simulation can utilize historical surgical and literature data to predict neural responses and/or changes based upon a predicted amount of retraction and/or decompression performed” (Nawana, ¶[0183]-[0184]), Nawana effectively discloses the framework for a predictive nerve decompression score. The linkage of predicted decompression effects with normalized pain outcome tracking shows that Nawana’s system already functions as a predictive scoring mechanism, aligning with the claimed decompression score (as outlined in ¶[0020] of the Instant Application).
It would have been prima facie obvious before the effective filing date of the claimed invention to have further modified the modified Schmidt in view of Nawana to predict a nerve decompression score for the decompression procedure. The modified Schmidt provides the computational surgical planning framework and Nawana provides the predictive assessment of decompression sufficiency and outcomes. A person of ordinary skill in the art would have found it obvious to combine these teachings because each reference is directed to improving surgical planning and outcomes in spinal surgery. Combining Nawana’s predictive decompression modeling with the modified Schmidt’s planning/predicting system would have been straightforward, as all systems operate on imaging data and surgical simulations. The combination improves patient outcomes by allowing prediction and quantification of nerve decompression success during surgical planning, thereby reducing risks of inadequate decompression, improving decision-making, and enhancing surgical precision.
Regarding claim 13, the modified Schmidt does not fully disclose generating a plurality of decompression plans; determining a decompression score for each decompression plan; receiving selection of one of the decompression plans; and generating a decompression surgical plan based on the selected decompression plan. Rather, the modified Schmidt teaches a computer-implemented framework that models the spine and generates a score based on comparisons between models and medical data (Schmidt, ¶[0115]), but it does not teach generating a plurality of decompression plans, determining a decompression score for each decompression plan, receiving selection of one of the decompression plans, and generating a decompression surgical plan based on the selected decompression plan.
Nawana teaches a multi-option, outcome-driven planning workflow in which the treatment options module “can include a plurality of possible treatment options” and determines which options are associated with a diagnosis based on prior treatments and outcomes, evaluating attributes including “pain levels … bone removed, disc removed … reduction in pain … and functional outcome,” to “provide more accurate recommendations of treatments” (Nawana, ¶[0148]). Consistent with determining a score for each plan, the options are “provided to the user with historic success rates” (Nawana, ¶[0150]). Nawana further teaches receiving selection of one of the plans by disclosing “choosing at least a one of the plans having a most desired effect” (Nawana, ¶[0022]) and teaches generating a plan based on the selected plan by disclosing that the system can “recommend an optimized plan for the selected Surgical procedure” (Nawana, ¶[0175]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the modified Schmidt in view of Nawana to generate a plurality of decompression plans, determine a decompression score for each decompression plan, receive selection of one of the decompression plans, and generate a decompression surgical plan based on the selected decompression plan because Schmidt already generates a score based on model and medical-data comparisons and Nawana teaches presenting multiple candidate plans with associated outcome-based performance information and user selection resulting in an optimized plan. The combination would have been feasible because both references are directed to computer-based surgical planning and evaluation using patient data and outcome information, and incorporating Nawana’s multi-plan selection and per-option performance evaluation into Schmidt’s scoring framework would have been a routine design choice for one of ordinary skill in the art. The benefit of the combination would have been improved surgical planning by enabling comparison and selection among multiple candidate plans using quantified performance information, thereby supporting more informed plan selection and improved patient outcomes.
Regarding claim 15, Schmidt teaches a computer-implemented method for modeling a surgical correction (Schmidt, Abstract; ¶[0020]: "Disclosed are systems and methods for constructing a three dimensional simulation of the curvature of a boney structure, such as the spine", and using that model and medical data "to assist surgeons with determining the nature of a corrective procedure, predict postoperative changes in the curvature of the bony structure, the nature of the hardware necessary for use during the procedure and customizations of the hardware for the particular morphology of the patient", demonstrating computer-implemented modeling of a spine for planning a patient-specific surgical correction; ¶[0014]: "the computer system... construct[s] a three dimensional simulation of each vertebral body in the spine and morph[s] the three-dimensional simulation into a realistic visualization of the patient morphology by translating, angulating and rotating the models of the vertebral bodies, perform[s] predictive analysis on the three-dimensional simulation, and transmit[s] via the communications interface for review and user input", showing that the modeling is performed by a computer system and is used for predictive surgical analysis and user review).
Also regarding claim 15, Schmidt does not fully teach obtaining patient data of a patient intraoperatively during a surgical procedure, the patient data including image data of one or more regions of a patient's spine. Schmidt teaches obtaining patient data including image data of one or more regions of the patient's spine because Schmidt teaches a model comprising "a set of spatial coordinates derived from images of the bony structure captured in at least two different planes" and teaches obtaining coronal and sagittal X-ray images for generating the spine model (Schmidt, Abstract; ¶[0020]; Figs. 3 and 5). However, Schmidt does not fully teach obtaining the patient data intraoperatively during a surgical procedure.
Nawana teaches obtaining patient data intraoperatively during a surgical procedure, wherein the patient data includes image data of one or more regions of a spine of the patient. Nawana teaches that the images used during the procedure can include "images gathered in real-time with the positioning, e.g., skin surface mapping, fluoroscopy, ultrasound, or intraoperative CT images" and that "[t]he patient can be imaged throughout the procedure in real time to help ensure that the patient is properly positioned during the procedure" (Nawana, ¶[0222]). Nawana additionally teaches that "the procedure analysis module 230 can be configured to analyze gathered images of a patient to generate a 3D model of the patients anatomy based on the images" and that "[t]he images can include previously gathered images, e.g., fluoroscopy, MRI, or CT images stored in the diagnosis database 310, and/or images gathered in real-time, e.g., fluoroscopy, ultrasound, or intraoperative CT images" (Nawana, ¶[0245]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Schmidt in view of Nawana such that Schmidt's patient data, including image data of one or more regions of the patient's spine, is obtained intraoperatively during a surgical procedure. This modification would have been possible because Schmidt already obtains patient image data and generates a patient-specific spine model from such image data, while Nawana provides a compatible intraoperative surgical support system that obtains real-time patient images, including fluoroscopy, ultrasound, or intraoperative CT images, and generates a 3D anatomical model from gathered patient images. The benefit of the combination would have been improved intraoperative accuracy and surgical decision support by allowing Schmidt's patient-specific correction model and surgical planning framework to be informed by current intraoperative image data and updated patient anatomy during the procedure.
Also regarding claim 15, the modified Schmidt teaches generating, using at least one computer modeling module, at least one corrected anatomical configuration for the patient's spine (Schmidt, ¶[0142]: "The process starts with a model of the spine, including each of the vertebral bodies of interest", showing that generation of the spine model is performed using at least one computer modeling module; ¶[0143]: "Morphing module 2204 uses a point cloud model for each vertebral body and can generate a simulation of a patient's morphology in a point cloud for the entire spine", explaining that the spine simulation is generated using computer modeling models for the vertebral bodies; ¶[0104]: "The three dimensional model includes a preoperative curve 802 and a postoperative curve 804. The sagittal view of FIG. 8A shows that the surgeon corrected the spine to put it in proper alignment", showing that the model represents a corrected anatomical configuration; ¶[0138]: "Material module 2205 enables altering the three-dimensional simulation by a predetermined amount or to the percent of correction from the surgeon input to enable preoperative visualization and/or prediction of the amount of correction required for a particular patient's spinal morphology", demonstrating generating or altering the corrected configuration using the modeling module). However, the modified Schmidt does not fully teach generating the corrected anatomical configuration intraoperatively.
Nawana teaches making the surgical simulation available intraoperatively and generating models from intraoperative image data. Nawana teaches that the SPP module 218 can be available to users "inside and outside the OR" and that "a user can perform a simulation using the SPP module 218 outside the OR... and/or inside the OR, e.g., as immediate prep before a scheduled surgery" (Nawana, ¶[0187]). Nawana also teaches that a saved simulation can be visible and accessible in the OR because "the system 10 can allow a user to pull up a simulation saved in the procedure database 316, thereby allowing the simulation to be visible and/or accessible in an OR" (Nawana, ¶[0219]). Nawana further teaches generating a 3D anatomical model from gathered images, including real-time fluoroscopy, ultrasound, or intraoperative CT images, as discussed above (Nawana, ¶[0245]). Thus, Nawana teaches using intraoperative image data and intraoperative access to the simulation/modeling workflow to generate or use model-based surgical correction information intraoperatively.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the modified Schmidt in view of Nawana such that the at least one corrected anatomical configuration for the patient's spine is generated intraoperatively. This modification would have been possible because Schmidt already generates corrected anatomical configurations using a computer modeling module, while Nawana provides a compatible intraoperative surgical support workflow in which gathered intraoperative images can be used to generate a 3D anatomical model and simulations can be accessed or performed inside the OR. The benefit of the combination would have been improved intraoperative planning accuracy by allowing the corrected anatomical configuration and associated surgical planning information to be generated or updated using current intraoperative patient data rather than relying only on earlier images or preoperative assumptions.
Also regarding claim 15, the modified Schmidt does not fully teach that the at least one computer modeling module is programmed to model soft tissue of the patient. Schmidt teaches generating a three-dimensional virtual spine model for visualization and predictive analysis and further teaches that its disclosed modeling and morphing techniques are not limited to bony vertebral bodies, explicitly stating that "disc structures" and "other non-bony structures within the anatomy of a subject" "may similarly be modeled and morphed utilizing the system and techniques disclosed herein" (Schmidt, ¶[0173]; ¶¶[0121]-[0128]). However, Schmidt does not teach programming the computer modeling module to model patient soft tissue with an explicit soft-tissue biomechanical representation within the simulation as required by the amended claim.
Galbusera teaches a patient-specific computer spine simulation in which soft tissues are explicitly represented within the model, including modeling spinal ligaments and intervertebral disks within the simulation framework. In particular, Galbusera discloses that "Six ligament groups are modeled as non-linear springs: anterior longitudinal ligament, posterior longitudinal ligament, flaval ligament, interspinous ligament, supraspinous ligament, and capsular ligaments" (Galbusera, p. 4, "Instrumented Spine Model"). Galbusera further discloses creating intervertebral disks as part of the model, stating "When the volume meshes of two adjacent vertebrae have been generated, the intervertebral disk is automatically created" (Galbusera, p. 3, "Instrumented Spine Model").
Anderson further teaches creating a patient-specific anatomy model substantially based on imaging data and generating a three-dimensional model of the patient's spine from images, where the model includes layered anatomical features such as "ligaments, tendons, [and] muscles" (Anderson, ¶¶[0143], [0157]), confirming the feasibility of incorporating soft tissue layers into an image-derived spine model.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the modified Schmidt in view of Galbusera and Anderson to program the at least one computer modeling module to model soft tissue of the patient. This modification would have been possible because Schmidt already employs computer-based three-dimensional spine simulation and expressly contemplates extending its modeling and morphing to "disc structures" and "other non-bony structures", and Galbusera provides a known, implementable approach for explicitly representing soft-tissue structures within a spine simulation, including ligament groups and intervertebral disks, which could be incorporated into Schmidt's existing modeling framework. Anderson further confirms the suitability of including soft tissue layers such as ligaments, tendons, and muscles in an image-derived patient anatomy model. The benefit of the combination would have been improved predictive accuracy and surgical planning reliability by enabling Schmidt's simulation to account for the biomechanical influence of soft tissue structures on spinal behavior during correction.
Also regarding claim 15, the modified Schmidt teaches receiving input on a primary spine procedure to adjust the patient's spine towards the at least one corrected anatomical configuration (Schmidt, ¶[0085]: "Computer 110 may analyze X-ray images in the medical data to determine an appropriate method of performing a spinal surgery and/or the parameters of the medical device to ensure that proper alignment is achieved", showing determining or receiving information for a primary spinal procedure to adjust the spine toward proper alignment; ¶[0138]: "Material module 2205 enables altering the three-dimensional simulation by a predetermined amount or to the percent of correction from the surgeon input", showing surgeon input for adjusting the spine toward the corrected configuration; ¶[0140]: "materials module 2205 enables the surgeon to input patient specific data which can be used to modify the three-dimensional simulation", showing receipt of surgeon input used to modify the spine model and plan the correction; ¶[0162]: "Material module 2205 is a preoperative planning tool that makes mechanical calculations and visually guides the surgeon through the process of choosing the correct hardware", showing input and planning for the primary corrective spine procedure). However, the modified Schmidt does not fully teach receiving the input intraoperatively.
