Soft tissue balance in navigated surgical procedures

Abstract

A method for surgical planning includes planning, in connection with determining resections of patient anatomy for a surgical procedure, post-operative laxity of a joint of a patient. The planning the post-operative laxity includes estimating anticipated contact points of post-operative joint anatomy, where the estimating the anticipated contact points is based on articulation angle of the patient anatomy and on biomechanics of the patient anatomy.

Description

SOFT TISSUE BALANCE IN NAVIGATED SURGICAL PROCEDURESBACKGROUND

[0001] Total Knee Arthroplasty (“TKA”), commonly referred to as a “knee replacement”, is a procedure of orthopedic surgery' in which a knee joint, such as an arthritic knee joint, is replaced with a prosthesis. In a knee replacement, a series of bone resections are made to accommodate the placement of implants.SUMMARY

[0002] Shortcomings of the prior art are overcome and additional advantages are provided through the provision of a computer-implemented method. The method includes planning, in connection with determining resections of patient anatomy for a surgical procedure, post-operative laxity of a joint of a patient. Planning the post- operative laxity includes estimating anticipated contact points of post-operative joint anatomy. The estimating the anticipated contact points is based on articulation angle of the patient anatomy and on biomechanics of the patient anatomy.

[0003] In one or more embodiments, the patient anatomy is at least a portion of a knee of the patient, and the anticipated contact points are contact points of femoral and tibial components.

[0004] In one or more embodiments, the biomechanics includes estimations of rollback of a tibia of the patient.

[0005] In one or more embodiments, the planning the post-operative laxity accounts for removal of anatomical features of the patient anatomy.

[0006] In one or more embodiments, the anatomical features include one or more osteophytes.

[0007] In one or more embodiments, planning the post-operative laxity uses a soft tissue anatomy simulator that accommodates modifiable anatomy models and input forces, and estimates an impact of the removal of the anatomical features.

[0008] In one or more embodiments, planning the post-operative laxity estimates an effect of removal of the anatomical features on one or more of extension or flexion of the joint of the patient.

[0009] In one or more embodiments, planning the post-operative laxity further includes: obtaining a digital patient-specific bone model presenting the anatomical features for removal; segmenting the anatomical features from other anatomy presented in the bone model; removing the anatomical features from the bone model to provide an updated bone model, providing the updated bone model and an indication of a known or assumed force to an anatomy simulator; determining, based on the providing the updated bone model and the indication of the known or assumed force, one or more laxity values as reflected by the anatomy simulator using the updated bone model; and outputting the one or more laxity values to facilitate soft tissue balancing for the surgical procedure.

[0010] In one or more embodiments, the known or assumed force is determined based on stressing the patient anatomy during the surgical procedure.

[0011] In one or more embodiments, the known or assumed force is determined using one or more of a tensioner or device that expands the joint of the patient until a desired force is achieved.

[0012] In one or more embodiments, the known or assumed force is determined based on identifying forces applied by a user stressing patient anatomies in flexion and stressing patient anatomies with a tensioner calibrated to one or more specific force values, and determining amounts of force the user applies to patient anatomies during soft tissue assessment.

[0013] In one or more embodiments, the method includes tuning the anatomy simulator in real-time during the surgical procedure based on data from a surgical navigation system, the data relating known amounts of force to observed laxity amounts, the observed laxity amounts being observed based on applying the known amounts of force to the patient anatomy.

[0014] In one or more embodiments, anatomy simulator approximates soft tissues of the patient anatomy with components having spring constants to approximate behavior of the soft tissues of the patient anatomy, wherein the anatomy simulatorsolves for the spring constants, and wherein the determining the one or more laxity values includes using the spring constants to determine deformation of the soft tissues of the patient anatomy.

[0015] Additional aspects of the present disclosure are directed to systems and computer program products configured to perform the methods described above and herein. The present summary is not intended to illustrate each aspect of, every implementation of, and / or every embodiment of the present disclosure. Additional features and advantages are realized through the concepts described herein.BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Aspects described herein are particularly pointed out and distinctly claimed as examples in the claims at the conclusion of the specification. The foregoing and other objects, features, and advantages of the disclosure are apparent from the following detailed description taken in conjunction with the accompanying drawings in which:

[0017] FIG. 1 depicts example resections of a total knee arthroplasty;

[0018] FIGS. 2A-2C depict example schematic illustrations of patient knee anatomy;

[0019] FIG. 3 illustrating post-operative knee anatomy with implants;

[0020] FIG. 4 depicts a schematic illustration of contact point shift based on tibial rollback;

[0021] FIG. 5 depicts an example graph showing anteroposterior translations of the medial and lateral tibiofemoral contacts on the tibial surface;

[0022] FIG. 6 depicts geometrical center axis condylar motion across a range of flexion and extension;

[0023] FIG. 7 depicts example knee anatomy with osteophytes;

