ROBOTIC ASSISTED LIGAMENT GRAFT PLACEMENT AND TENSIONING

TECHNICAL FIELD

The present disclosure relates generally to methods, systems, and apparatuses related to a computer-assisted surgical system that includes various hardware and software components that work together to enhance surgical workflows. The disclosed techniques may be applied to, for example, shoulder, hip, and knee arthroplasties, as well as other surgical interventions such as arthroscopic procedures, spinal procedures, maxillofacial procedures, rotator cuff procedures, ligament repair and replacement procedures. More particularly, the present disclosure relates to methods and systems of planning and preparing a joint for a ligament reconstruction surgery and performing aspects of such a surgery. The methods and systems may relate to preparing or generating a patient-specific surgical plan for forming an anterior cruciate ligament (ACL) graft tunnel and creating a tunnel for an ACL graft.

BACKGROUND

The use of computers, robotics, and imaging to provide aid during surgery is known in the art. There has been a great deal of study and development of computer-aided navigation and robotic systems used to guide surgical procedures. For example, a precision freehand sculptor employs a robotic surgery system to assist the surgeon in accurately cutting a bone into a desired shape.

The anterior cruciate ligament is the most frequently injured ligament in the knee and among the most common sports medicine procedures performed in the United States each year. ACL injuries most often result from non-contact, deceleration injuries or contact injuries with a rotational component. Approximately 100,000 ACL reconstructions are performed each year.

When ACL reconstruction procedures fail, the most common cause is tunnel malposition. Tunnel malposition occurs when the tunnel through which the grafted ligament is placed is in a non-anatomic position when compared with the native knee. Over 70% of ACL reconstruction failures result from this issue.

Tunnels are usually oriented according to one of two techniques: transtibial tunnel creation and anteromedial tunnel creation. Creation of a transtibial tunnel enables the surgeon to have better visualization of the anatomy and is less demanding for the surgeon to create. However, various clinical analyses have indicated that the transtibial technique places the tunnel in a non-anatomic position, which is less favorable for patient outcomes. In contrast, anteromedial tunnel creation is more demanding on the surgeon to accurately prepare, but provides an anatomical tunnel placement that can lead to increased rotary stability when properly performed. Visualization of the anatomy when performing the anteromedial technique is limited because the knee must be hyperflexed to prepare the tunnel. Depictions of knees having tunnels 20, 30 formed using the transtibial and anteromedial techniques are depicted in FIGS. 1A and 1B, respectively.

In addition to correctly positioning and orienting the graft tunnel, providing initial tensioning of the graft is paramount to the outcome of the surgery. A low initial graft tension can result in joint laxity, while over-tensioning the graft can lead to dysfunction, graft failure, and abnormal tibiofemoral kinematics resulting in cartilage degeneration. In conventional ACL repair surgery, graft tension is set to restore the normal anterior-posterior knee laxity. While returning to normal knee laxity is a useful standard, many factors can influence knee laxity. For example, the material properties of the graft material, the position of the graft tunnel, and the trajectory of the graft tunnel all influence the knee laxity post-surgery.

Graft tension is conventionally applied on the tibia side, and the graft is manually fixed when in a position of maximum tension (usually between 20 degrees and 30 degrees flexion of the knee). Graft tension can be applied manually or can be controlled with a tensioner or a tensioning boot. However, even with the use of instrumentation, the graft tension after fixation can vary due to inaccuracies from intraoperative tibia rotation or relaxation of the graft material and/or fixation assembly.

Previous systems attempting to improve the outcome of ACL reconstructions include an ACL navigation system from Praxim Medivision S.A. of La Tronche, France. The Praxim system used image-free modeling to recreate patient anatomy. Based on anatomical models and intraoperatively collected kinematics, such as passive flexion and extension of the knee), the system assessed the impingement risk and anisometry profile for a given set of tunnel placements. However, the Praxim system does not identify an ideal tunnel placement for a particular patient and does not assist a surgeon when performing an ACL reconstruction.

As such, a need exists for systems and methods that improve tunnel formation for ligament reconstruction surgical procedures to improve patient outcomes. In addition, a need exists to improve ligament tensioning using surgical navigation techniques. A further need exists to assist medical professionals performing ligament reconstructions with the determination of the location and orientation of a tunnel placement for the surgical procedure based on the client's anatomy, desired graft tension, desired joint laxity, and/or the like.

SUMMARY

There is provided a method of planning a surgical tunnel during a surgical procedure. The method comprises receiving, by a surgical system, kinematic information related to a range of motion of a knee joint; registering, by the surgical system, one or more surfaces of a bony anatomy of the knee joint; generating, by the surgical system, a three-dimensional model of the knee joint, and determining, by the surgical system, a surgical plan based on the kinematic information and the three-dimensional model, wherein the surgical plan comprises one or more patient-specific graft tunnel parameters.

According to certain embodiments, receiving, by a surgical system, kinematic information related to a range of motion of a knee joint comprises affixing one or more tracking arrays to one or more bones of the patient; flexing and extending the knee joint through a range of motion; and recording, by a tracking system, a plurality of positions of the knee joint through the range of motion.

According to certain embodiments, the range of motion of the knee joint comprises at least one of a passive range of motion and a stressed range of motion.

According to certain embodiments, registering one or more surfaces of a bony anatomy of the knee joint comprises receiving, by a probe tracking system, a plurality of locations of a probe as the probe is moved across the one or more surfaces of the bony anatomy; and storing position information regarding the plurality of locations to characterize the one or more surfaces of the bony anatomy.

According to certain embodiments, determining a surgical plan comprises estimating one or more properties of the ligament graft performing a dynamic simulation of the knee joint based on the one or more properties of the ligament graft; and optimizing the one or more patient-specific graft tunnel parameters based on the dynamic simulation to minimize one or more of the amount of strain on the ligament graft, the amount of contact or stress on an entrance of the graft tunnel, impingement of the ligament graft, and anisometry of the tunnel. According to certain additional embodiments, the method further comprises determining a target tension for the ligament graft based on the dynamic simulation to produce a desired knee laxity. According to certain additional embodiments, the one or more properties of the ligament graft comprise one or more of cross-sectional area, cross-sectional geometry, elasticity, length, and a number of bundles of the ligament graft.

According to certain embodiments, the method further comprises forming one or more tunnel segments based on the surgical plan; fixing, by the surgeon, the ligament graft through the one or more tunnel segments; and performing, by the surgeon, one or more stability assessment tests upon the knee joint. According to certain additional embodiments, the one or more stability assessment tests comprise one or more of a Drawer test, a Lachman test, and a Pivot Shift test. According to certain additional embodiments, the method further comprises measuring a joint laxity value of the knee joint; comparing the joint laxity value of the knee joint with a joint laxity value of a non-operated knee joint of the patient; and adjusting an actual tension of the ligament graft based on the joint laxity value of the non-operated knee joint.

According to certain embodiments, determining a surgical plan further comprises receiving, by the surgical system, past procedure data from a remote database, wherein the past procedure data comprises graft tunnel parameters and patient outcome information; and optimizing the one or more patient-specific graft tunnel parameters based on the past procedure data. According to certain additional embodiments, optimizing the one or more patient-specific graft tunnel parameters based on past procedure data comprises utilizing machine learning techniques.

According to certain embodiments, the method further comprises displaying, by the surgical system, the surgical plan on a display screen; and inputting, by a surgeon, one or more alterations to one or more patient-specific graft tunnel parameters.

There is also provided a graft tunnel planning system for use during a surgical procedure. The system comprises a plurality of tracking markers configured to be affixed to one or more bones of a patient; a tracking unit configured to capture location data of the plurality of tracking markers at discrete intervals through a range of motion of a knee joint of the patient; a point probe configured to capture geometry data of a bony surface of the patient; and a computing module configured to receive the location data from the tracking unit; receive the geometry data from the point probe; and determine a surgical plan based on the location data and the geometry data, wherein the surgical plan comprises one or more patient-specific graft tunnel parameters.

According to certain embodiments, the computing module is further configured to calculate the range of motion of the knee joint based on the location data.

According to certain embodiments, the range of motion of the knee joint comprises at least one of a passive range of motion and a stressed range of motion.

According to certain embodiments, the computing module is further configured to generate a three-dimensional model of the knee joint of the patient based on the geometry data; estimate one or more properties of the ligament graft; perform a dynamic simulation of the knee joint based on the three-dimensional model of the knee joint and the one or more properties of the ligament graft; and optimize the one or more patient-specific graft tunnel parameters based on the dynamic simulation. According to certain additional embodiments, the computing module is further configured to minimize one or more of the amount of strain on the ligament graft, the amount of contact or stress on an entrance of the graft tunnel, impingement of the ligament graft, and anisometry of the tunnel. According to certain additional embodiments, the computing module is further configured to determine a target tension for the ligament graft based on the dynamic simulation to produce a desired knee laxity.

According to certain embodiments, the computing module is further configured to receive past procedure data from a remote database, wherein the past procedure data comprises graft tunnel parameters and patient outcome information; and optimize the one or more patient-specific graft tunnel parameters based on the past procedure data.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and form a part of the specification, illustrate the embodiments of the present disclosure and together with the written description serve to explain the principles, characteristics, and features of the present disclosure. In the drawings:

FIG. 1A depicts a knee having a tunnel formed by the transtibial tunnel creation technique.