Nawana teaches intraoperative use of procedure selection and simulation tools. Nawana teaches that the SPP module can be used inside the OR, including that "a user can perform a simulation using the SPP module 218... inside the OR, e.g., as immediate prep before a scheduled surgery" (Nawana, ¶[0187]). Nawana further teaches that the actual procedure can be tracked against a saved 3D simulated surgery and that the saved simulation can be visible or accessible in the OR (Nawana, ¶[0219]). Nawana further teaches that if the actual procedure deviates from the saved plan, "the system 10 can allow a user, e.g., the surgeon, to access the surgical procedure planning module 218 to modify the saved simulation for the surgical procedure" and that "[i]n this way, the surgeon can prepare a plan on the fly with consideration to unexpected circumstances that arise during the procedure and/or to test different surgical techniques and/or medical devices prior to actually performing the techniques and/or actually using the medical devices" (Nawana, ¶[0239]). Thus, Nawana teaches receiving intraoperative input for planning or modifying a surgical procedure during the actual procedure.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the modified Schmidt in view of Nawana to receive input intraoperatively on a primary spine procedure to adjust the patient's spine towards the at least one corrected anatomical configuration. This modification would have been possible because Schmidt already receives surgeon input for adjusting the three-dimensional simulation and planning the corrective spine procedure, while Nawana provides a compatible intraoperative surgical planning and tracking framework that allows the user to access, modify, and test surgical plans and techniques during the procedure. The benefit of the combination would have been improved intraoperative decision support by permitting the surgeon to update the primary corrective procedure in view of intraoperative conditions, current patient data, and deviations from the planned correction.
Also regarding claim 15, the modified Schmidt does not fully teach identifying a set of ancillary spine procedures; receiving selection of one of the set of ancillary spine procedures; and predicting intraoperatively an outcome for the selected ancillary spine procedure based on a simulation performed using a virtual model of the patient's spine and the modeled soft tissue of the patient. The modified Schmidt teaches a computer-implemented planning workflow in which a spine model is generated and modified based on surgeon input and predictive analysis is performed for correction planning (Schmidt, ¶[0014]; ¶[0138]; Fig. 17). However, the modified Schmidt does not expressly disclose identifying a set of ancillary spine procedures, receiving selection of one of the set of ancillary spine procedures, and predicting intraoperatively an outcome for the selected ancillary spine procedure based on a simulation performed using a virtual model of the patient's spine and the modeled soft tissue of the patient.
Nawana teaches an option-based, outcome-driven workflow in which the "treatment options module 212... can include a plurality of possible treatment options" and can determine which of the plurality of possible treatment options are associated with a diagnosis "based on prior treatments and outcomes," using patient- and treatment-specific variables including "bone removed, disc removed, ...reduction in pain,... and functional outcome" (Nawana, ¶[0148]). Nawana further teaches providing the options "to the user with historic success rates of each of the possible treatment option(s)" (Nawana, ¶[0150]) and selection, describing "choosing at least a one of the plans having a most desired effect on the at least one medical diagnosis" (Nawana, ¶[0022]).
Nawana also teaches simulation-based prediction for a selected procedure by stating that "The SPP module 218 can allow a user to select a Surgical procedure to simulate... recommend an optimized plan for the selected surgical procedure" (Nawana, ¶[0175]). Nawana further teaches that simulated aspects of the selected procedure include "bone removal, soft tissue removal, tissue and structure movement, correction", and "placement of all implants" (Nawana, ¶[0183]). Nawana further teaches that the system can "perform predictive Volumetric modeling of soft tissue movement, stretch, removal (e.g., of a herniated disc), and change based on each step of the simulated procedure" and that the user can "see in real time with the simulation how tissue and other structures will move based on each step of the procedure" (Nawana, ¶[0184]). Nawana further teaches projected outcome analysis because, when the simulation is complete, the SPP module can "analyze the procedure for projected results, e.g., potential healing, potential increase in patient mobility after 'X' amount of time, amount of correction, etc." and the user can "consult the projected results and decide whether to revise the surgery" (Nawana, ¶[0184]). These teachings show identification of multiple procedure options, user selection of a procedure, simulation of the selected procedure, and prediction of outcome information for the selected procedure.
Galbusera further supports that the selected procedure can be an ancillary spine procedure and that the simulation can be performed using a virtual spine model with modeled soft tissue. Galbusera teaches that, in planning correction of a spinal deformity, "the user has the possibility to simulate discectomies at selected levels, as commonly done in scoliosis surgery to facilitate the correction of the curves" and that, in such case, "the intervertebral disk is completely removed at the chosen levels, as well as the anterior and posterior longitudinal ligaments" (Galbusera, p. 5, "Planning of the Deformity Correction Surgery"). Thus, Galbusera teaches a discectomy with associated disk and ligament removal as an ancillary spine procedure used to facilitate the primary correction procedure, and Galbusera further teaches that modeled soft tissue structures such as ligaments and intervertebral disks are represented in the simulation (Galbusera, pp. 3-4, "Instrumented Spine Model").
Nawana further teaches the intraoperative aspect of predicting the outcome for the selected ancillary spine procedure because Nawana teaches that the SPP module may be used "inside the OR" (Nawana, ¶[0187]), that a saved simulation can be "visible and/or accessible in an OR" (Nawana, ¶[0219]), and that the plan can be modified on the fly during the procedure to test different surgical techniques or medical devices before actually performing the techniques or using the devices (Nawana, ¶[0239]). Thus, Nawana teaches that the selected procedure simulation and projected-results workflow can be used intraoperatively as part of the actual surgical procedure.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the modified Schmidt in view of Galbusera and Nawana to identify a set of ancillary spine procedures, receive selection of one of the set of ancillary spine procedures, and predict intraoperatively an outcome for the selected ancillary spine procedure based on a simulation performed using a virtual model of the patient's spine and the modeled soft tissue of the patient. This modification would have been possible because the modified Schmidt already provides the underlying computer-implemented spine modeling and predictive planning framework, Galbusera provides an implementable method for representing soft tissue, including ligaments and intervertebral disks, within the simulation model and teaches an ancillary discectomy/ligament-removal procedure used to facilitate spinal correction, and Nawana provides an implementable workflow for identifying a plurality of procedure options, receiving selection of one plan or procedure, performing simulation-based prediction of procedure outcomes, and making such simulation available intraoperatively in the OR. The benefit of the combination would have been providing a simulation-based intraoperative planning workflow that presents multiple candidate ancillary procedure options with outcome information, enables selection of an optimized ancillary procedure, and predicts correction, tissue movement, mobility, and related biomechanical effects during surgery, thereby supporting more informed procedure selection and reducing the risk of suboptimal planning outcomes.
Regarding claim 17, the modified Schmidt does not expressly disclose virtually simulating the selected one of the ancillary spine procedures. Rather, the modified Schmidt teaches a computer-implemented planning workflow in which a spine model is generated and modified based on surgeon input and predictive analysis is performed for correction planning (as shown above in claim 15), but it does not expressly disclose virtually simulating the selected one of the ancillary spine procedures.
Galbusera expressly teaches simulation of ancillary spine procedures selected by a user within the planning model, stating that “the user has the possibility to simulate discectomies at selected levels” and that “the intervertebral disk is completely removed at the chosen levels, as well as the anterior and posterior longitudinal ligaments” (Galbusera, p. 5). Galbusera further teaches that the planning interface supports prediction associated with the simulated procedure, stating that “A user-friendly graphical interface allows the user to plan the desired correction strategy and to easily predict the achievable correction as well as mechanical variables, such as the stresses in the instrumentation and in the biological tissues” (Galbusera, p. 10, 'Discussion').
Nawana further supports simulation of a selected procedure by stating that “The SPP module 218 can allow a user to select a Surgical procedure to simulate... recommend an optimized plan for the selected Surgical procedure” and that simulated aspects can include “soft tissue removal” and “tissue and structure movement” (Nawana, ¶[0175]; ¶[0183]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the modified Schmidt in view of Galbusera and Nawana to virtually simulate the selected one of the ancillary spine procedures. This modification would have been possible because the modified Schmidt already provides the computer-implemented spine modeling and predictive planning framework in which a simulation is modified based on surgeon input (Schmidt, Fig. 17, block 1306; Schmidt, ¶[0138]), Galbusera provides an implementable technique for simulating a selected ancillary procedure (discectomy with associated disk and ligament removal) within the planning model (Galbusera, p. 5), and Nawana provides an implementable workflow for selecting a procedure to simulate and generating a plan for the selected procedure based on simulation (Nawana, ¶[0175]). The benefit of the combination would have been enabling visualization and simulation of a selected ancillary procedure within the planning workflow to support more informed procedure selection and reduce the risk of suboptimal planning outcomes.
Regarding claim 18, Schmidt teaches a computer-implemented method for modeling a surgical correction to an anatomical configuration (Schmidt, Abstract; ¶[0020]: "Disclosed are systems and methods for constructing a three dimensional simulation of the curvature of a boney structure, such as the spine", and using that model and medical data "to assist surgeons with determining the nature of a corrective procedure, predict postoperative changes in the curvature of the bony structure, the nature of the hardware necessary for use during the procedure and customizations of the hardware for the particular morphology of the patient", demonstrating computer-implemented modeling of a spine for planning a patient-specific surgical correction; ¶[0014]: "the computer system... construct[s] a three dimensional simulation of each vertebral body in the spine and morph[s] the three-dimensional simulation into a realistic visualization of the patient morphology by translating, angulating and rotating the models of the vertebral bodies, perform[s] predictive analysis on the three-dimensional simulation, and transmit[s] via the communications interface for review and user input", showing that the modeling is performed by a computer system and is used for predictive surgical analysis and user review).
Also regarding claim 18, Schmidt does not fully teach obtaining patient data of a patient intraoperatively during a surgical procedure, the patient data including image data of one or more regions of a patient's spine. Schmidt teaches obtaining patient data including image data of one or more regions of the patient's spine because Schmidt teaches a model comprising "a set of spatial coordinates derived from images of the bony structure captured in at least two different planes" and teaches obtaining coronal and sagittal X-ray images for generating the spine model (Schmidt, Abstract; ¶[0020]; Figs. 3 and 5). However, Schmidt does not fully teach obtaining the patient data intraoperatively during a surgical procedure.
Nawana teaches obtaining patient data intraoperatively during a surgical procedure, wherein the patient data includes image data of one or more regions of a patient's spine. Nawana teaches that the images used during the procedure can include "images gathered in real-time... fluoroscopy, ultrasound, or intraoperative CT images" and that "[t]he patient can be imaged throughout the procedure in real time to help ensure that the patient is properly positioned during the procedure" (Nawana, ¶[0222], showing real-time intraoperative imaging of the patient during the procedure). Nawana additionally teaches that "the procedure analysis module 230 can be configured to analyze gathered images of a patient to generate a 3D model" and that "[t]he images can include previously gathered images, e.g., fluoroscopy, MRI, or CT images stored in the diagnosis database 310, and/or images gathered in real-time, e.g., fluoroscopy, ultrasound, or intraoperative CT images" (Nawana, ¶[0245], showing generation of a patient anatomical model using intraoperative image data).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Schmidt in view of Nawana such that Schmidt's patient data, including image data of one or more regions of the patient's spine, is obtained intraoperatively during a surgical procedure. This modification would have been possible because Schmidt already obtains patient image data and generates a patient-specific spine model from such image data, while Nawana provides a compatible intraoperative surgical support system that obtains real-time patient images, including fluoroscopy, ultrasound, or intraoperative CT images, and generates a 3D anatomical model from gathered patient images. The benefit of the combination would have been improved intraoperative accuracy and surgical decision support by allowing Schmidt's patient-specific correction model and surgical planning framework to be informed by current intraoperative image data and patient positioning information.
Also regarding claim 18, the modified Schmidt does not fully teach generating, using at least one computer modeling module, a virtual model intraoperatively of the patient's spine based on a native anatomical configuration of the spine and the patient data, wherein the at least one computer modeling module is programmed to model soft tissue of the patient. Rather, the modified Schmidt teaches generating, using at least one computer modeling module, a virtual model of the patient's spine based on a native anatomical configuration of the spine and the patient data (Schmidt, ¶[0142]: "The process starts with a model of the spine, including each of the vertebral bodies of interest", showing a virtual spine model based on the patient spine; ¶[0143]: "Morphing module 2204 uses a point cloud model for each vertebral body and can generate a simulation of a patient's morphology in a point cloud for the entire spine", showing generation of a patient-specific virtual spine model using a computer modeling module). Schmidt further teaches that its disclosed modeling and morphing techniques are not limited to bony vertebral bodies because "disc structures" and "other non-bony structures within the anatomy of a subject" "may similarly be modeled and morphed utilizing the system and techniques disclosed herein" (Schmidt, ¶[0173], showing that Schmidt contemplates modeling non-bony anatomical structures in the same modeling framework). However, the modified Schmidt does not fully teach generating the virtual model intraoperatively or that the computer modeling module is programmed to model soft tissue of the patient with an explicit soft-tissue representation in the simulation.
Nawana teaches generating a model intraoperatively from intraoperative patient image data. Nawana teaches that "the procedure analysis module 230 can be configured to analyze gathered images of a patient to generate a 3D model" and that "[t]he images can include previously gathered images, e.g., fluoroscopy, MRI, or CT images stored in the diagnosis database 310, and/or images gathered in real-time, e.g., fluoroscopy, ultrasound, or intraoperative CT images" (Nawana, ¶[0245], showing generation of an anatomical model from intraoperative image data). Nawana further teaches that the SPP module 218 can be used "inside the OR" and that "a user can perform a simulation using the SPP module 218... inside the OR, e.g., as immediate prep before a scheduled surgery" (Nawana, ¶[0187], further showing that the simulation workflow is available in the OR).