[0024] FIG. 8 depicts an example knee model of an anatomy simulator for use with aspects described herein;

[0025] FIGS. 9A-9B depict example processes for surgical planning, in accordance with aspects described herein; and

[0026] FIG. 10 depicts an example computer system to incorporate, use, and / or facilitate aspects described herein.DETAILED DESCRIPTION

[0027] Described herein are aspects (e.g., methods, systems, computer program products) for describing / determining optimized cut paths for cuts to accomplish desired resections, for instance cuts for active robotic execution of these cuts with a robot-mounted sagittal cutting instrument. For example, aspects provide a novel laxity planning methodology. For instance, aspects can incorporate and / or use known generalized joint biomechanics to estimate the contact position of the implants. In some embodiments, the methodology accounts for the removal of tissue such as osteophytes. In some embodiments, aspects use a soft tissue simulator that can accommodate modifiable bone models and input force to estimate the impact of osteophyte removal on post-operative laxity.

[0028] FIG. 1 depicts example cuts of a TKA, which generally includes 7 planar cuts: 5 femoral cuts to the patient femur, 1 tibial cut to the patient tibia, and 1 patella cut to the patient patella. These can all be achieved with a cutting instrument, for example a sagittal saw. Thus, a TKA generally includes seven planar resections: a tibial cut 102, a posterior femur cut 104, an anterior femur cut 106, a distal femur cut 108, trvo chamfer cuts (a posterior chamfer cut 110 that provides a chamfer between the posterior femur cut and the distal femur cut, and an anterior chamfer cut 112 that provides a chamfer between the anterior femur cut and the distal femur cut), and a patella cut 114.

[0029] A commonly overlooked potential benefit of navigated systems (e.g., surgical navigation technology / sy stems, for instance those that can incorporate / encompass surgical robotic navigation technology / platforms / systenis) is that they can help plan post-operative patient laxity. Laxity generally refers to the degree of “looseness” or “tightness” of the joint in various scenarios, and is largely predicated on the tension of the soft tissues in the joint after placement of implant(s). Some navigated systems perform this planning better than other navigated systems. Inthe context of a TKA scenario, planning the laxity includes predicting the relative tightness of the knee after the implants are placed.

[0030] In simple terms, ‘laxity’ in the context of a TKA is an assessment of the “tightness” or “feel” of the knee, which is driven by where the knee cuts are made and the placement and sizing of the implants. The general objective is for the soft tissues after implantation to be appropriately tensioned. More technically, laxity can refer to the distance between an assumed femur and tibia contact point, each on the medial or lateral side of the joint, respectively, when a deliberate force is applied to separate these contact points. The separation force can be subjectively applied such that increased separation of the assumed contact points would require a substantial increase in the applied force. The distance between the femur (with cartilage) and tibia (with cartilage) or between the femur implant and the tibial insert, under stress represents the laxity'. In clinical practice, tensioning may be achieved by the surgeon intraoperatively introducing stress to the knee joint at specific positions before any cuts are made. Generally the knee is extended (extension) and stressed medially and laterally, and the knee is flexed (flexion) and stressed medially and laterally. Some sy stems allow for the knee to be stressed through the range of motion. The laxity values (usually medial and lateral) are captured under each of these conditions, i.e., for various knee poses. The knee may also be stressed during a range of motion to capture midflexion values. The knee may be stressed in any of various ways --- for example with instrumentation or with force applied directly to the joint by the surgeon by hand. The knee may be tensioned subjectively to a point where greater elongation would require a substantial increase in force.

[0031] FIGS. 2A-2C depict example schematic illustrations of patient knee anatomy. FIG. 2A depicts a schematic representation of knee anatomy, including a distal end 204 of a femur 202 and proximal end 208 of a tibia 206, and illustrating distances that exist between the femur 202 (with cartilage) and tibia 206 (with cartilage) or between the femur implant 210 (also known as the femoral implant or component) and the tibial insert 212 that, sits on the tibial implant 21 1 , As shown, laxity refers to a distance between the femoral implant 210 and the tibial insert 212. Generally, a distance may be a surface-to-point measurement. The value of a well- designed navigation system is to estimate the post-operative laxity based on pre-operative laxity. Estimating the post-operative laxity can require estimating the anticipated femur and tibial contact points based on the planned resections.

[0032] FIG. 2B depicts a schematic representation of post-operative knee anatomy including the distal end 204 of the femur 202 with a femoral component 220 attached thereto, and the proximal end 208 of the tibia 206 with a placed tibial tray 211 and tibial insert 212. FIG. 2C depicts the femoral component 220 (top picture) and tibial tray 211 / tibial insert 212 (bottom picture) with markup showing example femur surface-to-tibial dwell points. Specifically, points 232 and 234 on the tibial insert identify example contact points of contact with the distal end of the femoral component 220 when the implants are placed. Curved lines 230 on the femoral component 220 in FIG. 2C indicate example paths of surface contact between the component 220 and the points 232, 234 when the knee flexes through its arc of motion.