FIG. 1B depicts a knee having a tunnel formed by the anteromedial tunnel creation technique.

FIG. 2 depicts an operating theatre including an illustrative computer-assisted surgical system (CASS) in accordance with an embodiment.

FIG. 3A depicts illustrative control instructions that a surgical computer provides to other components of a CASS in accordance with an embodiment.

FIG. 3B depicts illustrative control instructions that components of a CASS provide to a surgical computer in accordance with an embodiment.

FIG. 3C depicts an illustrative implementation in which a surgical computer is connected to a surgical data server via a network in accordance with an embodiment.

FIG. 4 depicts an operative patient care system and illustrative data sources in accordance with an embodiment.

FIG. 5A depicts an illustrative flow diagram for determining a pre-operative surgical plan in accordance with an embodiment.

FIG. 5B depicts an illustrative flow diagram for determining an episode of care including pre-operative, intraoperative, and post-operative actions in accordance with an embodiment.

FIG. 5C depicts illustrative graphical user interfaces including images depicting an implant placement in accordance with an embodiment.

FIG. 6 depicts a block diagram illustrating a system for providing navigation and control to a surgical tool according to an embodiment.

FIG. 7 depicts a diagram illustrating an environment for operating a system for navigation and control of a surgical tool during a surgical procedure according to an embodiment.

FIG. 8 depicts an illustrative flow diagram of an exemplary method of performing a surgical procedure according to an embodiment.

FIG. 9 depicts an exemplary display for use in planning the tunnel according to an embodiment.

FIG. 10 illustrates a block diagram of an illustrative data processing system in which aspects of the illustrative embodiments are implemented.

DETAILED DESCRIPTION

This disclosure is not limited to the particular systems, devices and methods described, as these may vary. The terminology used in the description is for the purpose of describing the particular versions or embodiments only, and is not intended to limit the scope.

As used in this document, the singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise. Unless defined otherwise, all technical and scientific terms used herein have the same meanings as commonly understood by one of ordinary skill in the art. Nothing in this disclosure is to be construed as an admission that the embodiments described in this disclosure are not entitled to antedate such disclosure by virtue of prior invention. As used in this document, the term “comprising” means “including, but not limited to.”

Definitions

For the purposes of this disclosure, the term “implant” is used to refer to a prosthetic device or structure manufactured to replace or enhance a biological structure. For example, in a total hip replacement procedure a prosthetic acetabular cup (implant) is used to replace or enhance a patients worn or damaged acetabulum. While the term “implant” is generally considered to denote a man-made structure (as contrasted with a transplant), for the purposes of this specification an implant can include a biological tissue or material transplanted to replace or enhance a biological structure.

For the purposes of this disclosure, the term “real-time” is used to refer to calculations or operations performed on-the-fly as events occur or input is received by the operable system. However, the use of the term “real-time” is not intended to preclude operations that cause some latency between input and response, so long as the latency is an unintended consequence induced by the performance characteristics of the machine.

Although much of this disclosure refers to surgeons or other medical professionals by specific job title or role, nothing in this disclosure is intended to be limited to a specific job title or function. Surgeons or medical professionals can include any doctor, nurse, medical professional, or technician. Any of these terms or job titles can be used interchangeably with the user of the systems disclosed herein unless otherwise explicitly demarcated. For example, a reference to a surgeon could also apply, in some embodiments to a technician or nurse.

CASS Ecosystem Overview

FIG. 2 provides an illustration of an example computer-assisted surgical system (CASS) 200, according to some embodiments. As described in further detail in the sections that follow, the CASS uses computers, robotics, and imaging technology to aid surgeons in performing orthopedic surgery procedures such as total knee arthroplasty (TKA) or total hip arthroplasty (THA). For example, surgical navigation systems can aid surgeons in locating patient anatomical structures, guiding surgical instruments, and implanting medical devices with a high degree of accuracy. Surgical navigation systems such as the CASS 200 often employ various forms of computing technology to perform a wide variety of standard and minimally invasive surgical procedures and techniques. Moreover, these systems allow surgeons to more accurately plan, track and navigate the placement of instruments and implants relative to the body of a patient, as well as conduct pre-operative and intra-operative body imaging.

An Effector Platform 205 positions surgical tools relative to a patient during surgery. The exact components of the Effector Platform 205 will vary, depending on the embodiment employed. For example, for a knee surgery, the Effector Platform 205 may include an End Effector 205B that holds surgical tools or instruments during their use. The End Effector 205B may be a handheld device or instrument used by the surgeon (e.g., a NAVIO@ hand piece or a cutting guide or jig) or, alternatively, the End Effector 205B can include a device or instrument held or positioned by a Robotic Arm 205A.

The Effector Platform 205 can include a Limb Positioner 205C for positioning the patient's limbs during surgery. One example of a Limb Positioner 205C is the SMITH AND NEPHEW SPIDER2 system. The Limb Positioner 205C may be operated manually by the surgeon or alternatively change limb positions based on instructions received from the Surgical Computer 250 (described below).

Resection Equipment 210 (not shown in FIG. 2) performs bone or tissue resection using, for example, mechanical, ultrasonic, or laser techniques. Examples of Resection Equipment 210 include drilling devices, burring devices, oscillatory sawing devices, vibratory impaction devices, reamers, ultrasonic bone cutting devices, radio frequency ablation devices, and laser ablation systems. In some embodiments, the Resection Equipment 210 is held and operated by the surgeon during surgery. In other embodiments, the Effector Platform 205 may be used to hold the Resection Equipment 210 during use.

The Effector Platform 205 can also include a cutting guide or jig 205D that is used to guide saws or drills used to resect tissue during surgery. Such cutting guides 205D can be formed integrally as part of the Effector Platform 205 or Robotic Arm 205A, or cutting guides can be separate structures that can be matingly and/or removably attached to the Effector Platform 205 or Robotic Arm 205A. The Effector Platform 205 or Robotic Arm 205A can be controlled by the CASS 200 to position a cutting guide or jig 205D adjacent to the patient's anatomy in accordance with a pre-operatively or intraoperatively developed surgical plan such that the cutting guide or jig will produce a precise bone cut in accordance with the surgical plan.

The Tracking System 215 uses one or more sensors to collect real-time position data that locates the patient's anatomy and surgical instruments. For example, for TKA procedures, the Tracking System may provide a location and orientation of the End Effector 205B during the procedure. In addition to positional data, data from the Tracking System 215 can also be used to infer velocity/acceleration of anatomy/instrumentation, which can be used for tool control. In some embodiments, the Tracking System 215 may use a tracker array attached to the End Effector 205B to determine the location and orientation of the End Effector 205B. The position of the End Effector 205B may be inferred based on the position and orientation of the Tracking System 215 and a known relationship in three-dimensional space between the Tracking System 215 and the End Effector 205B. Various types of tracking systems may be used in various embodiments of the present invention including, without limitation, Infrared (IR) tracking systems, electromagnetic (EM) tracking systems, video or image based tracking systems, and ultrasound registration and tracking systems.

Any suitable tracking system can be used for tracking surgical objects and patient anatomy in the surgical theatre. For example, a combination of IR and visible light cameras can be used in an array. Various illumination sources, such as an IR LED light source, can illuminate the scene allowing three-dimensional imaging to occur. In some embodiments, this can include stereoscopic, tri-scopic, quad-scopic, etc. imaging. In addition to the camera array, which in some embodiments is affixed to a cart, additional cameras can be placed throughout the surgical theatre. For example, handheld tools or headsets worn by operators/surgeons can include imaging capability that communicates images back to a central processor to correlate those images with images captured by the camera array. This can give a more robust image of the environment for modeling using multiple perspectives. Furthermore, some imaging devices may be of suitable resolution or have a suitable perspective on the scene to pick up information stored in quick response (QR) codes or barcodes. This can be helpful in identifying specific objects not manually registered with the system.

In some embodiments, specific objects can be manually registered by a surgeon with the system preoperatively or intraoperatively. For example, by interacting with a user interface, a surgeon may identify the starting location for a tool or a bone structure. By tracking fiducial marks associated with that tool or bone structure, or by using other conventional image tracking modalities, a processor may track that tool or bone as it moves through the environment in a three-dimensional model.

In some embodiments, certain markers, such as fiducial marks that identify individuals, important tools, or bones in the theater may include passive or active identifiers that can be picked up by a camera or camera array associated with the tracking system. For example, an IR LED can flash a pattern that conveys a unique identifier to the source of that pattern, providing a dynamic identification mark. Similarly, one or two dimensional optical codes (barcode. QR code, etc.) can be affixed to objects in the theater to provide passive identification that can occur based on image analysis. If these codes are placed asymmetrically on an object, they can also be used to determine an orientation of an object by comparing the location of the identifier with the extents of an object in an image. For example, a QR code may be placed in a corner of a tool tray, allowing the orientation and identity of that tray to be tracked. Other tracking modalities are explained throughout. For example, in some embodiments, augmented reality headsets can be worn by surgeons and other staff to provide additional camera angles and tracking capabilities.