Galbusera teaches a patient-specific computer spine simulation in which soft tissues are explicitly represented within the model, including modeling spinal ligaments and intervertebral disks within the simulation framework. Galbusera discloses that "Six ligament groups are modeled as non-linear springs: anterior longitudinal ligament, posterior longitudinal ligament, flaval ligament, interspinous ligament, supraspinous ligament, and capsular ligaments" (Galbusera, p. 4, "Instrumented Spine Model", showing explicit modeling of spinal ligaments as soft tissue structures in the spine simulation). Galbusera further discloses creating intervertebral disks as part of the model, stating that "[w]hen the volume meshes of two adjacent vertebrae have been generated, the intervertebral disk is automatically created" (Galbusera, p. 3, "Instrumented Spine Model", showing modeling of intervertebral disk soft tissue structures between vertebrae).
Anderson further teaches creating a patient-specific anatomy model substantially based on imaging data and generating a three-dimensional model of the patient's spine from images, where the model includes layered anatomical features such as "ligaments, tendons, [and] muscles" (Anderson, ¶¶[0143], [0157], confirming that image-derived patient-specific spine models can include soft tissue features). Nawana further teaches that the anatomical visualization may include "tissue (e.g., soft tissue), bone, nerves, intervertebral disc material" and that the visualization can be patient specific, "similar to that discussed above regarding modeling of the patient for pre-op electronic simulation" (Nawana, ¶[0242], showing patient-specific anatomical visualization including soft tissue and intervertebral disc material). Nawana also teaches generating a 3D anatomical model based on gathered images, including real-time fluoroscopy, ultrasound, or intraoperative CT images (Nawana, ¶[0245]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the modified Schmidt in view of Galbusera, Anderson, and Nawana to generate the virtual model intraoperatively and to program the at least one computer modeling module to model soft tissue of the patient. This modification would have been possible because Schmidt already employs computer-based three-dimensional spine simulation and expressly contemplates extending its modeling and morphing to "disc structures" and "other non-bony structures"; Nawana provides a compatible intraoperative modeling workflow that generates a 3D anatomical model from gathered intraoperative images and makes the simulation workflow available inside the OR; Galbusera provides a known, implementable approach for explicitly representing soft-tissue structures within a spine simulation, including ligament groups and intervertebral disks; Anderson confirms that image-derived patient anatomy models may include soft tissue layers such as ligaments, tendons, and muscles; and Nawana teaches generating patient-specific anatomical models from gathered patient images, including real-time intraoperative images. The benefit of the combination would have been improved predictive accuracy and surgical planning reliability by enabling Schmidt's simulation to account for the biomechanical influence of patient soft tissue structures on spinal behavior during correction using patient-specific intraoperative image data.
Also regarding claim 18, the modified Schmidt teaches determining a target anatomical configuration for the one or more regions, wherein the target anatomical configuration is different than the native anatomical configuration because Schmidt teaches that "[t]he three-dimensional model includes a preoperative curve 802 and a postoperative curve 804" where "the surgeon corrected the spine to put it in proper alignment" (Schmidt, ¶[0104], showing a corrected postoperative target configuration different from the preoperative native configuration). Schmidt further teaches that "Material module 2205 enables altering the three-dimensional simulation by a predetermined amount or to the percent of correction from the surgeon input to enable preoperative visualization and/or prediction of the amount of correction required for a particular patient's spinal morphology" (Schmidt, ¶[0138], showing determination of a corrected target anatomical configuration based on a desired amount of correction). These teachings show determining a target corrected anatomical configuration for the patient's spine that is different from the native anatomical configuration.
Also regarding claim 18, the modified Schmidt does not fully teach identifying one or more intraoperative surgical alterations to soft tissue features surrounding the patient's spine to adjust an intraoperative mobility of the patient's spine to access a target site of the spine for spinal device placement, wherein the one or more intraoperative surgical alterations to the soft tissue features are identified based at least in part on the virtual model of the patient's spine and the target anatomical configuration. Rather, the modified Schmidt teaches treating soft tissue surgical alterations, including ligament resection and ligament cutting, as intraoperative surgical data that affects predicted spinal movement and surgical outcome because Schmidt teaches that medical data may include "[t]he surgical approach" and "ligaments resected", and because Schmidt teaches that "if the transverse ligament is cut on the concave side (intraoperative data), the probability of success of the surgery for the new patient may drop to 73.5%" and that "some or all of the relevant medical data may be used to predict movement of the new patient's spine after surgery" (Schmidt, ¶¶[0122], [0128], showing that ligament resection and ligament cutting are soft tissue surgical alterations used as intraoperative data tied to predicted spinal movement and outcome modeling). Schmidt also teaches hardware-related planning for proper alignment because computer 110 may analyze X-ray images and medical data "to determine an appropriate method of performing a spinal surgery and/or the parameters of the medical device to ensure that proper alignment is achieved", and material module 2205 guides the surgeon in choosing hardware capable of achieving the desired correction (Schmidt, ¶¶[0085], [0162], [0166], showing planning of spinal device parameters and hardware selection based on the patient-specific model and desired correction). However, Schmidt does not fully teach identifying intraoperative surgical alterations to soft tissue features that adjust intraoperative mobility of the patient's spine to access a target site of the spine for spinal device placement.
Galbusera teaches soft tissue release or removal steps used to facilitate spinal correction in a virtual spine model and in relation to the desired target correction. Galbusera teaches that a user may "simulate discectomies at selected levels, as commonly done in scoliosis surgery to facilitate the correction of the curves" and that, in such case, "the intervertebral disk is completely removed at the chosen levels, as well as the anterior and posterior longitudinal ligaments" (Galbusera, p. 5, "Planning of the Deformity Correction Surgery", showing simulation of soft tissue removal steps selected in a virtual spine model to facilitate movement of the spine toward the planned correction). Galbusera also teaches that the desired surgical correction is planned by allowing the user to translate or rotate a single vertebra or group of vertebrae until a desired correction has been achieved (Galbusera, p. 5, "Planning of the Deformity Correction Surgery", showing that the modeled correction uses the virtual spine model and target anatomical configuration). Thus, Galbusera teaches that removal of soft tissue structures, including intervertebral disk tissue and longitudinal ligaments, is identified in the simulation based on the virtual spine model and the desired target correction to facilitate spinal correction by increasing or adjusting the ability of the spinal segments to move toward the target anatomical configuration.
Nawana teaches spinal surgical planning and intraoperative tracking for accessing a target spinal site and placing spinal devices. Nawana teaches that a trajectory of lateral approach can be precisely determined to access a target vertebra while avoiding nerve damage, and identifies implantation of one or more percutaneous screws as a spinal surgical procedure in which precise patient positioning is important (Nawana, ¶[0221], showing target-vertebra access planning for spinal device placement). Nawana further teaches that "[a] vertebra is circled in the display 42 for ease of identification of a surgical target 44" (Nawana, ¶[0181], showing identification of a target spinal site). Nawana also teaches that aspects of a selected surgical procedure that can be simulated include "an access point on the patient", "a path through and/or retraction of tissue and nervous structures", "soft tissue removal", "tissue and structure movement", "correction", "movement due to indirect decompression", and "placement of all implants" (Nawana, ¶[0183], showing simulation of access planning, tissue retraction, soft tissue removal, tissue movement, correction, and implant placement). Nawana further teaches tracking actions of instruments in the actual surgical space, including "removal of bone, movement of tissue, insertion of material (e.g., a bone screw, interbody cage, biologic, combination treatment, etc.)" (Nawana, ¶[0237], showing intraoperative tracking of tissue movement and spinal device insertion).
The Examiner is not relying on Nawana's access trajectory alone as the claimed intraoperative surgical alteration. Rather, Schmidt teaches soft tissue surgical alterations, such as ligament cutting and ligament resection, that affect predicted spinal movement; Galbusera teaches discectomy with removal of intervertebral disk and longitudinal ligaments to facilitate correction in a virtual spine model based on a desired target correction; and Nawana teaches simulation of a procedure including tissue retraction, soft tissue removal, tissue and structure movement, correction, indirect decompression movement, target-site access, and implant placement. Thus, in the proposed combination, the intraoperative surgical alteration to soft tissue features is the release, resection, removal, or retraction of soft tissue that changes the mobility or relative movement of the patient's spine. The soft tissue alterations are identified based at least in part on the virtual model and target anatomical configuration because the virtual spine model and desired correction are used to determine where release, removal, or retraction of soft tissue would facilitate movement toward the target correction and provide access to the target site. Nawana's target-vertebra access and implant-placement teachings are relied upon to show the surgical context in which that adjusted mobility and tissue movement are used to access the target spinal site and place or insert the spinal device.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the modified Schmidt in view of Galbusera and Nawana such that the one or more intraoperative surgical alterations to soft tissue features surrounding the patient's spine are selected or identified to adjust intraoperative mobility of the patient's spine to access a target site of the spine for spinal device placement, wherein the one or more intraoperative surgical alterations to the soft tissue features are identified based at least in part on the virtual model of the patient's spine and the target anatomical configuration. This modification would have been possible because Schmidt already treats soft tissue surgical alterations, such as ligament cutting and resection, as variables affecting predicted spinal movement and as surgical data tied to movement toward a corrected anatomical configuration; Galbusera teaches that soft tissue removal, including discectomy and removal of longitudinal ligaments, facilitates correction of spinal curves in a virtual spine model based on a desired target correction; and Nawana provides a compatible surgical planning and intraoperative tracking framework involving target vertebra access, access points, soft tissue removal, tissue retraction, tissue and structure movement, correction, implant placement, and insertion of spinal materials such as bone screws and interbody cages. A person of ordinary skill in the art would have recognized that combining these teachings would allow the surgical plan to identify a soft tissue release, resection, removal, or retraction step based on the virtual spine model and desired target correction, change spinal mobility or relative spinal movement, use the changed mobility or tissue movement to establish or improve access to the target spinal site, and permit placement or insertion of a spinal device at that site. The benefit of the combination would have been improved surgical planning and intraoperative decision support by linking soft tissue release or removal to predicted spinal mobility, using that predicted mobility to assess access and device-placement feasibility, and allowing the surgeon to select or refine intraoperative surgical alterations based on whether the resulting spinal mobility and tissue movement provide appropriate access to a target spinal site for spinal device placement.
Also regarding claim 18, the modified Schmidt does not fully teach predicting the intraoperative mobility of the patient's spine attributable to the one or more intraoperative surgical alterations to the soft tissue features surrounding the patient's spine based on a simulation performed on the virtual model and the modeled soft tissue. Rather, the modified Schmidt teaches prediction of spinal movement based on intraoperative surgical alteration data because Schmidt teaches that "if the transverse ligament is cut on the concave side (intraoperative data), the probability of success of the surgery for the new patient may drop to 73.5%" and that "some or all of the relevant medical data may be used to predict movement of the new patient's spine after surgery" (Schmidt, ¶[0128], showing prediction of spinal movement based on intraoperative ligament-cutting data). Further, Galbusera, Anderson, and Nawana teach modeled soft tissue of the patient, as discussed above. However, the modified Schmidt does not fully teach predicting intraoperative mobility of the patient's spine attributable to the one or more intraoperative surgical alterations based on a simulation performed on the virtual model and the modeled soft tissue.
Nawana teaches predicting movement of tissues and structures attributable to surgical steps based on simulation with modeled soft tissue. Nawana teaches that a simulated surgery may include "soft tissue removal, tissue and structure movement, correction, movement due to indirect decompression" and "placement of all implants" (Nawana, ¶[0183], showing simulation of soft tissue removal and movement of tissue and structures during the procedure). Nawana further teaches running a simulation that predicts movement attributable to procedural steps using modeled soft tissue, stating that the system can "perform predictive volumetric modeling of soft tissue movement, stretch, removal (e.g., of a herniated disc), and change based on each step of the simulated procedure" and that the user can "see in real time with the simulation how tissue and other structures will move based on each step of the procedure" (Nawana, ¶[0184], showing simulation-based prediction of tissue and structural movement attributable to each procedural step).
Galbusera further supports that the simulation can be performed using a virtual spine model with modeled soft tissue structures and can output spinal mobility metrics based on the simulation because Galbusera teaches that "the finite element simulation is performed" and that simulation results include "nodal displacements" and "global orientations of the vertebrae before and after correction" extracted from the simulation (Galbusera, Fig. 6; p. 6, "Postprocessing and Data Analysis", showing simulation outputs reflecting spinal movement and vertebral orientation changes). Galbusera also teaches simulating discectomies with removal of intervertebral disk tissue and longitudinal ligaments to facilitate correction of the spinal curves, as discussed above (Galbusera, p. 5, "Planning of the Deformity Correction Surgery"). Anderson also supports accounting for soft tissue surgical alterations in modeled motion because Anderson teaches that when supporting tissues "will be cut or resected", the model "takes this into account in modeling the resultant motion sequences" (Anderson, ¶[0078], showing that modeled motion can account for soft tissue cutting or resection).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the modified Schmidt in view of Nawana, Galbusera, and Anderson to predict the intraoperative mobility of the patient's spine attributable to the one or more intraoperative surgical alterations to the soft tissue features surrounding the patient's spine based on a simulation performed on the virtual model and the modeled soft tissue. This modification would have been possible because Schmidt already uses a virtual spine modeling framework and already treats an intraoperative surgical alteration to soft tissue features, ligament cutting, as an input tied to predicted spine movement; Galbusera provides an implementable method for representing soft tissue within the simulation model and simulating soft tissue removal to facilitate correction; Anderson confirms that the model may account for supporting tissues that will be cut or resected when modeling resultant motion sequences; and Nawana provides an implementable simulation workflow that predicts how tissues and structures move attributable to each step of a procedure using predictive volumetric modeling of soft tissue behavior. The benefit of the combination would have been reducing complication risk and mechanical failure by enabling the planned correction to be evaluated using numerical simulation that predicts loads and stresses in the instrumentation and biological tissues, while also allowing step-based simulation of soft-tissue change and movement that affects the correction, access pathway, and device-placement feasibility, so that the surgeon can select safer strategies, verify access to the target spinal site, and refine the planned intraoperative surgical alteration before actual performance of the alteration during the procedure.