[0033] Referring back to FIG. 2A, another value that is referenced is the gap 216, which is the distal femoral resection (217)-to-tibial resection (218) distance under tension. Generally the gap 216 is equal to the laxity 214 plus the implant thicknesses (femoral component, tibial tray, and insert) at the estimated contact points.

[0034] FIG. 3 depicts additional details of these aspects, illustrating a post- operative knee anatomy with implants and illustrating that gap distance equals laxityplus implant thickness. 302 illustrates a cross-sectional side view7of the femoral implant 304 that affixes to the distal end of the femur (a front view of which is shown by 310). The posterior thickness 306 is different than the distal thickness 308. A common thickness of the distal femoral condyle of the femoral implant regardless of implant size is 9 millimeter (mm ) from the point of the distal femoral cut (which corresponds to planar surface 309) to the surface of the femoral component that contact the tibial insert. 320 illustrates a side view of the tibial implant (tray 322 and insert 324) with a labeled dwell point 326. The quoted insert thickness may be a thickness of the whole construct (between the lines 328 and 330 corresponding to the dwell point 326 and the underside of the tibial tray 322) including the metal. This example shows an 11 mm distance from the resection (indicated by 330) to the dwell point 326.

[0035] While the optimal post-operative laxity targets may be subjective and depend on surgeon preference, there are well-established targets in the literature. Specifically, lateral extension gap and medial extension gap are often each between .5 nun and 1.0 mm, with medial extension gap typically being slightly smaller than the lateral extension gap. Additionally, lateral flexion gap is often between 4.0 mm and 4.5 mm, and medial flexion gap is often between 2.0 mm and 2.5 mm.

[0036] Many robotic systems, or navigated systems more generally, do not accurately plan the post-operative laxity. For instance, navigation systems that have laxity planning do this poorly and are not accurate. Poor accuracy can lead to poor resection planning and poor clinical outcomes.

[0037] Current drawbacks are generally driven by several issues:-Poor registration accuracy;-Poor cutting accuracy;-Inconsistent pre-operative and post-operative tensioning of the knee;-Severe arthritis or other damage to the anatomy can affect the value of pre- operative laxity values;-Poor planning of the estimated femur and tibial contact points (i.e., failure to accurately estimate the femur and tibial contact points; and / or-Failure to account for the effect of osteophyte removal.

[0038] Regarding planning of the estimated femur and tibial contact points, it is challenging to estimate post-operative implant contact points (femur and tibia) because of the complexity of the knee biomechanics. Navigation solutions for TKA fail to estimate the femur and tibial implant contact points, i.e., the actual implant contact positions, when estimating laxity. For example, poor accuracy observed with most navigation solutions reflect that contact point based estimations are not based on the biomechanics of the patient knee.

[0039] Aspects described herein propose incorporating estimated implant contact points into laxity estimation. That is, a laxity estimation methodology is proposed thatestimates laxity values based on an estimation of implant contact points of placed implants. The estimated implant contact points may be estimated for the planned resections in the knee joint during TKA procedure.

[0040] In accordance with aspects described herein, a process estimates contact point(s) based on the biomechanics of the patient knee. Considerations such as tibial rollback can be accounted-for in the estimation of contact point(s). A process can estimate contact point(s) based on the articulation of the knee and known biomechanics, for instance as known from literature. For instance, aspects can incorporate and / or use generalized joint biomechanics to estimate the contact positions of the implants. Considerations such as tibial rollback are to be accounted for in the estimation of the contact point. For example, an algorithm can estimate the contact point based on inputs that include articulation angle and estimation(s) of rollback of the tibia.

[0041] During flexion, the tibia slides relative to the femur. By way of example, in flexion, the contact points of the tibia with the femur translate posteriorly. This is reflected in FIG. 4, depicting a schematic illustration of contact point shift based on tibial rollback. This occurs both with natural anatomy and post-operatively with TKA implants. FIG. 4 shows this biomechanical phenomenon with reference to the femoral component. 402 of FIG. 4 depicts a scenario in which no implant contact point estimation in accordance with aspects described herein is used, and 404 depicts a scenario in which implant contact point estimation in accordance with aspects described herein is used. Both scenarios are depicted as a side view of the knee in flexion. Referring to 402, femoral component 406 is shown with the anterior femur 408 facing upward. Below component 406 is the anterior tibia and tibial surface 410. Initially, a contact point on the tibial surface is estimated to be point 414. Based on knee flexion to a set degree (say 90%), a contact point on the femoral component surface is estimated to be point 412. Here, there is no biomechanical consideration or attempt to estimate actual implant contact points accounting for tibial rollback, for example.