In addition to optical tracking, certain features of objects can be tracked by registering physical properties of the object and associating them with objects that can be tracked, such as fiducial marks fixed to a tool or bone. For example, a surgeon may perform a manual registration process whereby a tracked tool and a tracked bone can be manipulated relative to one another. By impinging the tip of the tool against the surface of the bone, a three-dimensional surface can be mapped for that bone that is associated with a position and orientation relative to the frame of reference of that fiducial mark. By optically tracking the position and orientation (pose) of the fiducial mark associated with that bone, a model of that surface can be tracked with an environment through extrapolation.

The registration process that registers the CASS 200 to the relevant anatomy of the patient can also involve the use of anatomical landmarks, such as landmarks on a bone or cartilage. For example, the CASS 200 can include a 3D model of the relevant bone or joint and the surgeon can intraoperatively collect data regarding the location of bony landmarks on the patient's actual bone using a probe that is connected to the CASS. Bony landmarks can include, for example, the medial malleolus and lateral malleolus, the ends of the proximal femur and distal tibia, and the center of the hip joint. The CASS 200 can compare and register the location data of bony landmarks collected by the surgeon with the probe with the location data of the same landmarks in the 3D model. Alternatively, the CASS 200 can construct a 3D model of the bone or joint without pre-operative image data by using location data of bony landmarks and the bone surface that are collected by the surgeon using a CASS probe or other means. The registration process can also include determining various axes of a joint. For example, for a TKA the surgeon can use the CASS 200 to determine the anatomical and mechanical axes of the femur and tibia. The surgeon and the CASS 200 can identify the center of the hip joint by moving the patient's leg in a spiral direction (i.e., circumduction) so the CASS can determine where the center of the hip joint is located.

A Tissue Navigation System 220 (not shown in FIG. 2) provides the surgeon with intraoperative, real-time visualization for the patient's bone, cartilage, muscle, nervous, and/or vascular tissues surrounding the surgical area. Examples of systems that may be employed for tissue navigation include fluorescent imaging systems and ultrasound systems.

The Display 225 provides graphical user interfaces (GUIs) that display images collected by the Tissue Navigation System 220 as well other information relevant to the surgery. For example, in one embodiment, the Display 225 overlays image information collected from various modalities (e.g., CT, MRI, X-ray, fluorescent, ultrasound, etc.) collected pre-operatively or intra-operatively to give the surgeon various views of the patient's anatomy as well as real-time conditions. The Display 225 may include, for example, one or more computer monitors. As an alternative or supplement to the Display 225, one or more members of the surgical staff may wear an Augmented Reality (AR) Head Mounted Device (HMD). For example, in FIG. 2 the Surgeon 211 is wearing an AR HMD 255 that may, for example, overlay pre-operative image data on the patient or provide surgical planning suggestions. Various example uses of the AR HMD 255 in surgical procedures are detailed in the sections that follow.

Surgical Computer 250 provides control instructions to various components of the CASS 200, collects data from those components, and provides general processing for various data needed during surgery. In some embodiments, the Surgical Computer 250 is a general purpose computer. In other embodiments, the Surgical Computer 250 may be a parallel computing platform that uses multiple central processing units (CPUs) or graphics processing units (GPU) to perform processing. In some embodiments, the Surgical Computer 250 is connected to a remote server over one or more computer networks (e.g., the Internet). The remote server can be used, for example, for storage of data or execution of computationally intensive processing tasks.

Various techniques generally known in the art can be used for connecting the Surgical Computer 250 to the other components of the CASS 200. Moreover, the computers can connect to the Surgical Computer 250 using a mix of technologies. For example, the End Effector 205B may connect to the Surgical Computer 250 over a wired (i.e., serial) connection. The Tracking System 215, Tissue Navigation System 220, and Display 225 can similarly be connected to the Surgical Computer 250 using wired connections. Alternatively, the Tracking System 215. Tissue Navigation System 220, and Display 225 may connect to the Surgical Computer 250 using wireless technologies such as, without limitation, Wi-Fi, Bluetooth, Near Field Communication (NFC), or ZigBee.

Powered Impaction and Acetabular Reamer Devices

Part of the flexibility of the CASS design described above with respect to FIG. 2 is that additional or alternative devices can be added to the CASS 200 as necessary to support particular surgical procedures. For example, in the context of hip surgeries, the CASS 200 may include a powered impaction device. Impaction devices are designed to repeatedly apply an impaction force that the surgeon can use to perform activities such as implant alignment. For example, within a total hip arthroplasty (THA), a surgeon will often insert a prosthetic acetabular cup into the implant host's acetabulum using an impaction device. Although impaction devices can be manual in nature (e.g., operated by the surgeon striking an impactor with a mallet), powered impaction devices are generally easier and quicker to use in the surgical setting. Powered impaction devices may be powered, for example, using a battery attached to the device. Various attachment pieces may be connected to the powered impaction device to allow the impaction force to be directed in various ways as needed during surgery. Also in the context of hip surgeries, the CASS 200 may include a powered, robotically controlled end effector to ream the acetabulum to accommodate an acetabular cup implant.

In a robotically-assisted THA, the patient's anatomy can be registered to the CASS 200 using CT or other image data, the identification of anatomical landmarks, tracker arrays attached to the patient's bones, and one or more cameras. Tracker arrays can be mounted on the iliac crest using clamps and/or bone pins and such trackers can be mounted externally through the skin or internally (either posterolaterally or anterolaterally) through the incision made to perform the THA. For a THA, the CASS 200 can utilize one or more femoral cortical screws inserted into the proximal femur as checkpoints to aid in the registration process. The CASS 200 can also utilize one or more checkpoint screws inserted into the pelvis as additional checkpoints to aid in the registration process. Femoral tracker arrays can be secured to or mounted in the femoral cortical screws. The CASS 200 can employ steps where the registration is verified using a probe that the surgeon precisely places on key areas of the proximal femur and pelvis identified for the surgeon on the display 225. Trackers can be located on the robotic arm 205A or end effector 205B to register the arm and/or end effector to the CASS 200. The verification step can also utilize proximal and distal femoral checkpoints. The CASS 200 can utilize color prompts or other prompts to inform the surgeon that the registration process for the relevant bones and the robotic arm 205A or end effector 205B has been verified to a certain degree of accuracy (e.g., within 1 mm).

For a THA, the CASS 200 can include a broach tracking option using femoral arrays to allow the surgeon to intraoperatively capture the broach position and orientation and calculate hip length and offset values for the patient. Based on information provided about the patient's hip joint and the planned implant position and orientation after broach tracking is completed, the surgeon can make modifications or adjustments to the surgical plan.

For a robotically-assisted THA, the CASS 200 can include one or more powered reamers connected or attached to a robotic arm 205A or end effector 205B that prepares the pelvic bone to receive an acetabular implant according to a surgical plan. The robotic arm 205A and/or end effector 205B can inform the surgeon and/or control the power of the reamer to ensure that the acetabulum is being resected (reamed) in accordance with the surgical plan. For example, if the surgeon attempts to resect bone outside of the boundary of the bone to be resected in accordance with the surgical plan, the CASS 200 can power off the reamer or instruct the surgeon to power off the reamer. The CASS 200 can provide the surgeon with an option to turn off or disengage the robotic control of the reamer. The display 225 can depict the progress of the bone being resected (reamed) as compared to the surgical plan using different colors. The surgeon can view the display of the bone being resected (reamed) to guide the reamer to complete the reaming in accordance with the surgical plan. The CASS 200 can provide visual or audible prompts to the surgeon to warn the surgeon that resections are being made that are not in accordance with the surgical plan.

Following reaming, the CASS 200 can employ a manual or powered impactor that is attached or connected to the robotic arm 205A or end effector 205B to impact trial implants and final implants into the acetabulum. The robotic arm 205A and/or end effector 205B can be used to guide the impactor to impact the trial and final implants into the acetabulum in accordance with the surgical plan. The CASS 200 can cause the position and orientation of the trial and final implants vis-à-vis the bone to be displayed to inform the surgeon as to how the trial and final implant's orientation and position compare to the surgical plan, and the display 225 can show the implant's position and orientation as the surgeon manipulates the leg and hip. The CASS 200 can provide the surgeon with the option of re-planning and re-doing the reaming and implant impaction by preparing a new surgical plan if the surgeon is not satisfied with the original implant position and orientation.

Preoperatively, the CASS 200 can develop a proposed surgical plan based on a three dimensional model of the hip joint and other information specific to the patient, such as the mechanical and anatomical axes of the leg bones, the epicondylar axis, the femoral neck axis, the dimensions (e.g., length) of the femur and hip, the midline axis of the hip joint, the ASIS axis of the hip joint, and the location of anatomical landmarks such as the lesser trochanter landmarks, the distal landmark, and the center of rotation of the hip joint. The CASS-developed surgical plan can provide a recommended optimal implant size and implant position and orientation based on the three dimensional model of the hip joint and other information specific to the patient. The CASS-developed surgical plan can include proposed details on offset values, inclination and anteversion values, center of rotation, cup size, medialization values, superior-inferior fit values, femoral stem sizing and length.