Regarding claim 21, the modified Schmidt teaches that the method further comprising: receiving, from a surgeon, one or more inputs comprising adjustments to the one or more intraoperative surgical alterations; and updating the prediction of the intraoperative mobility based on the inputs from the surgeon (Schmidt, ¶[0121]-[0128]: “…The medical data of the old patients in the database may include, among other medical data, the following: The surgical approach… ligaments resected …”; “…if the transverse ligament is cut on the concave side (intraoperative data)… In embodiments, some or all of the relevant medical data may be used to predict movement of the new patient’s spine after surgery …”, showing that intraoperative soft tissue surgical alterations (e.g., ligaments resected, ligament cutting) are treated as inputs/variables that affect predicted spine movement; Schmidt, ¶[0138]: “Material module 2205 enables altering the three-dimensional simulation by a predetermined amount or to the percent of correction from the surgeon input to enable preoperative visualization and/or prediction of the amount of correction required for a particular patient's spinal morphology”, showing that surgeon input is received and used to alter the simulation and update predictive results; Schmidt, ¶[0140]: “materials module 2205 enables the surgeon to input patient specific data which can be used to modify the three-dimensional simulation”, further demonstrating that surgeon inputs modify the simulated model; Schmidt, ¶[0163]: “… surgeon enters various data through a series of either drop down menus or slider bars or dialog boxes to enter any patient specific parameters… These input data are then used in a series of appropriate algorithms within materials module 2205 perform the stress/strain calculations and rendering module 2206 generates a visual representation…”, showing that surgeon-provided adjustments are processed by algorithms to update calculated outcomes and visualized predictions, consistent with updating the prediction of intraoperative mobility based on surgeon input).
Regarding claim 22, the modified Schmidt teaches that the method further comprises generating instructions for performing the one or more intraoperative surgical alterations (Schmidt, ¶[0085]: “computer 110 may analyze X-ray images in the medical data to determine an appropriate method of performing a spinal surgery and/or the parameters of the medical device to ensure that proper alignment is achieved”, showing the system determining an appropriate surgical method within the surgical planning workflow; Schmidt, ¶[0136]: “The computer 11 may then analyze the X-ray images and the medical data to determine instructions for constructing a simulation of the spinal morphology of a patient’s vertebral body for pre-operative visualization and to further simulate the predictive outcomes visually of multiple degrees of corrective surgery”, explicitly discloses determining “instructions” within the planning workflow; Schmidt, ¶[0121]-[0128]: “…The medical data of the old patients in the database may include, among other medical data, the following: The surgical approach… ligaments resected …”; “…if the transverse ligament is cut on the concave side (intraoperative data)…”, showing that the planned procedure can include intraoperative soft tissue surgical alterations; Schmidt, ¶[0162]: “Material module 2205 is a preoperative planning tool that makes mechanical calculations and visually guides the surgeon through the process of choosing the correct hardware”, demonstrating operative guidance generated by the planning tool; Schmidt, ¶[0166]: “Material module 2205 enables stress calculations, surgical pre-operative planning and predictive analytics… With this information the surgeon may more accurately choose the appropriate hardware capable of postoperatively achieving the desired percentage of correction”, further confirming operative guidance generated by the planning tool).
Regarding claim 23, the modified Schmidt teaches that predicting the intraoperative mobility includes identifying obstacles to completing the one or more intraoperative surgical alterations (Schmidt, ¶[0166]: “Material module 2205 enables stress calculations, surgical pre-operative planning and predictive analytics… With this information the surgeon may more accurately choose the appropriate hardware capable of postoperatively achieving the desired percentage of correction”, shows predictive analytics and planning that evaluates feasibility constraints relevant to completing the planned alterations; Schmidt, ¶[0167]: “Knowing how much to move/morph the spine increases the predictive analytics capabilities and, therefore, the likelihood of success of a procedure”, shows evaluating whether the planned movement/correction is achievable, which corresponds to identifying obstacles to completing the planned alterations).
Regarding claim 24, the modified Schmidt teaches that predicting the intraoperative mobility includes identifying risks associated with the one or more intraoperative surgical alterations to the soft tissue features (Schmidt, ¶[0163]: “FIG. 26 is a screen shot of a user interface 2600 by which a surgeon enters various data through a series of either drop down menus or slider bars or dialog boxes to enter any patient specific parameters, including things like, location of pedicle screws, screw material, rod dimensions and materials, patient risk factors (smoker, drinker, BMI, etc.), age, height, curve stiffness, everything specific to that patient. These input data are then used in a series of appropriate algorithms within materials module 2205 perform the stress/strain calculations and rendering module 2206 generates a visual representation of the hardware with a color coding or other visual graphics indicating if acceptable levels of risk are associated with the designated hardware configuration”, shows that the system evaluates and identifies risks associated with planned surgical alterations using predictive analytics; Schmidt, ¶[0166]: “Material module 2205 enables stress calculations, surgical pre-operative planning and predictive analytics… With this information the surgeon may more accurately choose the appropriate hardware capable of postoperatively achieving the desired percentage of correction”, further supports that risks associated with planned surgical alterations are identified as part of the predictive planning workflow).
Regarding claim 37, Schmidt teaches a computer-implemented method (Schmidt, Abstract; ¶[0020]: "Disclosed are systems and methods for constructing a three dimensional simulation of the curvature of a boney structure, such as the spine", and using that model and medical data "to assist surgeons with determining the nature of a corrective procedure, predict postoperative changes in the curvature of the bony structure, the nature of the hardware necessary for use during the procedure and customizations of the hardware for the particular morphology of the patient", demonstrating a computer-implemented method for modeling a spine and planning a patient-specific surgical correction; ¶[0014]: "the computer system... construct[s] a three dimensional simulation of each vertebral body in the spine and morph[s] the three-dimensional simulation into a realistic visualization of the patient morphology by translating, angulating and rotating the models of the vertebral bodies, perform[s] predictive analysis on the three-dimensional simulation, and transmit[s] via the communications interface for review and user input", showing that the modeling is performed by a computer system and is used for predictive surgical analysis and user review).
Also regarding claim 37, Schmidt does not fully teach generating, using at least one computer modeling module, a model intraoperatively of a spine of a patient and soft tissue during a surgical procedure based on image data of the patient. Rather, Schmidt teaches generating, using at least one computer modeling module, a model of a spine of a patient based on image data of the patient because Schmidt teaches a model comprising "a set of spatial coordinates derived from images of the bony structure captured in at least two different planes" and teaches obtaining coronal and sagittal X-ray images for generating the spine model (Schmidt, Abstract; ¶[0020]; Figs. 3 and 5). Schmidt further teaches generating the patient-specific spine model using at least one computer modeling module because "[t]he process starts with a model of the spine, including each of the vertebral bodies of interest" and because "Morphing module 2204 uses a point cloud model for each vertebral body and can generate a simulation of a patient's morphology in a point cloud for the entire spine" (Schmidt, ¶¶[0142], [0143]). Schmidt further teaches that its disclosed modeling and morphing techniques are not limited to bony vertebral bodies because "disc structures" and "other non-bony structures within the anatomy of a subject" "may similarly be modeled and morphed utilizing the system and techniques disclosed herein" (Schmidt, ¶[0173]). However, Schmidt does not fully teach generating the model intraoperatively during a surgical procedure or modeling soft tissue of the patient with an explicit soft-tissue representation in the simulation.
Nawana teaches generating a model intraoperatively from intraoperative patient image data. Nawana teaches that the images used during the procedure can include "images gathered in real-time with the positioning, e.g., skin surface mapping, fluoroscopy, ultrasound, or intraoperative CT images" and that "[t]he patient can be imaged throughout the procedure in real time to help ensure that the patient is properly positioned during the procedure" (Nawana, ¶[0222], showing real-time intraoperative imaging of the patient during the procedure). Nawana additionally teaches that "the procedure analysis module 230 can be configured to analyze gathered images of a patient to generate a 3D model" and that "[t]he images can include previously gathered images, e.g., fluoroscopy, MRI, or CT images stored in the diagnosis database 310, and/or images gathered in real-time, e.g., fluoroscopy, ultrasound, or intraoperative CT images" (Nawana, ¶[0245], showing generation of a patient anatomical model using intraoperative image data). Nawana further teaches that the anatomical visualization may include "tissue (e.g., soft tissue), bone, nerves, intervertebral disc material" and that the visualization can be patient specific, "similar to that discussed above regarding modeling of the patient for pre-op electronic simulation" (Nawana, ¶[0242], showing patient-specific anatomical visualization including soft tissue and intervertebral disc material).
Galbusera teaches a patient-specific computer spine simulation in which soft tissues are explicitly represented within the model, including modeling spinal ligaments and intervertebral disks within the simulation framework. Galbusera discloses that "Six ligament groups are modeled as non-linear springs: anterior longitudinal ligament, posterior longitudinal ligament, flaval ligament, interspinous ligament, supraspinous ligament, and capsular ligaments" (Galbusera, p. 4, "Instrumented Spine Model", showing explicit modeling of spinal ligaments as soft tissue structures in the spine simulation). Galbusera further discloses creating intervertebral disks as part of the model, stating that "[w]hen the volume meshes of two adjacent vertebrae have been generated, the intervertebral disk is automatically created" (Galbusera, p. 3, "Instrumented Spine Model", showing modeling of intervertebral disk soft tissue structures between vertebrae). Anderson further teaches creating a patient-specific anatomy model substantially based on imaging data and generating a three-dimensional model of the patient's spine from images, where the model includes layered anatomical features such as "ligaments, tendons, [and] muscles" (Anderson, ¶¶[0143], [0157], confirming that image-derived patient-specific spine models can include soft tissue features).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Schmidt in view of Galbusera, Anderson, and Nawana such that the computer modeling module generates, intraoperatively during the surgical procedure, a model of the patient's spine and soft tissue based on image data of the patient. This modification would have been possible because Schmidt already builds patient-specific spine models from image data and expressly contemplates extending its modeling beyond bony vertebral bodies to disc structures and other non-bony structures, Nawana provides a compatible intraoperative modeling workflow that obtains real-time intraoperative image data and generates a 3D anatomical model from gathered images, Galbusera provides a known, implementable approach for explicitly representing spinal soft tissues, including ligaments and intervertebral disks, within a spine simulation, and Anderson confirms that patient-specific anatomy models derived from imaging data can include layered soft tissue representations. The benefit of the combination would have been improved intraoperative accuracy, predictive accuracy, and surgical planning reliability by enabling Schmidt's patient-specific simulation to account for current intraoperative image data and the biomechanical influence of patient soft tissue structures on spinal behavior during correction.
Also regarding claim 37, the modified Schmidt does not fully teach determining mobility of at least a portion of the spine of the patient caused by one or more intraoperative surgical alterations to the soft tissue of the patient to access a target site of the spine for placement of and prior to implanting of one or more implants for achieving a target anatomical configuration. Rather, the modified Schmidt teaches treating soft tissue surgical alterations, including ligament resection and ligament cutting, as surgical data that affects predicted spinal movement and surgical outcome because Schmidt teaches that medical data may include "[t]he surgical approach" and "ligaments resected", and because Schmidt teaches that "if the transverse ligament is cut on the concave side (intraoperative data), the probability of success of the surgery for the new patient may drop to 73.5%" and that "some or all of the relevant medical data may be used to predict movement of the new patient's spine after surgery" (Schmidt, ¶¶[0122], [0128], showing that ligament resection and ligament cutting are soft tissue surgical alterations used as surgical data tied to predicted spinal movement and outcome modeling). Schmidt further teaches determining a target anatomical configuration because Schmidt teaches that "[t]he three-dimensional model includes a preoperative curve 802 and a postoperative curve 804" where "the surgeon corrected the spine to put it in proper alignment" (Schmidt, ¶[0104], showing a corrected postoperative target configuration different from the preoperative configuration). Schmidt also teaches hardware-related planning for proper alignment because computer 110 may analyze X-ray images and medical data "to determine an appropriate method of performing a spinal surgery and/or the parameters of the medical device to ensure that proper alignment is achieved", and material module 2205 guides the surgeon in choosing hardware capable of achieving the desired correction (Schmidt, ¶¶[0085], [0162], [0166], showing planning of spinal device parameters and hardware selection based on the patient-specific model and desired correction). However, Schmidt does not fully teach determining mobility caused by one or more intraoperative surgical alterations to soft tissue to access a target site of the spine for placement of and prior to implanting of one or more implants for achieving the target anatomical configuration.