[0042] 404 depicts the scenario in which implant contact point estimation in accordance with aspects described herein is used. Femoral component 406 is again shown with the anterior femur 408 facing upward. Based on knee flexion to a setdegree (say 90%), the contact point on the femoral component surface is again estimated to be point 412. However, in this scenario, and accounting for tibial rollback, the actual contact point on the tibial surface 410 is updated to be point 414’, posterior to point 414. As a result, the post-operative laxity estimation, which is a function of the positioning of this contact point as explained previously, may be different than if point 414 were used.

[0043] The phenomenon depicted presents anteroposterior translation of the medial and lateral tibiofemoral contacts on the tibial surfaces. FIG. 5 depicts an example graph showing anteroposterior translations of the medial and lateral tibiofemoral contacts on the tibial surface. Additionally, FIG. 6 depicts geometrical center axis (GCA) condylar motion (in mm) across a range of flexion / extension (in %) for medial and lateral flexion and extension, in both males (on the left) and females (on the right). Both figures present example data that can be used for more accurately estimating contact point locations (leading to more accurate laxity calculations) and therefore facilitating more accurate TKA resection planning.

[0044] In accordance with further aspects described herein for more accurate TKA planning, laxity planning can additionally or alternatively account for removal of anatomical features(s) of the patient anatomy. For example, an osteophyte, also known as a bone spur, is a bony outgrowth or projection that typically forms along the edges of bones from osteoarthritis, aging, joint degeneration, and inflammation. FIG.7 depicts an example model of a femur 702 (on the left) with a corresponding radiographic image (on the right) showing osteophytes 704. Osteophytes are usually removed during surgery, but some (for example posterior femur or tibia osteophytes) can be extremely difficult to remove before executing the TKA cuts. Because laxity is captured before cutting and is used to plan cut placement, the laxity measurements therefore could be rendered inaccurate once the osteophytes are removed. This is because osteophytes alter the anatomy and thus they may cause smaller or larger laxity values than would be captured if they were removed. In some examples, the osteophytes may be adding extra tension to the soft tissue structures and impinging movement. In addition, osteophytes can also affect the ability to extend and / or flex the knee (e.g., in the form of restricting extension and / or flexion).

[0045] Thus, proposed in accordance with some aspects is a novel laxity planning methodology that, also can account for the removal of osteophytes or other patient anatomy. In some embodiments, aspects propose using a soft tissue simulator that can accommodate modifiable bone models and input force to estimate the impact of osteophyte removal on post-operative laxity. Improved laxity planning accuracy provided in accordance with aspects described herein can result in improved clinical outcomes if the surgeon plans the laxities based on, for example, established literature.

[0046] To solve for the effect of osteophytes on soft tissue balance, an example process / pipeline is provided as follows:(a) Reconstruct advanced imaging into a patient specific bone model (CT, MRI, x-ray, ultrasound, etc.), with the osteophytes being visible / reflected in the imaging;(b) Segment the osteophytes on the femur and tibia (as applicable) using a segmentation approach / process, for instance a manual segmentation process or an automated segmentation process such one using a trained machine learning algorithm;(c) Remove the segmented osteophytes from the bone model to create an updated bone model, i.e., without the segmented osteophytes. In examples, the updated bone model includes / reflects at this point no relevant femoral / tibial osteophytes;(d) During the laxity assessment, the actual patient bone will have the osteophytes. The bone may be stressed at a known or assumed force. The process inputs the updated bone model into an anatomy simulator and subject to the known or assumed force. The anatomy simulator can be a known simulator; open source simulators exist, for example.-The simulator can be tuned in real-time based on data from the navigation system. For example, if it is known that 100 newtons (N) of force is being applied to the medial compartment in flexion and it can be seen that this introduces 5 mm of laxity in the navigation then the simulator can be tuned accordingly in real time.-The process introduces into the simulator (which may optionally be tuned as discussed) the bone model that, has the osteophytes removed (e.g., the updated bone model) and determines the laxity value from the model. This ‘adjusted’ laxity value can be presented to the user as a more accurate means of planning the resections. For instance, adjusted laxity value(s) can be used to update or determine position, placement, angle, and / or other characteristics of resections (including, for example, cut positions and / or paths) for better clinical outcomes.

[0047] In this manner, the anatomy simulator is used to predict the changes in laxity from the removal of the osteophytes prior to their removal. FIG. 8 depicts an example knee model of an anatomy simulator for use with aspects described herein. In the simulator, the soft tissues may be approximated to / represented by a structure(s) with springdike properties, wherein a process is to therefore solve for the patient- specific ‘spring constants’ of the specific patient’s soft tissue structures. Given these spring constants, a process can determine, for a given amount of force, the deformation of a given spring (representative of given soft tissue). 800 shows an interface that presents the anatomy model (including implant models) and various labeled soft tissues.