For a THA, the CASS-developed surgical plan can be viewed preoperatively and intraoperatively, and the surgeon can modify CASS-developed surgical plan preoperatively or intraoperatively. The CASS-developed surgical plan can display the planned resection to the hip joint and superimpose the planned implants onto the hip joint based on the planned resections. The CASS 200 can provide the surgeon with options for different surgical workflows that will be displayed to the surgeon based on a surgeon's preference. For example, the surgeon can choose from different workflows based on the number and types of anatomical landmarks that are checked and captured and/or the location and number of tracker arrays used in the registration process.

According to some embodiments, a powered impaction device used with the CASS 200 may operate with a variety of different settings. In some embodiments, the surgeon adjusts settings through a manual switch or other physical mechanism on the powered impaction device. In other embodiments, a digital interface may be used that allows setting entry, for example, via a touchscreen on the powered impaction device. Such a digital interface may allow the available settings to vary based, for example, on the type of attachment piece connected to the power attachment device. In some embodiments, rather than adjusting the settings on the powered impaction device itself, the settings can be changed through communication with a robot or other computer system within the CASS 200. Such connections may be established using, for example, a Bluetooth or Wi-Fi networking module on the powered impaction device. In another embodiment, the impaction device and end pieces may contain features that allow the impaction device to be aware of what end piece (cup impactor, broach handle, etc.) is attached with no action required by the surgeon, and adjust the settings accordingly. This may be achieved, for example, through a QR code, barcode, RFID tag, or other method.

Examples of the settings that may be used include cup impaction settings (e.g., single direction, specified frequency range, specified force and/or energy range); broach impaction settings (e.g., dual direction/oscillating at a specified frequency range, specified force and/or energy range); femoral head impaction settings (e.g., single direction/single blow at a specified force or energy); and stem impaction settings (e.g., single direction at specified frequency with a specified force or energy). Additionally, in some embodiments, the powered impaction device includes settings related to acetabular liner impaction (e.g., single direction/single blow at a specified force or energy). There may be a plurality of settings for each type of liner such as poly, ceramic, oxinium, or other materials. Furthermore, the powered impaction device may offer settings for different bone quality based on preoperative testing/imaging/knowledge and/or intraoperative assessment by surgeon.

In some embodiments, the powered impaction device includes feedback sensors that gather data during instrument use, and send data to a computing device such as a controller within the device or the Surgical Computer 250. This computing device can then record the data for later analysis and use. Examples of the data that may be collected include, without limitation, sound waves, the predetermined resonance frequency of each instrument, reaction force or rebound energy from patient bone, location of the device with respect to imaging (e.g., fluoro, CT, ultrasound, MRI, etc.) registered bony anatomy, and/or external strain gauges on bones.

Once the data is collected, the computing device may execute one or more algorithms in real-time or near real-time to aid the surgeon in performing the surgical procedure. For example, in some embodiments, the computing device uses the collected data to derive information such as the proper final broach size (femur); when the stem is fully seated (femur side), or when the cup is seated (depth and/or orientation) for a THA. Once the information is known, it may be displayed for the surgeon's review, or it may be used to activate haptics or other feedback mechanisms to guide the surgical procedure.

Additionally, the data derived from the aforementioned algorithms may be used to drive operation of the device. For example, during insertion of a prosthetic acetabular cup with a powered impaction device, the device may automatically extend an impaction head (e.g., an end effector) moving the implant into the proper location, or turn the power off to the device once the implant is fully seated. In one embodiment, the derived information may be used to automatically adjust settings for quality of bone where the powered impaction device should use less power to mitigate femoral/acetabular/pelvic fracture or damage to surrounding tissues.

Robotic Arm

In some embodiments, the CASS 200 includes a robotic arm 205A that serves as an interface to stabilize and hold a variety of instruments used during the surgical procedure. For example, in the context of a hip surgery, these instruments may include, without limitation, retractors, a sagittal or reciprocating saw, the reamer handle, the cup impactor, the broach handle, and the stem inserter. The robotic arm 205A may have multiple degrees of freedom (like a Spider device), and have the ability to be locked in place (e.g., by a press of a button, voice activation, a surgeon removing a hand from the robotic arm, or other method).

In some embodiments, movement of the robotic arm 205A may be effectuated by use of a control panel built into the robotic arm system. For example, a display screen may include one or more input sources, such as physical buttons or a user interface having one or more icons, that direct movement of the robotic arm 205A. The surgeon or other healthcare professional may engage with the one or more input sources to position the robotic arm 205A when performing a surgical procedure.

A tool or an end effector 205B attached or integrated into a robotic arm 205A may include, without limitation, a burring device, a scalpel, a cutting device, a retractor, a joint tensioning device, or the like. In embodiments in which an end effector 205B is used, the end effector may be positioned at the end of the robotic arm 205A such that any motor control operations are performed within the robotic arm system. In embodiments in which a tool is used, the tool may be secured at a distal end of the robotic arm 205A, but motor control operation may reside within the tool itself.

The robotic arm 205A may be motorized internally to both stabilize the robotic arm, thereby preventing it from falling and hitting the patient, surgical table, surgical staff, etc., and to allow the surgeon to move the robotic arm without having to fully support its weight. While the surgeon is moving the robotic arm 205A, the robotic arm may provide some resistance to prevent the robotic arm from moving too fast or having too many degrees of freedom active at once. The position and the lock status of the robotic arm 205A may be tracked, for example, by a controller or the Surgical Computer 250.

In some embodiments, the robotic arm 205A can be moved by hand (e.g., by the surgeon) or with internal motors into its ideal position and orientation for the task being performed. In some embodiments, the robotic arm 205A may be enabled to operate in a “free” mode that allows the surgeon to position the arm into a desired position without being restricted. While in the free mode, the position and orientation of the robotic arm 205A may still be tracked as described above. In one embodiment, certain degrees of freedom can be selectively released upon input from user (e.g., surgeon) during specified portions of the surgical plan tracked by the Surgical Computer 250. Designs in which a robotic arm 205A is internally powered through hydraulics or motors or provides resistance to external manual motion through similar means can be described as powered robotic arms, while arms that are manually manipulated without power feedback, but which may be manually or automatically locked in place, may be described as passive robotic arms.

A robotic arm 205A or end effector 205B can include a trigger or other means to control the power of a saw or drill. Engagement of the trigger or other means by the surgeon can cause the robotic arm 205A or end effector 205B to transition from a motorized alignment mode to a mode where the saw or drill is engaged and powered on. Additionally, the CASS 200 can include a foot pedal (not shown) that causes the system to perform certain functions w % ben activated. For example, the surgeon can activate the foot pedal to instruct the CASS 200 to place the robotic arm 205A or end effector 205B in an automatic mode that brings the robotic arm or end effector into the proper position with respect to the patient's anatomy in order to perform the necessary resections. The CASS 200 can also place the robotic arm 205A or end effector 205B in a collaborative mode that allows the surgeon to manually manipulate and position the robotic arm or end effector into a particular location. The collaborative mode can be configured to allow the surgeon to move the robotic arm 205A or end effector 205B medially or laterally, while restricting movement in other directions. As discussed, the robotic arm 205A or end effector 205B can include a cutting device (saw, drill, and burr) or a cutting guide or jig 205D that will guide a cutting device. In other embodiments, movement of the robotic arm 205A or robotically controlled end effector 205B can be controlled entirely by the CASS 200 without any, or with only minimal, assistance or input from a surgeon or other medical professional. In still other embodiments, the movement of the robotic arm 205A or robotically controlled end effector 205B can be controlled remotely by a surgeon or other medical professional using a control mechanism separate from the robotic arm or robotically controlled end effector device, for example using a joystick or interactive monitor or display control device.

The examples below describe uses of the robotic device in the context of a hip surgery; however, it should be understood that the robotic arm may have other applications for surgical procedures involving knees, shoulders, etc. One example of use of a robotic arm in the context of forming an anterior cruciate ligament (ACL) graft tunnel is described in U.S. Provisional Patent Application No. 62/723,898 filed Aug. 28, 2018 and entitled “Robotic Assisted Ligament Graft Placement and Tensioning.” the entirety of which is incorporated herein by reference.

A robotic arm 205A may be used for holding the retractor. For example in one embodiment, the robotic arm 205A may be moved into the desired position by the surgeon. At that point, the robotic arm 205A may lock into place. In some embodiments, the robotic arm 205A is provided with data regarding the patient's position, such that if the patient moves, the robotic arm can adjust the retractor position accordingly. In some embodiments, multiple robotic arms may be used, thereby allowing multiple retractors to be held or for more than one activity to be performed simultaneously (e.g., retractor holding & reaming).

The robotic arm 205A may also be used to help stabilize the surgeon's hand while making a femoral neck cut. In this application, control of the robotic arm 205A may impose certain restrictions to prevent soft tissue damage from occurring. For example, in one embodiment, the Surgical Computer 250 tracks the position of the robotic arm 205A as it operates. If the tracked location approaches an area where tissue damage is predicted, a command may be sent to the robotic arm 205A causing it to stop. Alternatively, where the robotic arm 205A is automatically controlled by the Surgical Computer 250, the Surgical Computer may ensure that the robotic arm is not provided with any instructions that cause it to enter areas where soft tissue damage is likely to occur. The Surgical Computer 250 may impose certain restrictions on the surgeon to prevent the surgeon from reaming too far into the medial wall of the acetabulum or reaming at an incorrect angle or orientation.