Galbusera teaches soft tissue release or removal steps used to facilitate spinal correction in a virtual spine model and in relation to the desired target correction. Galbusera teaches that a user may "simulate discectomies at selected levels, as commonly done in scoliosis surgery to facilitate the correction of the curves" and that, in such case, "the intervertebral disk is completely removed at the chosen levels, as well as the anterior and posterior longitudinal ligaments" (Galbusera, p. 5, "Planning of the Deformity Correction Surgery", showing simulation of soft tissue removal steps selected in a virtual spine model to facilitate movement of the spine toward the planned correction). Galbusera also teaches that the desired surgical correction is planned by allowing the user to translate or rotate a single vertebra or group of vertebrae until a desired correction has been achieved (Galbusera, p. 5, "Planning of the Deformity Correction Surgery", showing that the modeled correction uses the virtual spine model and target anatomical configuration). Thus, Galbusera teaches that removal of soft tissue structures, including intervertebral disk tissue and longitudinal ligaments, is identified in the simulation to facilitate spinal correction by increasing or adjusting the ability of the spinal segments to move toward the target anatomical configuration.
Nawana teaches spinal surgical planning and intraoperative tracking for accessing a target spinal site and placing implants. Nawana teaches that "a trajectory of lateral approach can be very precisely determined so as to access a target vertebra while avoiding nerve damage" and identifies "implantation of one or more percutaneous screws" as a spinal surgical procedure in which precise patient positioning is important (Nawana, ¶[0221], showing target-vertebra access planning for spinal implant placement). Nawana further teaches that "[a] vertebra is circled in the display 42 for ease of identification of a surgical target 44" (Nawana, ¶[0181], showing identification of a target spinal site). Nawana also teaches that aspects of a selected surgical procedure that can be simulated include "an access point on the patient", "a path through and/or retraction of tissue and nervous structures", "soft tissue removal", "tissue and structure movement", "correction", "movement due to indirect decompression", and "placement of all implants" (Nawana, ¶[0183], showing simulation of access planning, tissue retraction, soft tissue removal, tissue movement, correction, and implant placement). Nawana further teaches tracking actions of instruments in the actual surgical space, including "removal of bone, movement of tissue, insertion of material (e.g., a bone screw, interbody cage, biologic, combination treatment, etc.)" (Nawana, ¶[0237], showing intraoperative tracking of tissue movement and implant or spinal material insertion). Nawana further teaches that the surgeon can access the surgical procedure planning module during the procedure "to test different surgical techniques and/or medical devices prior to actually performing the techniques and/or actually using the medical devices" (Nawana, ¶[0239], showing evaluation before actual use or implantation of the devices).
The Examiner is not relying on Nawana's access trajectory alone as the claimed intraoperative surgical alteration. Rather, Schmidt teaches soft tissue surgical alterations, such as ligament cutting and ligament resection, that affect predicted spinal movement; Galbusera teaches discectomy with removal of intervertebral disk and longitudinal ligaments to facilitate correction in a virtual spine model based on a desired target correction; and Nawana teaches simulation of a procedure including tissue retraction, soft tissue removal, tissue and structure movement, correction, indirect decompression movement, target-site access, implant placement, and insertion of spinal materials. Thus, in the proposed combination, the intraoperative surgical alteration to soft tissue is the release, resection, removal, or retraction of soft tissue that changes the mobility or relative movement of at least a portion of the patient's spine. Nawana's target-vertebra access and implant-placement teachings are relied upon to show the surgical context in which that adjusted mobility and tissue movement are used to access the target spinal site before implanting the one or more implants for achieving the target anatomical configuration.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the modified Schmidt in view of Galbusera, Anderson, and Nawana to determine mobility of at least a portion of the spine caused by one or more intraoperative surgical alterations to the soft tissue of the patient to access a target site of the spine for placement of and prior to implanting of one or more implants for achieving a target anatomical configuration. This modification would have been possible because Schmidt already treats soft tissue surgical alterations, such as ligament cutting and resection, as variables affecting predicted spinal movement and as surgical data tied to movement toward a corrected anatomical configuration; Galbusera teaches that soft tissue removal, including discectomy and removal of longitudinal ligaments, facilitates correction of spinal curves in a virtual spine model based on a desired target correction; Anderson confirms that when supporting tissues will be cut or resected, the model takes this into account in modeling resultant motion sequences; and Nawana provides a compatible surgical planning and intraoperative tracking framework involving target vertebra access, access points, soft tissue removal, tissue retraction, tissue and structure movement, correction, implant placement, and insertion of spinal materials such as bone screws and interbody cages. A person of ordinary skill in the art would have recognized that combining these teachings would allow the surgical planning system to identify a soft tissue release, resection, removal, or retraction step, determine the resulting mobility or relative spinal movement before implanting the one or more implants, use the determined mobility or tissue movement to establish or improve access to the target spinal site, and permit placement or insertion of the one or more implants at that site to achieve the target anatomical configuration. The benefit of the combination would have been improved pre-implant and intraoperative decision support by allowing the surgeon to evaluate predicted mobility effects of intended soft tissue alterations before implanting the one or more implants, thereby helping to verify access, implant-placement feasibility, and movement of the spine toward the target anatomical configuration.
Also regarding claim 37, the modified Schmidt does not fully teach updating a surgical plan intraoperatively for the surgical procedure based on the mobility and the target anatomical configuration of the spine, wherein the surgical plan includes one or more images of a virtual model of the spine in the target anatomical configuration, and mobility information for evaluating the mobility of at least a portion of the spine for moving the spine toward the target anatomical configuration during the surgical procedure being performed on the patient, wherein the mobility information includes at least one image of the spine at an intraoperative configuration prior to achieving the target anatomical configuration. Rather, the modified Schmidt teaches generating a surgical plan for achieving a target anatomical configuration because the three-dimensional model may be analyzed "to determine an appropriate treatment plan", computer 110 may analyze X-ray images and medical data "to determine an appropriate method of performing a spinal surgery and/or the parameters of the medical device to ensure that proper alignment is achieved", and material module 2205 is a planning tool that guides the surgeon in choosing hardware capable of achieving the desired correction (Schmidt, ¶¶[0083], [0085], [0162], [0166]). Schmidt further teaches image-based virtual model outputs representing the target anatomical configuration because Schmidt teaches that "[t]he three-dimensional model includes a preoperative curve 802 and a postoperative curve 804" where "the surgeon corrected the spine to put it in proper alignment" (Schmidt, ¶[0104]) and teaches that its simulations are displayed for visualization and predictive analysis (Schmidt, ¶¶[0014], [0136]). Schmidt further teaches mobility information for evaluating movement of the spine toward a target configuration because Schmidt teaches a model of the spine over time from a preoperative state to a postoperative state and teaches that such models "may be used to predict the change in curvature of a spine" (Schmidt, ¶[0105], showing time-based mobility information for evaluating movement of the spine toward a corrected configuration). However, Schmidt does not fully teach updating the surgical plan intraoperatively based on the mobility and target anatomical configuration, or that the mobility information includes at least one image of the spine at an intraoperative configuration prior to achieving the target anatomical configuration.
Nawana teaches intraoperative plan tracking and modification in the context of tissue movement, target-site access, and implant placement. Nawana teaches that the simulated surgery can include "an access point on the patient", "a path through and/or retraction of tissue and nervous structures", "soft tissue removal", "tissue and structure movement", "correction", and "placement of all implants" (Nawana, ¶[0183]). Nawana further teaches that the user can save simulated procedures at various points throughout the simulation, repeat aspects of the procedure more than once, test different surgical products, and test the suitability of different access points (Nawana, ¶[0183]). Nawana also teaches that actual surgical tracking may include "movement of tissue" and "insertion of material (e.g., a bone screw, interbody cage, biologic, combination treatment, etc.)" (Nawana, ¶[0237]). Further, Nawana teaches that the plan tracking module provides feedback "throughout actual performance the surgical procedure as measured against at least one model, e.g., a saved simulated procedure and/or a pre-programmed procedure" and allows personnel "to continually validate and confirm that the steps being taken in the surgery line up with a saved pre-op plan" (Nawana, ¶[0238]). Nawana further teaches triggering alerts when deviations occur, including "not enough tissue and/or bone removed", "too much tissue and/or bone removed", or "an instrument has entered an undesirable area of the anatomy based on the pre-op plan" (Nawana, ¶[0238]). In response, Nawana teaches that "the system 10 can allow a user, e.g., the Surgeon, to access the Surgical procedure planning module 218 to modify the saved simulation for the surgical procedure" and that "[i]n this way, the Surgeon can prepare a plan on the fly with consideration to unexpected circumstances that arise during the procedure and/or to test different surgical techniques and/or medical devices prior to actually performing the techniques and/or actually using the medical devices" (Nawana, ¶[0239]). Thus, Nawana teaches updating the surgical plan intraoperatively in response to surgical progress or deviations, where the modified plan can account for mobility-related tissue movement, soft tissue removal, access-point suitability, surgical product or device selection, and implant placement at the surgical target.
Nawana also teaches providing images and mobility information useful for evaluating the mobility of the spine during the surgical procedure before the target anatomical configuration is achieved. Nawana teaches that the user can save simulated procedures at various points throughout the simulation and can see "in real time with the simulation how tissue and other structures will move based on each step of the procedure" (Nawana, ¶¶[0183], [0184], showing intermediate step-based mobility information for evaluating movement toward the target configuration). Nawana further teaches that the plan tracking module can track an actual surgical procedure in the OR against a 3D simulated surgery and can allow a saved simulation to be visible or accessible in the OR (Nawana, ¶[0219], showing intraoperative access to the virtual model and simulation during the actual procedure). Nawana also teaches that the procedure analysis module can provide visualization of patient anatomy in an OR using augmented reality, where computer-generated imagery can be overlaid on the patient and the imagery can be provided in real time with surgery (Nawana, ¶[0244], showing intraoperative image-based visualization of patient anatomy during the procedure). Nawana further teaches that the procedure analysis module can generate a 3D model based on gathered images, including real-time fluoroscopy, ultrasound, or intraoperative CT images, and register the model to reference markers on the patient in the OR or other surgical setting (Nawana, ¶[0245], showing intraoperative image-based model information). These teachings support mobility information including at least one image of the spine at an intraoperative configuration prior to achieving the target anatomical configuration because the system provides real-time intraoperative image-based visualization and step-based simulation of movement before completion of the correction.
These Nawana teachings are relied upon as part of the same surgical simulation and tracking workflow. Nawana describes a selected simulated procedure that can include access points, tissue retraction, soft tissue removal, tissue and structure movement, correction, and implant placement; actual surgical tracking that includes movement of tissue and insertion of spinal material; comparison of the actual procedure against a saved simulated or pre-programmed procedure; image-based visualization and model generation in the OR; and modification of the saved simulation on the fly when intraoperative circumstances or deviations arise. Thus, Nawana is not being relied upon for isolated, unrelated disclosures, but for an integrated workflow in which soft tissue movement or removal, target-site access, implant placement, image-based intraoperative model visualization, mobility evaluation, intraoperative tracking, deviation feedback, and plan modification operate together.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the modified Schmidt in view of Nawana to update the surgical plan intraoperatively for the surgical procedure based on the mobility and the target anatomical configuration of the spine, wherein the surgical plan includes one or more images of a virtual model of the spine in the target anatomical configuration and mobility information for evaluating mobility of at least a portion of the spine for moving the spine toward the target anatomical configuration during the surgical procedure, wherein the mobility information includes at least one image of the spine at an intraoperative configuration prior to achieving the target anatomical configuration. This modification would have been possible because Schmidt already provides a patient-specific spine correction model, a correction-planning framework, image-based virtual model outputs representing corrected alignment, time-based modeling of spinal movement toward a corrected configuration, predictive use of ligament cutting or resection as variables affecting spinal movement, and hardware-related planning for achieving proper alignment; Galbusera teaches that discectomy and removal of longitudinal ligaments facilitate correction by increasing the ability to correct the spinal curve; and Nawana provides a compatible intraoperative surgical support framework that simulates tissue retraction, soft tissue removal, tissue and structure movement, correction, access-point suitability, implant placement, and insertion of spinal materials, while also providing intraoperative tracking, intraoperative image-based visualization, and on-the-fly modification of the saved simulation during the procedure. A person of ordinary skill in the art would have had reason to combine these teachings so that, when intraoperative imaging or tracking indicates that the planned release, resection, removal, or retraction has produced too little or too much tissue movement or spinal mobility for the intended access path, implant placement, or target correction, the surgeon can update the surgical plan based on mobility information and the target anatomical configuration before implanting the one or more implants. The benefit of the combination would have been improved intraoperative decision support by linking soft tissue release or removal to predicted spinal mobility, displaying the target configuration and intermediate intraoperative configuration information, using that mobility information to assess access and implant-placement feasibility, and revising the plan intraoperatively when actual surgical progress deviates from the predicted access, mobility, or target-placement conditions.