[0048] To determine the deformation, it may be helpful to have an indication of the force that the soft tissues are being subjected to. This could be determined with / using tensioners or related devices, for instance those that expand the joint until the desired forces are achieved. In some cases, it can be challenging to insert such tools into the joint, for example when the joint is in extension. It is generally accepted that surgeons apply similar forces when stressing a knee in flexion and in extension. The system could be tuned to identify the forces applied by each user by having the user stress knees in flexion and then to stress the same knees with a calibrated tensioner to a specific force value. The amount of force the surgeon generally applies to the knee during soft tissue assessment could then be tuned over one or more subject knees.

[0049] In addition, and as noted, osteophytes can also affect the ability to extend and / or flex the knee. The anatomy simulator, having the bone model that has the osteophytes could therefore be used to estimate the effect of osteophyte removal onextension and / or flexion using similar concepts to those above in determining the effect on joint laxity. This may be done with or without predicting the changes in laxity from the removal of the osteophytes.

[0050] Accordingly, FIGS. 9A-9B depict example processes for surgical planning. The processes may be executed, in one or more examples, by a processor or processing circuitry of one or more computers / computer sy stems, such as those described herein. In one example, program code or instructions may, based on execution thereof by a processing circuit / processor(s), implement one, some, or all aspects of FIGS. 9A-9B.

[0051] Referring to FIG. 9A, the process includes planning (902), in connection with determining resections of patient anatomy for a surgical procedure, post- operative laxity of a joint of a patient. The planning of this post-operative laxity includes estimating (904) anticipated contact points of post-operative joint anatomy. The estimating the anticipated contact points is based on articulation angle of the patient anatomy and on biomechanics of the patient anatomy. In some embodiments, the patient anatomy is at least a. portion of a knee of the patient, and the anticipated contact points are contact points of femoral and tibial components. In some embodiments, the biomechanics includes estimations of rollback of a tibia of the patient.

[0052] In accordance with some embodiments, the planning of the post-operative laxity can, optionally, account, for removal of anatomical features of the patient anatomy. For instance, intraoperative removal of features could inform update(s) to a patient-specific anatomy model based on the anatomical feature removal, an example process of which is described below. In any case, in some embodiments, the anatomical features include one or more osteophytes. The planning of the post- operative laxity can use a soft tissue anatomy simulator that, accommodates modifiable anatomy models and input forces, and estimates an impact of the removal of the anatomical features. In accordance with some embodiments, the planning of the post-operative laxity estimates an effect of removal of the anatomical features on one or more of extension or flexion of the joint of the patient.

[0053] Thus, FIG. 9B presents an example process of planning of the post- operative laxity. The process includes obtaining (910) a digital patient-specific bonemodel presenting the anatomical features for removal, and segmenting (912) the anatomical features from other anatomy presented in the bone model. The process also includes removing (914) the anatomical features from the bone model to provide an updated bone model, and then providing (916) the updated bone model and an indication of a known or assumed force to an anatomy simulator.

[0054] In some embodiments, the known or assumed force is determined based on stressing the patient anatomy during the surgical procedure. For instance, the known or assumed force may be determined using one or more of a tensioner or device that expands the joint of the patient until a desired force is achieved. Additionally or alternatively, the known or assumed force may be determined based on identifying forces applied by a user stressing patient anatomies in flexion and stressing patient anatomies with a tensioner calibrated to one or more specific force values, and determining amounts of force the user applies to patient anatomies during soft tissue assessment.

[0055] Still referring to FIG. 9B, the process also include determining (918), based on the providing the updated bone model and the indication of the known or assumed force, one or more laxity values as reflected by the anatomy simulator using the updated bone model. In examples, the anatomy simulator approximates soft tissues of the patient anatomy with components having spring constants to approximate behavior of the soft tissues of the patient anatomy, the anatomy simulator solves for the spring constants, and the determining (918) of the one or more laxity values includes using the spring constants to determine deformation of the soft tissues of the patient anatomy. In any case, the process of FIG. 9B then outputs the one or more laxity values, in order to facilitate automatic and / or manual (by the surgeon) soft tissue balancing for the surgical procedure.

[0056] In some embodiments, the process optionally also includes tuning the anatomy simulator in real-time during the surgical procedure based on data from a surgical navigation system, where the data relates known amounts of force to observed laxity amounts, and the observed laxity amounts are observed based on applying the known amounts of force to the patient anatomy.

[0057] Aspect can plan the post-operative laxity to aid in setting resection properties (placement, angle, etc.) accordingly. The properties may guide properrobotic execution of the desired cuts, for instance cuts for active robotic execution of the cuts with a robot-mounted sagittal cuting instrument. The planning can inform the properties to be sent to a robot surgical system (such as controller of a robot for performing some or all of the procedure). Alternatively, if aspects of the method are performed by the controller, then the process can further include controlling the robot to make the resections using the determined properties.