In some embodiments, the robotic arm 205A may be used to hold a cup impactor at a desired angle or orientation during cup impaction. When the final position has been achieved, the robotic arm 205A may prevent any further seating to prevent damage to the pelvis.

The surgeon may use the robotic arm 205A to position the broach handle at the desired position and allow the surgeon to impact the broach into the femoral canal at the desired orientation. In some embodiments, once the Surgical Computer 250 receives feedback that the broach is fully seated, the robotic arm 205A may restrict the handle to prevent further advancement of the broach.

The robotic arm 205A may also be used for resurfacing applications. For example, the robotic arm 205A may stabilize the surgeon while using traditional instrumentation and provide certain restrictions or limitations to allow for proper placement of implant components (e.g., guide wire placement, chamfer cutter, sleeve cutter, plan cutter, etc.). Where only a burr is employed, the robotic arm 205A may stabilize the surgeon's handpiece and may impose restrictions on the handpiece to prevent the surgeon from removing unintended bone in contravention of the surgical plan.

Surgical Procedure Data Generation and Collection

The various services that are provided by medical professionals to treat a clinical condition are collectively referred to as an “episode of care.” For a particular surgical intervention the episode of care can include three phases; pre-operative, intra-operative, and post-operative. During each phase, data is collected or generated that can be used to analyze the episode of care in order to understand various aspects of the procedure and identify patterns that may be used, for example, in training models to make decisions with minimal human intervention. The data collected over the episode of care may be stored at the Surgical Computer 250 or the Surgical Data Server 280 as a complete dataset. Thus, for each episode of care, a dataset exists that comprises all of the data collectively pre-operatively about the patient, all of the data collected or stored by the CASS 200 intra-operatively, and any post-operative data provided by the patient or by a healthcare professional monitoring the patient.

As explained in further detail, the data collected during the episode of care may be used to enhance performance of the surgical procedure or to provide a holistic understanding of the surgical procedure and the patient outcomes. For example, in some embodiments, the data collected over the episode of care may be used to generate a surgical plan. In one embodiment, a high-level, pre-operative plan is refined intra-operatively as data is collected during surgery. In this way, the surgical plan can be viewed as dynamically changing in real-time or near real-time as new data is collected by the components of the CASS 200. In other embodiments, pre-operative images or other input data may be used to develop a robust plan preoperatively that is simply executed during surgery. In this case, the data collected by the CASS 200 during surgery may be used to make recommendations that ensure that the surgeon stays within the pre-operative surgical plan. For example, if the surgeon is unsure how to achieve a certain prescribed cut or implant alignment, the Surgical Computer 250 can be queried for a recommendation. In still other embodiments, the pre-operative and intra-operative planning approaches can be combined such that a robust pre-operative plan can be dynamically modified, as necessary or desired, during the surgical procedure. In some embodiments, a biomechanics-based model of patient anatomy contributes simulation data to be considered by the CASS 200 in developing preoperative, intraoperative, and post-operative/rehabilitation procedures to optimize implant performance outcomes for the patient.

Aside from changing the surgical procedure itself, the data gathered during the episode of care may be used as an input to other procedures ancillary to the surgery. For example, in some embodiments, implants can be designed using episode of care data. Example data-driven techniques for designing, sizing, and fitting implants are described in U.S. patent application Ser. No. 13/814,531 filed Aug. 15, 2011 and entitled “Systems and Methods for Optimizing Parameters for Orthopaedic Procedures”; U.S. patent application Ser. No. 14/232,958 filed Jul. 20, 2012 and entitled “Systems and Methods for Optimizing Fit of an Implant to Anatomy”; and U.S. patent application Ser. No. 12/234,444 filed Sep. 19, 2008 and entitled “Operatively Tuning Implants for Increased Performance,” the entire contents of each of which are hereby incorporated by reference into this patent application.

Furthermore, the data can be used for educational, training, or research purposes. For example, using the network-based approach described below in FIG. 3C, other doctors or students can remotely view surgeries in interfaces that allow them to selectively view data as it is collected from the various components of the CASS 200. After the surgical procedure, similar interfaces may be used to “playback” a surgery for training or other educational purposes, or to identify the source of any issues or complications with the procedure.

Data acquired during the pre-operative phase generally includes all information collected or generated prior to the surgery. Thus, for example, information about the patient may be acquired from a patient intake form or electronic medical record (EMR). Examples of patient information that may be collected include, without limitation, patient demographics, diagnoses, medical histories, progress notes, vital signs, medical history information, allergies, and lab results. The pre-operative data may also include images related to the anatomical area of interest. These images may be captured, for example, using Magnetic Resonance Imaging (MRI), Computed Tomography (CT), X-ray, ultrasound, or any other modality known in the art. The pre-operative data may also comprise quality of life data captured from the patient. For example, in one embodiment, pre-surgery patients use a mobile application (“app”) to answer questionnaires regarding their current quality of life. In some embodiments, preoperative data used by the CASS 200 includes demographic, anthropometric, cultural, or other specific traits about a patient that can coincide with activity levels and specific patient activities to customize the surgical plan to the patient. For example, certain cultures or demographics may be more likely to use a toilet that requires squatting on a daily basis.

FIGS. 3A and 3B provide examples of data that may be acquired during the intra-operative phase of an episode of care. These examples are based on the various components of the CASS 200 described above with reference to FIG. 2; however, it should be understood that other types of data may be used based on the types of equipment used during surgery and their use.

FIG. 3A shows examples of some of the control instructions that the Surgical Computer 250 provides to other components of the CASS 200, according to some embodiments. Note that the example of FIG. 3A assumes that the components of the Effector Platform 205 are each controlled directly by the Surgical Computer 250. In embodiments where a component is manually controlled by the Surgeon 211, instructions may be provided on the Display 225 or AR HMD 255 instructing the Surgeon 211 how to move the component.

The various components included in the Effector Platform 205 are controlled by the Surgical Computer 250 providing position commands that instruct the component where to move within a coordinate system. In some embodiments, the Surgical Computer 250 provides the Effector Platform 205 with instructions defining how to react when a component of the Effector Platform 205 deviates from a surgical plan. These commands are referenced in FIG. 3A as “haptic” commands. For example, the End Effector 205B may provide a force to resist movement outside of an area where resection is planned. Other commands that may be used by the Effector Platform 205 include vibration and audio cues.

In some embodiments, the end effectors 205B of the robotic arm 205A are operatively coupled with cutting guide 205D. In response to an anatomical model of the surgical scene, the robotic arm 205A can move the end effectors 205B and the cutting guide 205D into position to match the location of the femoral or tibial cut to be performed in accordance with the surgical plan. This can reduce the likelihood of error, allowing the vision system and a processor utilizing that vision system to implement the surgical plan to place a cutting guide 205D at the precise location and orientation relative to the tibia or femur to align a cutting slot of the cutting guide with the cut to be performed according to the surgical plan. Then, a surgeon can use any suitable tool, such as an oscillating or rotating saw or drill to perform the cut (or drill a hole) with perfect placement and orientation because the tool is mechanically limited by the features of the cutting guide 205D. In some embodiments, the cutting guide 205D may include one or more pin holes that are used by a surgeon to drill and screw or pin the cutting guide into place before performing a resection of the patient tissue using the cutting guide. This can free the robotic arm 205A or ensure that the cutting guide 205D is fully affixed without moving relative to the bone to be resected. For example, this procedure can be used to make the first distal cut of the femur during a total knee arthroplasty. In some embodiments, where the arthroplasty is a hip arthroplasty, cutting guide 205D can be fixed to the femoral head or the acetabulum for the respective hip arthroplasty resection. It should be understood that any arthroplasty that utilizes precise cuts can use the robotic arm 205A and/or cutting guide 205D in this manner.

The Resection Equipment 210 is provided with a variety of commands to perform bone or tissue operations. As with the Effector Platform 205, position information may be provided to the Resection Equipment 210 to specify where it should be located when performing resection. Other commands provided to the Resection Equipment 210 may be dependent on the type of resection equipment. For example, for a mechanical or ultrasonic resection tool, the commands may specify the speed and frequency of the tool. For Radiofrequency Ablation (RFA) and other laser ablation tools, the commands may specify intensity and pulse duration.

Some components of the CASS 200 do not need to be directly controlled by the Surgical Computer 250, rather, the Surgical Computer 250 only needs to activate the component, which then executes software locally specifying the manner in which to collect data and provide it to the Surgical Computer 250. In the example of FIG. 3A, there are two components that are operated in this manner: the Tracking System 215 and the Tissue Navigation System 220.

The Surgical Computer 250 provides the Display 225 with any visualization that is needed by the Surgeon 211 during surgery. For monitors, the Surgical Computer 250 may provide instructions for displaying images, GUIs, etc. using techniques known in the art. The display 225 can include various aspects of the workflow of a surgical plan. During the registration process, for example, the display 225 can show a preoperatively constructed 3D bone model and depict the locations of the probe as the surgeon uses the probe to collect locations of anatomical landmarks on the patient. The display 225 can include information about the surgical target area. For example, in connection with a TKA, the display 225 can depict the mechanical and anatomical axes of the femur and tibia. The display 225 can depict varus and valgus angles for the knee joint based on a surgical plan, and the CASS 200 can depict how such angles will be affected if contemplated revisions to the surgical plan are made. Accordingly, the display 225 is an interactive interface that can dynamically update and display how changes to the surgical plan would impact the procedure and the final position and orientation of implants installed on bone.