Regarding claim 38, the modified Schmidt does not fully teach that selecting a set of reference cases based at least in part on one or more similarities between the spine and the set of reference cases. The modified Schmidt teaches identifying other cases by comparing a patient-specific three-dimensional spine model to “three-dimensional models of the curvature of other spines” and further teaches selecting a “cohort of patients… in a database” having “the same or similar characteristic medical data” (Schmidt, ¶[0083]; ¶[0121]). However, the modified Schmidt does not expressly teach selecting a set of reference cases based at least in part on one or more similarities between the patient’s spine and the set of reference cases as claimed.
Anderson teaches selecting reference cases (prior patients) based on similarities by “accessing at least one database having records of prior patient treatments” and “comparing… the current patient… with… prior patients… to identify prior patients with similar… factors” and “retrieving… records of prior patients with similar… factors” (Anderson, ¶[0008]). Nawana further teaches that prior patient cases in its system include “variables or attributes… that can be compared and grouped… automatically by the system” (Nawana, ¶[0148]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the modified Schmidt in view of Anderson and Nawana to select a set of reference cases based at least in part on one or more similarities between the patient’s spine and the set of reference cases. This modification would have been possible because the modified Schmidt already uses database cohorts having “the same or similar characteristic medical data” and compares a patient spine model to models of other spines, while Anderson and Nawana provide known, implementable database-based selection techniques that identify and retrieve prior cases based on similarity comparisons. The benefit of the combination would have been improved planning accuracy by leveraging similar-case data to inform mobility estimation for the current patient.
Also regarding claim 38, the modified Schmidt does not fully teach identifying reference mobility data from the set of reference cases. The modified Schmidt teaches using relevant medical data to “predict movement” of a patient’s spine (Schmidt, ¶[0128]), but it does not expressly teach identifying reference mobility data from a selected set of reference cases.
Nawana teaches that its stored prior-patient variables can include mobility-related data such as “range of motion” (Nawana, ¶[0148]). Anderson teaches accessing a database of prior patient treatment records that include “treatment outcomes,” and retrieving records of prior patients identified as similar to the current patient (Anderson, ¶[0008]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the modified Schmidt in view of Nawana and Anderson to identify reference mobility data from the selected set of reference cases. This modification would have been possible because the modified Schmidt already predicts spine movement based on patient data, Nawana expressly teaches storing mobility-related variables (including “range of motion”) for prior patients, and Anderson teaches retrieving records of similar prior patients including outcome information. The benefit of the combination would have been enabling mobility estimation to be grounded in mobility-related data observed in similar prior cases.
Also regarding claim 38, the modified Schmidt does not fully teach determining the mobility of at least a portion of the spine of the patient based on the reference mobility data. The modified Schmidt teaches selecting a cohort of similar patients in a database and using relevant medical data to “predict movement” of the new patient’s spine (Schmidt, ¶[0121]; ¶[0128]). However, the modified Schmidt does not expressly teach determining mobility of at least a portion of the spine based on reference mobility data identified from the selected reference cases.
Nawana teaches that patient-specific factors in its stored prior-patient data can include mobility-related variables, expressly listing “mobility” and “range of motion” among the patient-specific factors that may be received and used by the system (Nawana, ¶[0031]). Nawana also teaches using stored prior-patient variables to “discover trends in the variables between patients and relate these trends to patient type, procedure type, and functional outcomes” (Nawana, ¶[0148]), and those variables include mobility-related variables such as “range of motion” (Nawana, ¶[0148]).
Anderson teaches retrieving records of prior patients with “similar” information sets and outputting treatment and outcome information from those similar-case records, and further teaches that the system’s “modeling module” is configured to “simulate” available options where “the simulation is at least partially based on the outcome information from the records of prior patients retrieved” from the databases (Anderson, ¶[0006]; ¶[0008]; ¶[0009]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the modified Schmidt in view of Nawana and Anderson to determine the mobility of at least a portion of the spine of the patient based on reference mobility data from the selected reference cases. This modification would have been possible because the modified Schmidt already identifies cohorts of similar patients and predicts spine movement, Nawana expressly teaches that mobility-related variables (including “mobility” and “range of motion”) are part of the patient-specific data used for comparison/analysis, and Anderson teaches retrieving similar-case records and using retrieved prior-patient outcome information as an input to a simulation/modeling step, such that mobility-related reference variables from similar prior cases would have been used as reference inputs to determine mobility for the current patient. The benefit of the combination would have been improved reliability of mobility determination by grounding the mobility estimate in mobility-related reference variables derived from similar prior cases and their observed outcomes.
Regarding claim 40, the modified Schmidt teaches obtaining a three-dimensional model of the spine from a database (Schmidt, ¶[0023]: “The resulting three dimensional model of the curvature of the spine may be used to morph a pre-existing model of a normal spine to simulate the morphology of the patient for pre-operative visualization…”, teaching use of a pre-existing (stored) spine model; Schmidt, ¶[0145]: “…a model, e.g. a point map, of each vertebral body in a set of normal vertebral body models is retrieved…”, teaching obtaining/retrieving (from storage/database) a three-dimensional model of the spine/vertebral bodies).
Also regarding claim 40, the modified Schmidt does not fully teach moving vertebrae of the three-dimensional model to virtually simulate the one or more intraoperative surgical alterations. The modified Schmidt teaches moving vertebrae within a three-dimensional spine model by applying transformations to the vertebral body models, including that “each point in every point cloud model of a vertebral body is pivoted, translated, and rotated” (Schmidt, ¶[0145]). However, the modified Schmidt does not explicitly teach moving vertebrae of the three-dimensional model to virtually simulate the one or more intraoperative surgical alterations.
Nawana expressly teaches virtual simulation of surgical procedures on a modeled patient, stating that the system can perform “3D simulated Surgeries” on a “virtual patient,” and can store statistics regarding “an amount and/or exact location of bone and/or Soft tissue removed from the virtual patient,” thereby teaching virtual simulation of intraoperative alterations and associated tissue and structural movement (Nawana, ¶[0183]).
Galbusera further teaches virtual simulation of specific intraoperative alterations within a spine model, expressly stating that “the user has the possibility to simulate discectomies at selected levels” and that, in the simulation, “the intervertebral disk is completely removed… as well as the anterior and posterior longitudinal ligaments” (Galbusera, p. 5).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the modified Schmidt in view of Nawana and Galbusera to move vertebrae of the three-dimensional model to virtually simulate one or more intraoperative surgical alterations. This modification would have been possible because Schmidt already provides a three-dimensional spine modeling framework capable of vertebral movement via translation and rotation, while Nawana teaches virtual performance and simulation of surgical procedures involving bone and soft tissue removal on a virtual patient, and Galbusera teaches virtual simulation of specific intraoperative alterations (e.g., discectomy with disk and ligament removal) within a spine model. The benefit of the combination would have been enabling the planning model to reflect mobility changes attributable to virtually simulated intraoperative alterations prior to implanting hardware, thereby improving predictive accuracy and intraoperative planning reliability.
Also regarding claim 40, the modified Schmidt does not fully teach moving the vertebrae of the three-dimensional model to the target anatomical configuration. The modified Schmidt teaches generating a three-dimensional model of the spine and morphing/moving vertebral body models, including that the point cloud models can be “translated” and “rotated” during morphing (Schmidt, ¶[0145]) and that the model may include a “postoperative curve” showing the spine corrected into “proper alignment” (Schmidt, ¶[0104]). However, to the extent the claim requires explicitly moving vertebrae of the three-dimensional model to the target anatomical configuration as part of the planning workflow, Schmidt does not expressly describe moving individual vertebrae (or groups of vertebrae) to reach a desired target configuration via an interactive planning operation.
Galbusera teaches planning a desired surgical correction by moving vertebrae in the model, expressly stating that the user can “translate and/or rotate a single vertebra or a group of vertebrae… until a satisfying desired correction has been achieved” (Galbusera, p. 5).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the modified Schmidt in view of Galbusera to move the vertebrae of the three-dimensional model to the target anatomical configuration. This modification would have been possible because Schmidt already teaches morphing vertebral body models to represent corrected alignment and Galbusera provides an implementable, known planning interface for directly translating/rotating vertebrae in a spine model until the desired (target) correction is achieved. The benefit of the combination would have been improved controllability and clarity in achieving the target configuration during planning by enabling direct vertebra-level adjustments within the modeled correction workflow.
Regarding claim 41, the modified Schmidt does not fully teach that updating the surgical plan includes generating an intra-operative surgical plan with at least one surgical step different from surgical steps in a pre-operatively generated surgical plan for the surgical procedure. Rather, the modified Schmidt teaches generating a preoperative surgical plan for achieving a target anatomical configuration because the three-dimensional model may be analyzed "to determine an appropriate treatment plan", computer 110 may analyze X-ray images and medical data "to determine an appropriate method of performing a spinal surgery and/or the parameters of the medical device to ensure that proper alignment is achieved", and material module 2205 is a planning tool that guides the surgeon in choosing hardware capable of achieving the desired correction (Schmidt, ¶¶[0083], [0085], [0162], [0166]). However, the modified Schmidt does not fully teach generating an intra-operative surgical plan with at least one surgical step different from surgical steps in a pre-operatively generated surgical plan.
Nawana teaches generating an intra-operative surgical plan with at least one surgical step different from surgical steps in a pre-operatively generated surgical plan. Nawana teaches that the plan tracking module provides feedback "throughout actual performance the surgical procedure as measured against at least one model, e.g., a saved simulated procedure and/or a pre-programmed procedure" and allows personnel "to continually validate and confirm that the steps being taken in the surgery line up with a saved pre-op plan" (Nawana, ¶[0238], showing comparison of the actual intraoperative procedure to a saved pre-operative plan). Nawana further teaches that alerts can be triggered if "the actual procedure is deviating from the pre-op plan", including deviations such as "not enough tissue and/or bone removed", "too much tissue and/or bone removed", or "an instrument has entered an undesirable area of the anatomy based on the pre-op plan" (Nawana, ¶[0238], showing recognition of intraoperative differences from surgical steps or conditions in the pre-operative plan). In response to such intraoperative deviation or circumstances, Nawana teaches that "the system 10 can allow a user, e.g., the surgeon, to access the surgical procedure planning module 218 to modify the saved simulation for the surgical procedure" and that "[i]n this way, the surgeon can prepare a plan on the fly with consideration to unexpected circumstances that arise during the procedure and/or to test different surgical techniques and/or medical devices prior to actually performing the techniques and/or actually using the medical devices" (Nawana, ¶[0239], showing generation of an intra-operative surgical plan that modifies the saved pre-operative plan and can include different surgical techniques, medical devices, or responsive steps during the procedure). Thus, Nawana teaches that updating the surgical plan includes generating an intra-operative surgical plan with at least one surgical step different from surgical steps in a pre-operatively generated surgical plan for the surgical procedure.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the modified Schmidt in view of Nawana such that updating the surgical plan includes generating an intra-operative surgical plan with at least one surgical step different from surgical steps in a pre-operatively generated surgical plan for the surgical procedure. This modification would have been possible because Schmidt already provides a patient-specific spine correction model, a correction-planning framework, and hardware-related planning for achieving proper alignment, while Nawana provides a compatible intraoperative plan tracking and modification workflow that compares the actual procedure to a saved pre-operative plan, detects deviations from that plan, and allows the surgeon to modify the saved simulation and prepare a plan on the fly during the procedure. A person of ordinary skill in the art would have had reason to combine these teachings so that, when intraoperative imaging, tracking, tissue removal, tissue movement, access-path conditions, or implant-placement conditions differ from the pre-operatively generated surgical plan, the surgeon can generate an intra-operative surgical plan with a different surgical step before actually performing the technique or using the medical device. The benefit of the combination would have been improved intraoperative decision support and patient-specific adaptability by allowing the surgical plan to be revised during the procedure in response to unexpected circumstances or deviations from the pre-operative plan, thereby improving the likelihood that the selected surgical steps, access path, tissue alteration, and implant placement remain suitable for achieving the target anatomical configuration.
Claims 5, 19-20, and 39 are rejected under 35 U.S.C. 103 as being unpatentable over Schmidt et al. (US 20200261156 A1), hereto referred as Schmidt, in view of Nawana et al. (US-20140088990-A1), hereto referred as Nawana, and further in view of Galbusera et al. (Galbusera, Fabio et al. “Planning the Surgical Correction of Spinal Deformities: Toward the Identification of the Biomechanical Principles by Means of Numerical Simulation.” Frontiers in bioengineering and biotechnology 3 (2015): 178. Web.), hereto referred as Galbusera, and further in view of Anderson et al. (US-20100191071-A1), hereto referred as Anderson, and further in view of Mosnier et al. (US-20210145519-A1), hereto referred as Mosnier.
The modified Schmidt teaches claim 1, claim 18, and claim 37 as described above.
Regarding claim 5, the modified Schmidt does not fully teach that the method further comprises: determining one or more intraoperative correction values based on the predicted intraoperative mobility, wherein the one or more intraoperative correction values include at least one of a maximum distraction, lordosis correction, kyphosis correction, scoliosis correction, or spondylolisthesis correction. The modified Schmidt teaches computer-based planning for achieving spinal correction, including using “software” to ensure vertebral bodies are in normal sagittal alignment with corrected curvatures including “cervical lordosis” and “thoracic kyphosis” (Schmidt, ¶[0002]). However, the modified Schmidt does not fully teach determining one or more intraoperative correction values based on the predicted intraoperative mobility, wherein the one or more intraoperative correction values include at least one of a maximum distraction, lordosis correction, kyphosis correction, scoliosis correction, or spondylolisthesis correction.