[0058] In another example embodiment, a method is provided for post-operative laxity planning and soft tissue balancing for a surgical procedure. The method includes estimating anticipated contact points for planned resections of patient anatomy, and performing the post-operative laxity planning, where the post-operative laxity planning accounts for removal of anatomical features(s) of the patient anatomy. In examples, estimating the anticipated contact points is based on articulation angle of the patient anatomy and on biomechanics of the patient anatomy. In examples, the patient anatomy is at least a portion of a patient knee and the anticipated contact points are femur and tibia contact points, and the biomechanics are estimations of rollback of the tibia.

[0059] Additionally or alternatively, the anatomical features can include osteophytes.

[0060] Additionally or alternatively, the post-operative laxity planning can use a soft tissue anatomy simulator that accommodates modifiable anatomy models and input force(s) to estimate impact of anatomical feature removal on post-operative laxity / laxities. In examples, the method also includes estimating an impact / effect of removal of the anatomical features(s) on extension and / or flexion of a joint of the patient anatomy.

[0061] Additionally or alternatively, the post-operative laxity planning can include obtaining a digital patient-specific bone model presenting the anatomical feature(s) for removal, segmenting the anatomical feature(s) from other anatomy presented in the bone model, removing the anatomical feature(s) from bone model (e.g. by modifying the bone model) to provide an updated model, providing the updated bone model and an indication of a known or assumed force to an anatomy simulator, and determining, based on the providing the updated bone model and the indication of the known or assumed force, one or more laxity values as reflected bythe anatomy simulator using updated bone model; and outputting the one or more laxity values to facilitate proper soft tissue balancing / planning for the surgical procedure. In some examples, the known or assumed force is determined based on stressing the patient anatomy / subjecting soft tissue of the patient anatomy during the surgical procedure. In some examples, the known or assumed force is determined with / using tensioner(s) or device(s) that expand a joint of the patient anatomy until desired force(s) is / are achieved. In some examples, the known or assumed force is determined based on identifying forces applied by having a user stress patient anatomies in flexion and stress patient anatomies with a tensioner calibrated to specific force value(s), and determining amount(s) of force the user generally applies to patient anatomies during soft tissue assessment.

[0062] In some embodiments, the method further includes tuning the anatomy simulator in real-time during the surgical procedure based on data from a surgical navigation system, for instance data relating known amount(s) of force to observed laxity amount(s), the observed laxity amount(s) being observed based on applying the known amounts) of force to the patient anatomy.

[0063] Additionally or alternatively, in some embodiments the anatomy simulator approximates soft tissues of the patient anatomy with spring-like components having spring constants to approximate behavior of the soft tissues of the patient anatomy, where the anatomy simulator solves for the spring constants, and where the determining the one or more laxity values comprises using the spring constants to determine deformation of the soft tissues of the patient anatomy.

[0064] Aspects described herein can be helpful for surgical navigation technology / sy stems, navigated surgical procedures, and other industrial applications. Aspects could be integrated into robotic surgical systems, for example. In some embodiments, aspects are provided as software that can be integrated into target systems. There may be applications outside of surgery.

[0065] One or more embodiments described herein may be incorporated in, performed by, and / or used by one or more computer systems, such as one or more systems that are, or are in communication with, a camera system, tracking system, and / or orthopedic surgical robot, as examples. Processes described herein may be performed singly or collectively by one or more computer systems. A computersystem may also be referred to herein as a data processing device / system, computing device / system / node, or simply a computer. The computer system may be based on one or more of various system architectures and / or instruction set architectures.

[0066] FIG. 10 depicts an example computer system to incorporate, use, and / or facilitate aspects described herein. Computer system 1000 may be provided as part of a surgical navigation technology / system, for example. Computer system 1000 is in communication with one or more external device(s) 1002 (such as one or multiple robot(s), tracking camera / s), rigid robot tracking array(s), foot pedal(s), monitor(s), Deadman switch(es), etc.). Computer system 1000 includes one or more processor / s) 1002, for instance central processing unit(s) (CPUs). A processor can include functional components used in the execution of instructions, such as functional components to fetch program instructions from locations such as cache or main memory, decode program instructions, and execute program instructions, access memory for instruction execution, and write results of the executed instructions. A processor of processor / s) 1002 can also include register(s) to be used by one or more of the functional components. Computer system 1000 also includes memoty 1004, input / output (I / O) devices 1008, and I / O interfaces 1010, which may be coupled to the processor / s) 1102 and each other via one or more buses and / or other connections. Bus connections represent one or more of any of several types of bus structures, including a memoty bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include the Industry Standard Architecture (ISA), the Micro Channel Architecture (MCA), the Enhances ISA (EISA), the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI).

[0067] Memory 1004 can be or include main or system memory (e.g., Random Access Memory) used in the execution of program instructions, storage device(s) such as hard drive(s), flash media, or optical media as examples, and / or cache memory, as examples. Memory 1004 can include, for instance, a cache, such as a shared cache, which may be coupled to local caches (examples include LI cache, L2 cache, etc.) of processor / s) 1002. Additionally, memory’ 1004 may be or include at least one computer program product having a set (e.g., at least one) of programmodules, instructions, code or the like that is / are configured to cany out functions of embodiments described herein when executed by one or more processors.