As the workflow progresses to preparation of bone cuts or resections, the display 225 can depict the planned or recommended bone cuts before any cuts are performed. The surgeon 211 can manipulate the image display to provide different anatomical perspectives of the target area and can have the option to alter or revise the planned bone cuts based on intraoperative evaluation of the patient. The display 225 can depict how the chosen implants would be installed on the bone if the planned bone cuts are performed. If the surgeon 211 choses to change the previously planned bone cuts, the display 225 can depict how the revised bone cuts would change the position and orientation of the implant when installed on the bone.

The display 225 can provide the surgeon 211 with a variety of data and information about the patient, the planned surgical intervention, and the implants. Various patient-specific information can be displayed, including real-time data concerning the patient's health such as heart rate, blood pressure, etc. The display 225 can also include information about the anatomy of the surgical target region including the location of landmarks, the current state of the anatomy (e.g., whether any resections have been made, the depth and angles of planned and executed bone cuts), and future states of the anatomy as the surgical plan progresses. The display 225 can also provide or depict additional information about the surgical target region. For a TKA, the display 225 can provide information about the gaps (e.g., gap balancing) between the femur and tibia and how such gaps will change if the planned surgical plan is carried out. For a TKA, the display 225 can provide additional relevant information about the knee joint such as data about the joint's tension (e.g., ligament laxity) and information concerning rotation and alignment of the joint. The display 225 can depict how the planned implants' locations and positions will affect the patient as the knee joint is flexed. The display 225 can depict how the use of different implants or the use of different sizes of the same implant will affect the surgical plan and preview how such implants will be positioned on the bone. The CASS 200 can provide such information for each of the planned bone resections in a TKA or THA. In a TKA, the CASS 200 can provide robotic control for one or more of the planned bone resections. For example, the CASS 200 can provide robotic control only for the initial distal femur cut, and the surgeon 211 can manually perform other resections (anterior, posterior and chamfer cuts) using conventional means, such as a 4-in-1 cutting guide or jig 205D.

The display 225 can employ different colors to inform the surgeon of the status of the surgical plan. For example, un-resected bone can be displayed in a first color, resected bone can be displayed in a second color, and planned resections can be displayed in a third color. Implants can be superimposed onto the bone in the display 225, and implant colors can change or correspond to different types or sizes of implants.

The information and options depicted on the display 225 can vary depending on the type of surgical procedure being performed. Further, the surgeon 211 can request or select a particular surgical workflow display that matches or is consistent with his or her surgical plan preferences. For example, for a surgeon 211 who typically performs the tibial cuts before the femoral cuts in a TKA, the display 225 and associated workflow can be adapted to take this preference into account. The surgeon 211 can also preselect that certain steps be included or deleted from the standard surgical workflow display. For example, if a surgeon 211 uses resection measurements to finalize an implant plan but does not analyze ligament gap balancing when finalizing the implant plan, the surgical workflow display can be organized into modules, and the surgeon can select which modules to display and the order in which the modules are provided based on the surgeon's preferences or the circumstances of a particular surgery. Modules directed to ligament and gap balancing, for example, can include pre- and post-resection ligament/gap balancing, and the surgeon 211 can select which modules to include in their default surgical plan workflow depending on whether they perform such ligament and gap balancing before or after (or both) bone resections are performed.

For more specialized display equipment, such as AR HMDs, the Surgical Computer 250 may provide images, text, etc. using the data format supported by the equipment. For example, if the Display 225 is a holography device such as the Microsoft HoloLens™ or Magic Leap One™, the Surgical Computer 250 may use the HoloLens Application Program Interface (API) to send commands specifying the position and content of holograms displayed in the field of view of the Surgeon 211.

In some embodiments, one or more surgical planning models may be incorporated into the CASS 200 and used in the development of the surgical plans provided to the surgeon 211. The term “surgical planning model” refers to software that simulates the biomechanics performance of anatomy under various scenarios to determine the optimal way to perform cutting and other surgical activities. For example, for knee replacement surgeries, the surgical planning model can measure parameters for functional activities, such as deep knee bends, gait, etc., and select cut locations on the knee to optimize implant placement. One example of a surgical planning model is the LIFEMOD™ simulation software from SMITH AND NEPHEW, INC. In some embodiments, the Surgical Computer 250 includes computing architecture that allows full execution of the surgical planning model during surgery (e.g., a GPU-based parallel processing environment). In other embodiments, the Surgical Computer 250 may be connected over a network to a remote computer that allows such execution, such as a Surgical Data Server 280 (see FIG. 3C). As an alternative to full execution of the surgical planning model, in some embodiments, a set of transfer functions are derived that simplify the mathematical operations captured by the model into one or more predictor equations. Then, rather than execute the full simulation during surgery, the predictor equations are used. Further details on the use of transfer functions are described in U.S. Provisional Patent Application No. 62/719,415 entitled “Patient Specific Surgical Method and System.” the entirety of which is incorporated herein by reference.

FIG. 3B shows examples of some of the types of data that can be provided to the Surgical Computer 250 from the various components of the CASS 200. In some embodiments, the components may stream data to the Surgical Computer 250 in real-time or near real-time during surgery. In other embodiments, the components may queue data and send it to the Surgical Computer 250 at set intervals (e.g., every second). Data may be communicated using any format known in the art. Thus, in some embodiments, the components all transmit data to the Surgical Computer 250 in a common format. In other embodiments, each component may use a different data format, and the Surgical Computer 250 is configured with one or more software applications that enable translation of the data.

In general, the Surgical Computer 250 may serve as the central point where CASS data is collected. The exact content of the data will vary depending on the source. For example, each component of the Effector Platform 205 provides a measured position to the Surgical Computer 250. Thus, by comparing the measured position to a position originally specified by the Surgical Computer 250 (see FIG. 3B), the Surgical Computer can identify deviations that take place during surgery.

The Resection Equipment 210 can send various types of data to the Surgical Computer 250 depending on the type of equipment used. Example data types that may be sent include the measured torque, audio signatures, and measured displacement values. Similarly, the Tracking Technology 215 can provide different types of data depending on the tracking methodology employed. Example tracking data types include position values for tracked items (e.g., anatomy, tools, etc.), ultrasound images, and surface or landmark collection points or axes. The Tissue Navigation System 220 provides the Surgical Computer 250 with anatomic locations, shapes, etc. as the system operates.

Although the Display 225 generally is used for outputting data for presentation to the user, it may also provide data to the Surgical Computer 250. For example, for embodiments where a monitor is used as part of the Display 225, the Surgeon 211 may interact with a GUI to provide inputs which are sent to the Surgical Computer 250 for further processing. For AR applications, the measured position and displacement of the HMD may be sent to the Surgical Computer 250 so that it can update the presented view as needed.

During the post-operative phase of the episode of care, various types of data can be collected to quantify the overall improvement or deterioration in the patient's condition as a result of the surgery. The data can take the form of, for example, self-reported information reported by patients via questionnaires. For example, in the context of a knee replacement surgery, functional status can be measured with an Oxford Knee Score questionnaire, and the post-operative quality of life can be measured with a EQ5D-5L questionnaire. Other examples in the context of a hip replacement surgery may include the Oxford Hip Score, Harris Hip Score, and WOMAC (Western Ontario and McMaster Universities Osteoarthritis index). Such questionnaires can be administered, for example, by a healthcare professional directly in a clinical setting or using a mobile app that allows the patient to respond to questions directly. In some embodiments, the patient may be outfitted with one or more wearable devices that collect data relevant to the surgery. For example, following a knee surgery, the patient may be outfitted with a knee brace that includes sensors that monitor knee positioning, flexibility, etc. This information can be collected and transferred to the patient's mobile device for review by the surgeon to evaluate the outcome of the surgery and address any issues. In some embodiments, one or more cameras can capture and record the motion of a patient's body segments during specified activities postoperatively. This motion capture can be compared to a biomechanics model to better understand the functionality of the patient's joints and better predict progress in recovery and identify any possible revisions that may be needed.

The post-operative stage of the episode of care can continue over the entire life of a patient. For example, in some embodiments, the Surgical Computer 250 or other components comprising the CASS 200 can continue to receive and collect data relevant to a surgical procedure after the procedure has been performed. This data may include, for example, images, answers to questions, “normal” patient data (e.g., blood type, blood pressure, conditions, medications, etc.), biometric data (e.g., gait, etc.), and objective and subjective data about specific issues (e.g., knee or hip joint pain). This data may be explicitly provided to the Surgical Computer 250 or other CASS component by the patient or the patient's physician(s). Alternatively or additionally, the Surgical Computer 250 or other CASS component can monitor the patient's EMR and retrieve relevant information as it becomes available. This longitudinal view of the patient's recovery allows the Surgical Computer 250 or other CASS component to provide a more objective analysis of the patient's outcome to measure and track success or lack of success for a given procedure. For example, a condition experienced by a patient long after the surgical procedure can be linked back to the surgery through a regression analysis of various data items collected during the episode of care. This analysis can be further enhanced by performing the analysis on groups of patients that had similar procedures and/or have similar anatomies.