Mosnier teaches determining quantified correction values to apply in a spinal correction context, including lordosis, kyphosis, and scoliosis-related values such as “Cervical Lordosis”, “Proximal Junctional Kyphosis ( PJK )”, “T12 - S1 Lumbar Lordosis ( LL )”, “T4 - T12 TK”, and “Cobb Angles” (Mosnier, ¶[0124]). Mosnier further teaches calculating and applying a correction during spinal correction, stating that “the system can be configured to calculate a correction to apply” and describing spinal correction application “such as compression and/or distraction of one or more screws” (Mosnier, ¶[0282]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the modified Schmidt in view of Mosnier to determine one or more intraoperative correction values based on the predicted intraoperative mobility, wherein the one or more intraoperative correction values include at least one of a maximum distraction, lordosis correction, kyphosis correction, scoliosis correction, or spondylolisthesis correction. This would have been feasible because the modified Schmidt already uses computer software for planning spinal correction to achieve corrected alignment targets including lordosis and kyphosis (Schmidt, ¶[0002]), and Mosnier provides directly compatible quantified correction outputs, including lordosis, kyphosis, scoliosis-related parameters and compression and distraction correction values that can be selected and applied as correction targets in the same spinal correction planning workflow (Mosnier, ¶[0124]; Mosnier, ¶[0282]; Mosnier, ¶[0283]). The benefit of the combination would have been enabling Schmidt’s predicted intraoperative mobility outputs to be converted into quantified, procedure-usable correction targets, including distraction and alignment parameter targets, thereby reducing planning variability and improving the repeatability of intraoperative correction selection (Schmidt, ¶[0002]; Mosnier, ¶[0282]; Mosnier, ¶[0283]).
Regarding claim 19, the modified Schmidt does not fully teach training a machine learning algorithm based at least partially on a plurality of reference patient data sets, each of the plurality of reference patient data sets having data on a reference patient's spine, a reference intraoperative surgical alteration performed on the reference patient's spine, and a reference resulting anatomical configuration; and applying the machine learning algorithm to the virtual model of the patient's spine and the target anatomical configuration. Rather, the modified Schmidt teaches predictive modeling of spinal surgical outcomes using alteration variables such as ligament resections and intraoperative data (Schmidt, ¶[0121]–[0128]: “…The medical data of the old patients in the database may include, among other medical data, the following: The surgical approach… ligaments resected …”, shows that surgical history data includes whether ligaments were resected (a soft tissue surgical step/alteration); “…if the transverse ligament is cut on the concave side (intraoperative data), the probability of success of the surgery for the new patient may drop to 73.5%. In embodiments, some or all of the relevant medical data may be used to predict movement of the new patient’s spine after surgery …”, shows that cutting a ligament (a soft tissue surgical step/alteration) is explicitly tied to intraoperative spine movement and surgical outcome prediction). These disclosures show that Schmidt ties alterations to probability-based predictions and outcome analysis. The modified Schmidt does expressly say that it uses a machine learning algorithm trained on sets of prior patient data and then applying that trained model to new patient simulations.
Mosnier fills this gap by presenting a comprehensive surgical planning framework that goes beyond Schmidt’s use of probability-based predictors. Specifically, Mosnier describes how imaging, case planning, and data collection can be integrated with artificial intelligence and machine learning to generate predictive models of surgical outcomes (¶[0007]). Mosnier emphasizes the use of prior patient datasets to train algorithms capable of forecasting patient-specific spinal surgery results. This directly addresses the deficiency in Schmidt by showing how structured surgical alteration data, such as ligament resections already accounted for in Schmidt, can serve as training inputs for machine learning models, thereby extending the predictive power of the system to more robust, data-driven outcome predictions.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the modified Schmidt in view of Mosnier to incorporate machine learning trained on reference patient datasets including surgical alterations and their resulting anatomical configurations, and to apply that trained algorithm to the virtual model of the patient’s spine and the target anatomical configuration. This combination is feasible because Schmidt already encodes alteration variables as predictive inputs, which are the very type of structured data suitable for training and application of machine learning as taught by Mosnier. The motivation to combine is clear: enhancing Schmidt’s predictive framework with data-driven machine learning would improve the accuracy, adaptability, and reliability of surgical planning systems, thereby yielding more precise and clinically useful outcomes.
Regarding claim 20, the modified Schmidt does not fully teach training a machine learning algorithm based at least partially on a plurality of reference patient data sets and the one or more intraoperative surgical alterations, wherein each of the plurality of reference patient data sets having data on a reference patient's spine, a reference intraoperative surgical alteration performed on the reference patient's spine, and a reference resulting anatomical configuration; and applying the machine learning algorithm to the virtual model of the patient's spine and the one or more intraoperative surgical alterations. Rather, the modified Schmidt teaches predictive modeling based on surgical alteration variables such as ligament resections and intraoperative data, which are factored into outcome prediction for a new patient (¶[0121]–[0128]). These passages show that the modified Schmidt ties alterations to postoperative mobility and success rates. However, it does not disclose the use of a machine learning algorithm trained on prior patient datasets of spines, alterations, and resulting anatomical configurations, nor the application of such a trained algorithm to predict the resulting anatomical configuration for a new patient.
Mosnier reinforces this point by teaching that its “iterative virtuous cycle” integrates preoperative, intraoperative, and postoperative processes such as imaging analysis, case planning, and data collection with machine learning and predictive modeling to predict surgical outcomes (¶[0007]). In particular, Mosnier explains that artificial intelligence and machine learning can be applied “to predict the outcome of a spinal surgery, [including] one or more parameters of a spine of a patient after spinal surgery” (¶[0007]). These teachings directly address the gap in Schmidt by showing how a machine learning algorithm can be trained on prior patient datasets (including surgical alterations and resulting anatomical configurations) and then applied to new cases to anticipate postoperative anatomy. This integration naturally complements Schmidt’s predictive framework, making the combination both feasible and advantageous for improving the accuracy and reliability of surgical planning.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the modified Schmidt in view of Mosnier to train a machine learning algorithm on patient datasets including surgical alterations and resulting anatomical configurations, and to apply the trained algorithm to predict a new patient’s resulting configuration after surgery. The combination would have been feasible because the modified Schmidt already encodes surgical alterations and outcomes in a structured way, which are precisely the type of data Mosnier describes as inputs for machine learning. The motivation to combine is clear: augmenting Schmidt’s predictive framework with Mosnier’s machine learning approach would improve accuracy and reliability of predictions regarding a patient’s postoperative anatomical configuration, thereby enhancing surgical planning and clinical outcomes.
Regarding claim 39, the modified Schmidt does not fully teach that training a machine learning algorithm based on data from the set of reference cases, wherein each of the reference cases have data on a reference patient's spine, a reference surgical procedure performed on the reference patient's spine, and an outcome of the reference surgical procedure. The modified Schmidt teaches selecting a cohort of similar prior patient cases from a database and further teaches that prior patient “medical data… may include” procedure-related variables such as “ligaments resected” as well as outcome-related information such as “Follow-up information” and “complications” (Schmidt, ¶[0121]; ¶[0126]-[0127]). Anderson similarly teaches that reference-case records can include “prior patient characteristic information, prior patient treatment plan, and prior patient outcome” (Anderson, ¶[0220]). However, the modified Schmidt does not teach training a machine learning algorithm on reference-case datasets as claimed.
Mosnier teaches training a predictive model using machine learning based on data from prior spinal surgery cases. In particular, Mosnier teaches that the system can “utilize machine learning and/or a training algorithm (s) to generate the predictive model” and that the system is configured to utilize “a system database comprising a plurality of previous spinal surgery cases, results thereof, and/or one or more spinal parameters derived therefrom”, and to utilize such data in a “training phase” and “testing phase” (Mosnier, ¶[0150]-[0151]). Mosnier further teaches splitting the database data “into a training data set and a testing data set” and using the training data to build the predictive model (Mosnier, ¶[0151]-[0152]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the modified Schmidt in view of Mosnier (and as further supported by Anderson) to train a machine learning algorithm based on the set of reference cases, wherein each reference case includes reference spine/patient data, reference procedure data, and outcome data. This modification would have been possible because the modified Schmidt already organizes and uses prior-case surgical variables (including soft-tissue alterations such as “ligaments resected”) and outcome-related information in a database for predictive analytics, Anderson teaches storing reference-case records including treatment plans and outcomes, and Mosnier teaches a known, implementable approach for using a database of prior spinal surgery cases and results to train a machine learning predictive model. The benefit of the combination would have been improved predictive robustness and adaptability by enabling the system to learn patterns from prior-case data rather than relying solely on fixed predictor logic.
Also regarding claim 39, the modified Schmidt does not fully teach using the trained machine learning algorithm to determine the mobility of at least a portion of the spine. The modified Schmidt teaches determining/estimating spine movement in the form of “motion vectors” for a target patient (Schmidt, ¶[0117]). However, the modified Schmidt does not teach using a trained machine learning algorithm to determine mobility of at least a portion of the spine.
Mosnier teaches that, after training/testing, the “predictive model can then be used to predict one or more output values of the spine of a patient post-surgery” based on preoperative values (Mosnier, ¶[0153]), and further teaches applying machine learning to generate postoperative predictions using a trained predictive model (Mosnier, ¶[0179]-[0180]). When read in view of the modified Schmidt’s mobility metric (motion vectors), Mosnier’s patient-specific predicted spine outputs would have been used to determine (i) predicted movement/mobility of one or more spine portions and/or (ii) mobility-related parameters derived from predicted spine state changes.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the modified Schmidt in view of Mosnier to use the trained machine learning predictive model to determine mobility of at least a portion of the spine. This modification would have been possible because the modified Schmidt already defines mobility in terms of computed “motion vectors” for a target spine, and Mosnier teaches a known, implementable approach to train and apply a machine learning predictive model from prior spine-surgery cases to generate patient-specific predicted spine outputs, from which mobility (e.g., predicted motion vectors or analogous mobility-related parameters) would have been determined. The benefit of the combination would have been improved mobility estimation accuracy by leveraging learned relationships from prior-case data to predict patient-specific mobility effects.
Claims 10 and 16 is rejected under 35 U.S.C. 103 as being unpatentable over Schmidt et al. (US 20200261156 A1), hereto referred as Schmidt, in view of Nawana et al. (US-20140088990-A1), hereto referred as Nawana, and further in view of Galbusera et al. (Galbusera, Fabio et al. “Planning the Surgical Correction of Spinal Deformities: Toward the Identification of the Biomechanical Principles by Means of Numerical Simulation.” Frontiers in bioengineering and biotechnology 3 (2015): 178. Web.), hereto referred as Galbusera, and further in view of Anderson et al. (US-20100191071-A1), hereto referred as Anderson, and further in view of Moll (US-20080195081-A1), hereto referred as Moll.
The modified Schmidt teaches claim 1 as described above.
The modified Schmidt teaches claim 15 as described above.
Regarding claim 10, the modified Schmidt teaches that the one or more soft tissue surgical steps include severing a ligament along the patient's spine (Schmidt, ¶[0126]: "The medical data of the old patients in the database may include, among other medical data, the following: The surgical approach. ligaments resected", showing that Schmidt's surgical planning and prediction framework identifies ligament resection as a surgical step performed on soft tissue during spinal surgery; Schmidt, ¶[0128]: "if the transverse ligament is cut on the concave side (intraoperative data), the probability of success of the surgery for the new patient may drop to 73.5%", showing a specific intraoperative surgical step in which a spinal ligament is cut, i.e., severed, and showing that the ligament-cutting step is used as intraoperative surgical data in Schmidt's prediction framework). Additionally, claim 10 recites the soft tissue surgical steps in the alternative, namely severing, by a surgical robot, a ligament along the patient's spine, removing, by the surgical robot, at least a portion of an annulus of intervertebral disc, or resecting, by the surgical robot, cartilage along the spine. Accordingly, because the rejection relies at least on the ligament-severing alternative, the prior art need not separately teach or suggest the annulus-removal alternative or the cartilage-resection alternative. Nevertheless, as explained below, Moll further teaches or suggests the annulus-removal alternative. However, the modified Schmidt does not expressly teach that the severing of the ligament or removal of at least a portion of the annulus of the intervertebral disc is performed by a surgical robot.
Moll teaches performing spinal surgical procedures using a surgical robot. Under the broadest reasonable interpretation, Moll's robotic instrument system for performing spinal surgery is a surgical robot. Moll teaches "methods of performing various surgical procedures using such robotic instrument systems" and further teaches "minimally invasive spinal surgical applications with a flexible, robotically controlled catheter instrument" (Moll, ¶[0004], showing robotic performance of spinal surgical procedures). Moll teaches that examples of spinal procedures performed using the robotic system include "a lumbar discectomy, a laminectomy, a forminotomy, the delivery of a spinal stabilization device, a kyphoplasty, a spineoplasty, or other spinal surgery" (Moll, ¶[0004], showing that the robotic system is used to perform spinal surgical procedures along the spine). Moll further teaches that the catheter instrument can include a "tool," "laser," "grasper," "shaving port," "blade," "drill," or "other end-effector useful for the particular spinal procedure being performed" (Moll, ¶[0005], showing that the robotic spinal instrument can carry cutting, grasping, shaving, drilling, and other operative end-effectors for performing the spinal procedure).