[0068] Memory 1004 can store an operating system 1005 and other computer programs 1006, such as one or more computer programs / applications that execute to perform aspects described herein. Specifically, programs / applications can include computer readable program instructions that may be configured to carry out functions of embodiments of aspects described herein.

[0069] Examples of I / O devices 1008 include but are not limited to microphones, speakers, Global Positioning System (GPS) devices, RGB, IR, and / or spectral cameras, lights, accelerometers, gyroscopes, magnetometers, sensor devices configured to sense light, proximity, heart rate, body and / or ambient temperature, blood pressure, and / or skin resistance, registration probes and activity monitors. An I / O device may be incorporated into the computer system as shown, though in some embodiments an I / O device may be regarded as an external device (1012) coupled to the computer system through one or more I / O interfaces 1010.

[0070] Computer system 1000 may communicate with one or more external devices 1012 via one or more I / O interfaces 1010. Example external devices include a keyboard, a pointing device, a display, and / or any other devices that enable a user to interact with computer system 1000. Other example external devices include any device that enables computer system 1000 to communicate with one or more other computing systems or peripheral devices such as a printer. A network interface / adapter is an example I / O interface that enables computer system 1000 to communicate with one or more networks, such as a local area network (LAN), a general wide area network (WAN), and / or a public network (e.g., the Internet), providing communication with other computing devices or systems, storage devices, or the like. Ethernet-based (such as Wi-Fi) interfaces and Bluetooth® adapters are just examples of the currently available types of network adapters used in computer systems (BLUETOOTH is a registered trademark of Bluetooth SIG, Inc., Kirkland,Washington, U.S.A.).

[0071] The communication between I / O interfaces 1010 and external devices 1012 can occur across wired and / or wireless communications link(s) 1011, such as Ethernet-based wired or wireless connections. Example wireless connections includecellular, Wi-Fi, Bluetooth®, proximity -based, near-field, or other types of wireless connections. More generally, communications link(s) 1011 may be any appropriate wireless and / or wired communication link(s) for communicating data.

[0072] Particular external device(s) 1012 may include one or more data storage devices, which may store one or more programs, one or more computer readable program instructions, and / or data, etc. Computer system 1000 may include and / or be coupled to and in communication with (e.g., as an external device of the computer system) removable / non-removable, volatile / non -volatile computer system storage media. For example, it may include and / or be coupled to a non-removable, non-volatile magnetic media (typically called a “hard drive”), a magnetic disk drive for reading from and writing to a removable, non-volatile magnetic disk (e.g., a “floppy disk”), and / or an optical disk drive for reading from or writing to a removable, non-volatile optical disk, such as a CD-ROM, DVD-ROM or other optical media,

[0073] Aspects of the present invention may be a system, a method, and / or a computer program product, any of which may be configured to perform or facilitate aspects described herein. Computer system configured to perform these and other methods, and computer program products that include a computer readable storage medium storing instructions for execution to perform these and other methods are also provided.

[0074] Computer system 1000 may be operational with numerous other general purpose or special purpose computing sy stem environments or configurations. Computer system 1100 may take any of various forms, well-known examples of which include, but are not limited to, personal computer (PC) system(s), server computer system(s), such as messaging server(s), thin client(s), thick client / s), workstation(s), laptop(s), handheld device(s), mobile device(s) / computer(s) such as smartphone(s), tablet(s), and wearable device(s), multiprocessor system(s), microprocessor-based system(s), telephony device(s), network appliance(s) (such as edge appliance(s)), virtualization device(s), storage controller / s), set top box(es), programmable consumer electronic(s), network PC(s), minicomputer system(s), mainframe computer system(s), and distributed cloud computing environment(s) that include any of the above systems or devices, and the like.

[0075] In some embodiments, aspects of the present invention may take the form of a computer program product, which may be embodied as computer readable medium(s). A computer readable medium may be a tangible storage device / medium having computer readable program code / instructions stored thereon. Example computer readable medium(s) include, but are not limited to, electronic, magnetic, optical, or semiconductor storage devices or systems, or any combination of the foregoing. Example embodiments of a computer readable medium include a hard drive or other mass-storage device, an electrical connection having wires, random access memory (RAM), read-only memory (ROM), erasable-programmable read-only memory' such as EPROM or flash memory, an optical fiber, a portable computer disk / diskette, such as a compact disc read-only memory (CD-ROM) or Digital Versatile Disc (DVD), an optical storage device, a magnetic storage device, or any combination of the foregoing. The computer readable medium may be readable by a processor, processing unit, or the like, to obtain data (e.g., instructions) from the medium for execution. In a particular example, a computer program product is or includes one or more computer readable media that includes / stores computer readable program code to provide and facilitate one or more aspects described herein.