In some embodiments, data is collected at a central location to provide for easier analysis and use. Data can be manually collected from various CASS components in some instances. For example, a portable storage device (e.g., USB stick) can be attached to the Surgical Computer 250 into order to retrieve data collected during surgery. The data can then be transferred, for example, via a desktop computer to the centralized storage. Alternatively, in some embodiments, the Surgical Computer 250 is connected directly to the centralized storage via a Network 275 as shown in FIG. 3C.

FIG. 3C illustrates a “cloud-based” implementation in which the Surgical Computer 250 is connected to a Surgical Data Server 280 via a Network 275. This Network 275 may be, for example, a private intranet or the Internet. In addition to the data from the Surgical Computer 250, other sources can transfer relevant data to the Surgical Data Server 280. The example of FIG. 3C shows 3 additional data sources: the Patient 260, Healthcare Professional(s) 265, and an EMR Database 270. Thus, the Patient 260 can send pre-operative and post-operative data to the Surgical Data Server 280, for example, using a mobile app. The Healthcare Professional(s) 265 includes the surgeon and his or her staff as well as any other professionals working with Patient 260 (e.g., a personal physician, a rehabilitation specialist, etc.). It should also be noted that the EMR Database 270 may be used for both pre-operative and post-operative data. For example, assuming that the Patient 260 has given adequate permissions, the Surgical Data Server 280 may collect the EMR of the Patient pre-surgery. Then, the Surgical Data Server 280 may continue to monitor the EMR for any updates post-surgery.

At the Surgical Data Server 280, an Episode of Care Database 285 is used to store the various data collected over a patient's episode of care. The Episode of Care Database 285 may be implemented using any technique known in the art. For example, in some embodiments, a SQL-based database may be used where all of the various data items are structured in a manner that allows them to be readily incorporated in two SQL's collection of rows and columns. However, in other embodiments a No-SQL database may be employed to allow for unstructured data, while providing the ability to rapidly process and respond to queries. As is understood in the art, the term “No-SQL” is used to define a class of data stores that are non-relational in their design. Various types of No-SQL databases may generally be grouped according to their underlying data model. These groupings may include databases that use column-based data models (e.g., Cassandra), document-based data models (e.g., MongoDB), kev-value based data models (e.g., Redis), and/or graph-based data models (e.g., Allego). Any type of No-SQL database may be used to implement the various embodiments described herein and, in some embodiments, the different types of databases may support the Episode of Care Database 285.

Data can be transferred between the various data sources and the Surgical Data Server 280 using any data format and transfer technique known in the art. It should be noted that the architecture shown in FIG. 3C allows transmission from the data source to the Surgical Data Server 280, as well as retrieval of data from the Surgical Data Server 280 by the data sources. For example, as explained in detail below, in some embodiments, the Surgical Computer 250 may use data from past surgeries, machine learning models, etc. to help guide the surgical procedure.

In some embodiments, the Surgical Computer 250 or the Surgical Data Server 280 may execute a de-identification process to ensure that data stored in the Episode of Care Database 285 meets Health Insurance Portability and Accountability Act (HIPAA) standards or other requirements mandated by law. HIPAA provides a list of certain identifiers that must be removed from data during de-identification. The aforementioned de-identification process can scan for these identifiers in data that is transferred to the Episode of Care Database 285 for storage. For example, in one embodiment, the Surgical Computer 250 executes the de-identification process just prior to initiating transfer of a particular data item or set of data items to the Surgical Data Server 280. In some embodiments, a unique identifier is assigned to data from a particular episode of care to allow for re-identification of the data if necessary.

Although FIGS. 3A-3C discuss data collection in the context of a single episode of care, it should be understood that the general concept can be extended to data collection from multiple episodes of care. For example, surgical data may be collected over an entire episode of care each time a surgery is performed with the CASS 200 and stored at the Surgical Computer 250 or at the Surgical Data Server 280. As explained in further detail below, a robust database of episode of care data allows the generation of optimized values, measurements, distances, or other parameters and other recommendations related to the surgical procedure. In some embodiments, the various datasets are indexed in the database or other storage medium in a manner that allows for rapid retrieval of relevant information during the surgical procedure. For example, in one embodiment, a patient-centric set of indices may be used so that data pertaining to a particular patient or a set of patients similar to a particular patient can be readily extracted. This concept can be similarly applied to surgeons, implant characteristics, CASS component versions, etc.

Further details of the management of episode of care data is described in U.S. Patent Application No. 62/783,858 filed Dec. 21, 2018 and entitled “Methods and Systems for Providing an Episode of Care,” the entirety of which is incorporated herein by reference.

Open versus Closed Digital Ecosystems

In some embodiments, the CASS 200 is designed to operate as a self-contained or “closed” digital ecosystem. Each component of the CASS 200 is specifically designed to be used in the closed ecosystem, and data is generally not accessible to devices outside of the digital ecosystem. For example, in some embodiments, each component includes software or firmware that implements proprietary protocols for activities such as communication, storage, security, etc. The concept of a closed digital ecosystem may be desirable for a company that wants to control all components of the CASS 200 to ensure that certain compatibility, security, and reliability standards are met. For example, the CASS 200 can be designed such that a new component cannot be used with the CASS unless it is certified by the company.

In other embodiments, the CASS 200 is designed to operate as an “open” digital ecosystem. In these embodiments, components may be produced by a variety of different companies according to standards for activities, such as communication, storage, and security. Thus, by using these standards, any company can freely build an independent, compliant component of the CASS platform. Data may be transferred between components using publicly available application programming interfaces (APIs) and open, shareable data formats.

To illustrate one type of recommendation that may be performed with the CASS 200, a technique for optimizing surgical parameters is disclosed below. The term “optimization” in this context means selection of parameters that are optimal based on certain specified criteria. In an extreme case, optimization can refer to selecting optimal parameter(s) based on data from the entire episode of care, including any pre-operative data, the state of CASS data at a given point in time, and post-operative goals. Moreover, optimization may be performed using historical data, such as data generated during past surgeries involving, for example, the same surgeon, past patients with physical characteristics similar to the current patient, or the like.

The optimized parameters may depend on the portion of the patient's anatomy to be operated on. For example, for knee surgeries, the surgical parameters may include positioning information for the femoral and tibial component including, without limitation, rotational alignment (e.g., varus/valgus rotation, external rotation, flexion rotation for the femoral component, posterior slope of the tibial component), resection depths (e.g., varus knee, valgus knee), and implant type, size and position. The positioning information may further include surgical parameters for the combined implant, such as overall limb alignment, combined tibiofemoral hyperextension, and combined tibiofemoral resection. Additional examples of parameters that could be optimized for a given TKA femoral implant by the CASS 200 include the following:

Exemplary

Parameter
Reference
Recommendation (s)

Size
Posterior
The largest sized

implant that does

not overhang

medial/lateral bone

edges or overhang the

anterior femur.

A size that does not

result in overstuffing

the patella

femoral joint

Implant Position-
Medial/lateral cortical
Center the implant

Medial Lateral
bone edges
evenly between the

medial/lateral cortical

bone edges

Resection Depth-
Distal and posterior
6 mm of bone

Varus Knee
lateral

Resection Depth-
Distal and posterior
7 mm of bone

Valgus Knee
medial

Rotation-
Mechanical Axis
1° varus

Varus/Valgus

Rotation-External
Transepicondylar
1° external from the

Axis
transepicondylar axis

Rotation-Flexion
Mechanical Axis
3° flexed

Additional examples of parameters that could be optimized for a given TKA tibial implant by the CASS 200 include the following:

Exemplary

Parameter
Reference
Recommendation (s)

Size
Posterior
The lamest sized

implant that does not

overhang the medial,

lateral, anterior, and

posterior tibial edges

Implant Position
Medial/lateral and
Center the implant

anterior/posterior
evenly between the

cortical bone edges
medial/lateral and

anterior/posterior

cortical bone edges

Resection Depth-
Lateral/Medial
4 mm of bone

Varus Knee

Resection Depth-
Lateral/Medial
5 mm of bone

Valgus Knee

Rotation-
Mechanical Axis
1° valgus

Varus/Valgus

Rotation-External
Tibial Anterior
1° external from the

Posterior Axis
tibial anterior paxis

Posterior Slope
Mechanical Axis
3° posterior slope

For hip surgeries, the surgical parameters may comprise femoral neck resection location and angle, cup inclination angle, cup anteversion angle, cup depth, femoral stem design, femoral stem size, fit of the femoral stem within the canal, femoral offset, leg length, and femoral version of the implant.

Shoulder parameters may include, without limitation, humeral resection depth/angle, humeral stem version, humeral offset, glenoid version and inclination, as well as reverse shoulder parameters such as humeral resection depth/angle, humeral stem version, Glenoid tilt/version, glenosphere orientation, glenosphere offset and offset direction.