Moll teaches the relied-upon ligament-severing alternative because, during the described spinal procedure, "[t]he surgeon may also make a tiny slit in the ligamentum flavum, exposing the spinal nerves" (Moll, ¶[0028], showing cutting, i.e., severing, a ligament along the patient's spine). Moll then expressly teaches that the described lumbar discectomy or microdiscectomy procedure "may be performed with one or more flexible, robotically steerable catheter instruments and robotic catheter system" (Moll, ¶[0029], showing that the ligament-cutting spinal procedure is performed by the robotic instrument system). Thus, Moll teaches severing, by a surgical robot, a ligament along the patient's spine.
Moll further teaches or suggests the annulus-removal alternative because Moll teaches that lumbar discectomy removes part of a problem intervertebral disc, identifies the annulus fibrosis and nucleus pulposus as the two main parts of a disc, teaches that "the outer annulus fibrosis of the disc is sliced open and material from inside nucleus pulposus of the disc is scooped out," and further teaches that "[v]arious tools may be used with the catheter to remove the ruptured disc and other loose fragments of disc in the surrounding area" (Moll, ¶¶[0026]-[0028], showing robotic access to and operative cutting/removal of intervertebral disc material, including annulus access and removal of injured disc fragments). Moll also teaches that the discectomy procedure may be performed using a flexible, robotically steerable catheter and that FIGS. 3A-3D illustrate "a lumbar discectomy procedure using a flexible, robotically steerable catheter," including removal of parts of the herniated disc with a grasper (Moll, ¶¶[0029]-[0030], showing removal of intervertebral disc material by the robotic catheter system). Thus, Moll also teaches or suggests removing, by the surgical robot, at least a portion of an annulus of intervertebral disc.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the modified Schmidt in view of Moll such that the one or more soft tissue surgical steps are performed by a surgical robot, including at least severing a ligament along the patient's spine and further including, in the alternative, removing at least a portion of an annulus of an intervertebral disc. This modification would have been possible because the modified Schmidt already identifies ligament cutting or ligament resection as a soft tissue surgical step affecting spinal movement and already uses the soft tissue surgical step in a surgical planning framework, while Moll provides a compatible robotic spinal surgery system having robotically steerable catheter instruments and surgical tools for performing spinal procedures, including cutting a ligament along the spine and cutting/removing intervertebral disc material during a discectomy procedure. A person of ordinary skill in the art would have had reason to use Moll's robotic spinal surgery system to perform the planned soft tissue surgical steps identified in the modified Schmidt, including ligament cutting or resection and, where applicable to the planned spinal procedure, disc access and disc-material removal, because Moll teaches that, due to "the proximity of the spinal cord and associated nerves during these types of Surgical procedures, precise control and maneuverability of any surgical tools or catheter being used is desirable to avoid unintentional injury" (Moll, ¶[0029]). The benefit of the combination would have been improved precision and maneuverability when performing soft tissue surgical steps near spinal nerves and the spinal cord, thereby reducing the risk of unintended tissue injury while carrying out the planned soft tissue release, resection, cutting, or removal steps used to adjust spinal mobility, decompress neural structures, access a target spinal site, or facilitate the planned spinal correction.
Regarding claim 16, the modified Schmidt does not expressly disclose that the set of ancillary spine procedures includes: a laminectomy, a laminotomy, a microdiscectomy, a foraminotomy, and an osteophyte procedure. Rather, the modified Schmidt provides a predictive simulation framework for surgical planning, as shown in claim 15 above, but it does not identify specific ancillary procedures such as a laminectomy, a laminotomy, a microdiscectomy, a foraminotomy, and an osteophyte procedure.
Moll further discloses that minimally invasive spinal procedures include the specific ancillary procedures recited in claim 16 (Moll, Abstract: “a surgical method comprises... performing a lumbar discectomy, laminectomy, forminotomy, kyphoplasty, or spineoplasty”, showing explicit disclosure of the procedures). Additionally, Moll specifies that discectomy can be "microdiscectomy or microendoscopic discectomy" (Moll, ¶[0027]), demonstrates laminotomy and microdiscectomy. And to clear up any potential issue with the misspelling of "foraminotomy" found in the Moll Abstract, Moll elaborates on foraminotomy: “Foraminotomy is a surgical operation for relieving pressure on nerves… Foraminotomy involves the removal of bone material along the spine to take pressure off the spinal nerve” (Moll, ¶[0034]). Moll also describes that osteophyte procedures are included, noting that special cutting instruments or a drill may be used to remove bone spurs, which are osteophytes (Moll, ¶[0034]). These passages provide explicit identification of the claimed ancillary spine procedures.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the modified Schmidt in view of Moll to include ancillary spine procedures such as a laminectomy, laminotomy, microdiscectomy, foraminotomy, and osteophyte removal within the set of selectable procedures for planning and simulation. The modified Schmidt provides the predictive simulation framework, Galbusera teaches integration of surgeon-selected ancillary procedures into planning, and Moll explicitly identifies the specific ancillary spine procedures listed in the claim. It would have been feasible to incorporate these procedures into Schmidt’s planning system, and the benefit of doing so would be to expand the completeness of the surgical plan, ensuring that all relevant surgical options can be simulated, selected, and their outcomes predicted, thereby improving accuracy of planning and enhancing patient outcomes.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Schmidt et al. (US 20200261156 A1), hereto referred as Schmidt, in view of Nawana et al. (US-20140088990-A1), hereto referred as Nawana, and further in view of Galbusera et al. (Galbusera, Fabio et al. “Planning the Surgical Correction of Spinal Deformities: Toward the Identification of the Biomechanical Principles by Means of Numerical Simulation.” Frontiers in bioengineering and biotechnology 3 (2015): 178. Web.), hereto referred as Galbusera, and further in view of Anderson et al. (US-20100191071-A1), hereto referred as Anderson, and further in view of Gillman (US-20180008349-A1), hereto referred as Gillman.
The modified Schmidt teaches claim 1 as described above.
Regarding claim 14, the modified Schmidt does not expressly teach identifying one or more bony tissues for removal to adjust the intraoperative mobility, wherein the decompression plans include a laminectomy, a laminotomy, a microdiscectomy, a foraminotomy, or an osteophyte procedure. Rather, the modified Schmidt teaches generating and evaluating surgical planning simulations for spinal correction, including generating comparative scoring based on model and medical-data comparisons (as shown in claim 13 above), but does not expressly disclose identifying one or more bony tissues for removal to adjust intraoperative mobility, nor does the modified Schmidt specify decompression plans as including particular procedure types such as a laminectomy, laminotomy, microdiscectomy, foraminotomy, or osteophyte procedure.
Nawana teaches identifying and tracking bony tissue removal within a simulated surgical plan by specifying “an amount and/or exact location of bone and/or soft tissue removed from the virtual patient” and by simulating procedures that include “bone removal” and “movement due to indirect decompression” (Nawana, ¶[0174]; ¶[0183]; ¶[0184] ).
Gillman teaches decompression procedures including “laminectomy” and “foraminotomy” and teaches preoperatively “determining a size and a shape of an ideal amount of tissue to be removed from the spine of a patient prior to operation” (Gillman, ¶[0004]; ¶[0009]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the modified Schmidt in view of Nawana and Gillman to identify one or more bony tissues for removal to adjust the intraoperative mobility, wherein the decompression plans include a laminectomy, a laminotomy, a microdiscectomy, a foraminotomy, or an osteophyte procedure. It would have been obvious and feasible to combine because the modified Schmidt provides the computer-based spinal planning and simulation framework, Nawana provides explicit quantification and localization of bone removal within a virtual patient and ties such bone removal to decompression-related simulation, and Gillman provides explicit decompression procedure types and teaches determining an ideal amount of tissue to remove preoperatively, so incorporating Gillman’s decompression procedure categories and Nawana’s bone-removal identification within the modified Schmidt simulation is a routine integration of known procedure parameters into a preoperative planning module. The combination provides improved planning and intraoperative guidance by enabling decompression plans to be compared and generated with explicit bony-tissue removal identification and recognized decompression procedure types, thereby improving accuracy in achieving the desired intraoperative mobility and reducing the risk of inadequate or excessive tissue removal.
Response to Arguments
Objections
Applicant's arguments filed 4/7/2026, page 13, regarding the previous Objections of claim 37 has been fully considered and are persuasive. The previous Objections have been withdrawn. Additionally, there are new objections as shown above.
35 U.S.C. §112(a) and (b)
Applicant's arguments filed 4/7/2026, page 13-14, regarding the previous 112 Rejections of claim 4 has been fully considered and are persuasive except for the 112(b) rejection of claim 4. The previous 112 rejections have been withdrawn.
35 U.S.C. §103
Applicant's arguments filed 4/7/2026, pages 14-15, regarding the previous 103 Rejections of claims 1-4, 6-13, 15, 17-18, 21-24, 37-38, and 40 as well as claims 5, 14, 16, 19-20, and 39 have been fully considered but are not persuasive as shown below.
Applicant’s Argument:
Applicant argues that Schmidt, Galbusera, Anderson, and Nawana, individually and in combination, do not teach or disclose all elements of claims 1-4, 6-13, 15, 17-18, 21-24, 37-38, and 40. Applicant further argues that the amendments to independent claims 1, 15, 18, and 37 are based on agreements allegedly reached during the February 26, 2026 telephone conference. Applicant states that the remarks reflect the Examiner’s acknowledgment that the discussed amendments to independent claim 1 appeared to move prosecution forward, and Applicant therefore submits that the rejections set forth in the Office Action should be withdrawn.
Examiner’s Response:
Applicant’s argument is not persuasive. The Examiner does not agree that the February 26, 2026 telephone conference resulted in an agreement that the proposed claim amendments overcame the prior art of record or that the pending rejections would be withdrawn. Applicant’s own summary states only that the discussed amendments “appeared to move prosecution forward.” This statement does not establish that the Examiner agreed that the amended claims were allowable or that the prior art of record no longer supported a rejection.
The Examiner’s Interview Summary further confirms that no such agreement was reached. The Interview Summary states that the Applicant’s representatives and the Examiners discussed the proposed claim amendments, the nature of the invention, and the ways in which the invention may be distinguished from the prior art, and further states that “[t]he proposed strategies for overcoming the prior art would require further search and consideration.” Thus, the interview record reflects that the proposed amendments required additional review, not that the proposed amendments had already overcome the prior art or required withdrawal of the rejections.
The present Office action provides that further consideration. As set forth in the rejection above, the current claim limitations are taught or suggested by the combined teachings of Schmidt, Galbusera, Anderson, and Nawana. Schmidt teaches a computer-implemented spine correction modeling framework, patient-specific spine image data, corrected virtual spine modeling, soft tissue surgical step information affecting spinal movement, and surgical planning for achieving corrected alignment. Galbusera and Anderson teach modeling patient soft tissue, including spinal ligaments, intervertebral disks, and other soft tissue structures, within patient-specific anatomy or spine models. Nawana teaches intraoperative image acquisition, real-time model generation from gathered images, target-site access, tissue movement and removal, implant placement, insertion of spinal materials, and intraoperative modification of the saved surgical simulation.
Accordingly, Applicant’s reliance on the alleged interview agreement does not overcome the rejection. The rejections are maintained because the amended claim limitations are taught or suggested by the cited prior art as explained in the detailed claim mapping above, and because the stated combinations would have been obvious to one of ordinary skill in the art for the reasons provided.
Applicant’s Argument:
Applicant argues that dependent claims 5, 14, 16, 19-20, and 39 are patentable over the cited combinations for at least the reasons discussed with respect to the respective base claims and for the additional features recited in those dependent claims.
Examiner’s Response:
Applicant’s arguments are not persuasive. As discussed above, the respective base claims remain properly rejected over the cited prior art. Accordingly, Applicant’s argument that dependent claims 5, 14, 16, 19-20, and 39 are patentable based on the alleged patentability of the base claims is not persuasive.
Applicant also has not identified a specific deficiency in the additional teachings relied upon for the dependent claims. In particular, Applicant has not explained why Mosnier fails to teach or suggest the additional limitations of claims 5, 19-20, and 39, why Gillman fails to teach or suggest the additional limitations of claim 14, or why Moll fails to teach or suggest the additional limitations of claim 16. A general assertion that the dependent claims include additional features does not address the specific findings set forth in the rejections. Accordingly, the rejections of claims 5, 14, 16, 19-20, and 39 are maintained.
Conclusion
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 AARON MERRIAM whose telephone number is (703) 756-5938. The examiner can normally be reached M-F 8:00 am - 5:00 pm.
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/AARON MERRIAM/Examiner, Art Unit 3791
/MATTHEW KREMER/Primary Examiner, Art Unit 3791
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