[0076] As noted, program instruction contained or stored in / on a computer readable medium can be obtained and executed by any of various suitable components such as a processor of a computer system to cause the computer system to behave and function in a particular manner. Such program instructions for carrying out operations to perform, achieve, or facilitate aspects described herein may be written in, or compiled from code written in, any desired programming language. In some embodiments, such programming language includes object-oriented and / or procedural programming languages such as C, C++, C#, Java, etc.

[0077] Program code can include one or more program instructions obtained for execution by one or more processors. Computer program instructions may be provided to one or more processors of, e.g., one or more computer systems, to produce a machine, such that the program instructions, when executed by the one or more processors, perform, achieve, or facilitate aspects of the present invention, such as actions or functions described in flowcharts and / or block diagrams described herein. Thus, each block, or combinations of blocks, of the flowchart illustrationsand / or block diagrams depicted and described herein can be implemented, in some embodiments, by computer program instructions.

[0078] While several aspects of the present invention have been described and depicted herein, these are only examples, and alternative aspects may be affected by those skilled in the art to accomplish the same objectives. Accordingly, it is intended by the appended claims to cover all such alternative aspects as fall within the true spirit and scope of the invention.

[0079] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It. will be further understood that the terms “comprises” and / or “comprising”, when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0080] The corresponding structures, materials, acts, and equivalents of all means or step plus function elements in the claims below, if any, are intended to include any structure, material, or act for performing the function in combination with other claimed elements as specifically claimed. The description of one or more embodiments has been presented for purposes of illustration and description, but is not intended to be exhaustive or limited to in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiment was chosen and described in order to best explain various aspects and the practical application, and to enable others of ordinary skill in the art to understand various embodiments with various modifications as are suited to the particular use contemplated.

Claims

CLAIMSWhat is claimed is:1 . A computer -implemented method including: planning, in connection with determining resections of patient anatomy for a surgical procedure, post-operative laxity of a joint of a patient, the planning the post-operative laxity including: estimating anticipated contact points of post-operative joint anatomy, wherein the estimating the anticipated contact points is based on articulation angle of the patient anatomy and on biomechanics of the patient anatomy.

2. The method of claim 1, wherein the patient anatomy is at least a portion of a knee of the patient, and the anticipated contact points are contact points of femoral and tibial components.

3. The method of claim 2, wherein the biomechanics includes estimations of rollback of a tibia of the patient.

4. The method of claim 1, 2, or 3, wherein the planning the post-operative laxity accounts for removal of anatomical features of the patient anatomy.

5. The method of claim 4, wherein the anatomical features include one or more osteophytes.

6. The method of claim 4, wherein the planning the post-operative laxity uses a soft tissue anatomy simulator that accommodates modifiable anatomy models and input forces, and estimates an impact of the removal of the anatomical features.

7. The method of claim 6, wherein the planning the post-operative laxity estimates an effect of removal of the anatomical features on one or more of extension or flexion of the joint of the patient.

8. The method of claim 4, wherein the planning the post-operative laxity further includes:obtaining a digital patient-specific bone model presenting the anatomical features for removal; segmenting the anatomical features from other anatomy presented in the bone model; removing the anatomical features from the bone model to provide an updated bone model; providing the updated bone model and an indication of a known or assumed force to an anatomy simulator; determining, based on the providing the updated bone model and the indication of the known or assumed force, one or more laxity values as reflected by the anatomy simulator using the updated bone model; and outputting the one or more laxity values to facilitate soft tissue balancing for the surgical procedure.

9. The method of claim 8, wherein the known or assumed force is determined based on stressing the patient anatomy during the surgical procedure.

10. The method of claim 9, wherein the known or assumed force is determined using one or more of a tensioner or device that expands the joint of the patient until a desired force is achieved.

11. The method of claim 9, wherein the known or assumed force is determined based on identifying forces applied by a user stressing patient anatomies in flexion and stressing patient anatomies with a tensioner calibrated to one or more specific force values, and determining amounts of force the user applies to patient anatomies during soft tissue assessment.

12. The method of claim 8, further comprising tuning the anatomy simulator in real-time during the surgical procedure based on data from a surgical navigation system, the data relating known amounts of force to observed laxity amounts, the observed laxity amounts being observed based on applying the known amounts of force to the patient anatomy.

13. The method of claim 8, wherein the anatomy simulator approximates soft tissues of the patient anatomy with components having spring constants to approximate behavior of the soft tissues of the patient anatomy, wherein the anatomy simulator solves for the spring constants, and wherein the determining the one or more laxity values includes using the spring constants to determine deformation of the soft tissues of the patient anatomy.

14. A computer system comprising: a memory; and a processing circuit in communication with the memory, wherein the computer system is configured to perform a method of any of claims 1 to 13.

15. A computer program product com pri si ng : a computer readable storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method of any of claims 1 to 13.