Various conventional techniques exist for optimizing surgical parameters. However, these techniques are typically computationally intensive and, thus, parameters often need to be determined pre-operatively. As a result, the surgeon is limited in his or her ability to make modifications to optimized parameters based on issues that may arise during surgery. Moreover, conventional optimization techniques typically operate in a “black box” manner with little or no explanation regarding recommended parameter values. Thus, if the surgeon decides to deviate from a recommended parameter value, the surgeon typically does so without a full understanding of the effect of that deviation on the rest of the surgical workflow, or the impact of the deviation on the patient's post-surgery quality of life.

Operative Patient Care System

The general concepts of optimization may be extended to the entire episode of care using an Operative Patient Care System 420 that uses the surgical data, and other data from the Patient 405 and Healthcare Professionals 430 to optimize outcomes and patient satisfaction as depicted in FIG. 4.

Conventionally, pre-operative diagnosis, pre-operative surgical planning, intra-operative execution of a prescribed plan, and post-operative management of total joint arthroplasty are based on individual experience, published literature, and training knowledge bases of surgeons (ultimately, tribal knowledge of individual surgeons and their ‘network’ of peers and journal publications) and their native ability to make accurate intra-operative tactile discernment of “balance” and accurate manual execution of planar resections using guides and visual cues. This existing knowledge base and execution is limited with respect to the outcomes optimization offered to patients needing care. For example, limits exist with respect to accurately diagnosing a patient to the proper, least-invasive prescribed care; aligning dynamic patient, healthcare economic, and surgeon preferences with patient-desired outcomes; executing a surgical plan resulting in proper bone alignment and balance, etc.; and receiving data from disconnected sources having different biases that are difficult to reconcile into a holistic patient framework. Accordingly, a data-driven tool that more accurately models anatomical response and guides the surgical plan can improve the existing approach.

The Operative Patient Care System 420 is designed to utilize patient specific data, surgeon data, healthcare facility data, and historical outcome data to develop an algorithm that suggests or recommends an optimal overall treatment plan for the patient's entire episode of care (preoperative, operative, and postoperative) based on a desired clinical outcome. For example, in one embodiment, the Operative Patient Care System 420 tracks adherence to the suggested or recommended plan, and adapts the plan based on patient/care provider performance. Once the surgical treatment plan is complete, collected data is logged by the Operative Patient Care System 420 in a historical database. This database is accessible for future patients and the development of future treatment plans. In addition to utilizing statistical and mathematical models, simulation tools (e.g., LIFEMOD®) can be used to simulate outcomes, alignment, kinematics, etc. based on a preliminary or proposed surgical plan, and reconfigure the preliminary or proposed plan to achieve desired or optimal results according to a patient's profile or a surgeon's preferences. The Operative Patient Care System 420 ensures that each patient is receiving personalized surgical and rehabilitative care, thereby improving the chance of successful clinical outcomes and lessening the economic burden on the facility associated with near-term revision.

In some embodiments, the Operative Patient Care System 420 employs a data collecting and management method to provide a detailed surgical case plan with distinct steps that are monitored and/or executed using a CASS 200. The performance of the user(s) is calculated at the completion of each step and can be used to suggest changes to the subsequent steps of the case plan. Case plan generation relies on a series of input data that is stored on a local or cloud-storage database. Input data can be related to both the current patient undergoing treatment and historical data from patients who have received similar treatment(s).

A Patient 405 provides inputs such as Current Patient Data 410 and Historical Patient Data 415 to the Operative Patient Care System 420. Various methods generally known in the art may be used to gather such inputs from the Patient 405. For example, in some embodiments, the Patient 405 fills out a paper or digital survey that is parsed by the Operative Patient Care System 420 to extract patient data. In other embodiments, the Operative Patient Care System 420 may extract patient data from existing information sources, such as electronic medical records (EMRs), health history files, and payer/provider historical files. In still other embodiments, the Operative Patient Care System 420 may provide an application program interface (API) that allows the external data source to push data to the Operative Patient Care System. For example, the Patient 405 may have a mobile phone, wearable device, or other mobile device that collects data (e.g., heart rate, pain or discomfort levels, exercise or activity levels, or patient-submitted responses to the patient's adherence with any number of pre-operative plan criteria or conditions) and provides that data to the Operative Patient Care System 420. Similarly, the Patient 405 may have a digital application on his or her mobile or wearable device that enables data to be collected and transmitted to the Operative Patient Care System 420.

Current Patient Data 410 can include, but is not limited to, activity level, preexisting conditions, comorbidities, prehab performance, health and fitness level, pre-operative expectation level (relating to hospital, surgery, and recovery), a Metropolitan Statistical Area (MSA) driven score, genetic background, prior injuries (sports, trauma, etc.), previous joint arthroplasty, previous trauma procedures, previous sports medicine procedures, treatment of the contralateral joint or limb, gait or biomechanical information (back and ankle issues), levels of pain or discomfort, care infrastructure information (payer coverage type, home health care infrastructure level, etc.), and an indication of the expected ideal outcome of the procedure.

Historical Patient Data 415 can include, but is not limited to, activity level, preexisting conditions, comorbidities, prehab performance, health and fitness level, pre-operative expectation level (relating to hospital, surgery, and recovery), a MSA driven score, genetic background, prior injuries (sports, trauma, etc.), previous joint arthroplasty, previous trauma procedures, previous sports medicine procedures, treatment of the contralateral joint or limb, gait or biomechanical information (back and ankle issues), levels or pain or discomfort, care infrastructure information (payer coverage type, home health care infrastructure level, etc.), expected ideal outcome of the procedure, actual outcome of the procedure (patient reported outcomes [PROs], survivorship of implants, pain levels, activity levels, etc.), sizes of implants used, position/orientation/alignment of implants used, soft-tissue balance achieved, etc.

Healthcare Professional(s) 430 conducting the procedure or treatment may provide various types of data 425 to the Operative Patient Care System 420. This Healthcare Professional Data 425 may include, for example, a description of a known or preferred surgical technique (e.g., Cruciate Retaining (CR) vs Posterior Stabilized (PS), up-vs down-sizing, tourniquet vs tourniquet-less, femoral stem style, preferred approach for THA, etc.), the level of training of the Healthcare Professional(s) 430 (e.g., years in practice, fellowship trained, where they trained, whose techniques they emulate), previous success level including historical data (outcomes, patient satisfaction), and the expected ideal outcome with respect to range of motion, days of recovery, and survivorship of the device. The Healthcare Professional Data 425 can be captured, for example, with paper or digital surveys provided to the Healthcare Professional 430, via inputs to a mobile application by the Healthcare Professional, or by extracting relevant data from EMRs. In addition, the CASS 200 may provide data such as profile data (e.g., a Patient Specific Knee Instrument Profile) or historical logs describing use of the CASS during surgery.

Information pertaining to the facility where the procedure or treatment will be conducted may be included in the input data. This data can include, without limitation, the following: Ambulatory Surgery Center (ASC) vs hospital, facility trauma level, Comprehensive Care for Joint Replacement Program (CJR) or bundle candidacy, a MSA driven score, community vs metro, academic vs non-academic, postoperative network access (Skilled Nursing Facility [SNF] only, Home Health, etc.), availability of medical professionals, implant availability, and availability of surgical equipment.

These facility inputs can be captured by, for example and without limitation, Surveys (Paper/Digital), Surgery Scheduling Tools (e.g., apps, Websites, Electronic Medical Records [EMRs], etc.), Databases of Hospital Information (on the Internet), etc. Input data relating to the associated healthcare economy including, but not limited to, the socioeconomic profile of the patient, the expected level of reimbursement the patient will receive, and if the treatment is patient specific may also be captured.

These healthcare economic inputs can be captured by, for example and without limitation, Surveys (Paper/Digital), Direct Payer Information, Databases of Socioeconomic status (on the Internet with zip code), etc. Finally, data derived from simulation of the procedure is captured. Simulation inputs include implant size, position, and orientation. Simulation can be conducted with custom or commercially available anatomical modeling software programs (e.g., LIFEMOD®, AnyBody, or OpenSIM). It is noted that the data inputs described above may not be available for every patient, and the treatment plan will be generated using the data that is available.

Prior to surgery, the Patient Data 410, 415 and Healthcare Professional Data 425 may be captured and stored in a cloud-based or online database (e.g., the Surgical Data Server 280 shown in FIG. 3C). Information relevant to the procedure is supplied to a computing system via wireless data transfer or manually with the use of portable media storage. The computing system is configured to generate a case plan for use with a CASS 200. Case plan generation will be described hereinafter. It is noted that the system has access to historical data from previous patients undergoing treatment, including implant size, placement, and orientation as generated by a computer-assisted, patient-specific knee instrument (PSKI) selection system, or automatically by the CASS 200 itself. To achieve this, case log data is uploaded to the historical database by a surgical sales rep or case engineer using an online portal. In some embodiments, data transfer to the online database is wireless and automated.

Historical data sets from the online database are used as inputs to a machine learning model such as, for example, a recurrent neural network (RNN) or other form of artificial neural network. As is generally understood in the art, an artificial neural network functions similar to a biologic neural network and is comprised of a series of nodes and connections. The machine learning model is trained to predict one or more values based on the input data. For the sections that follow, it is assumed that the machine learning model is trained to generate predictor equations. These predictor equations may be optimized to determine the optimal size, position, and orientation of the implants to achieve the best outcome or satisfaction level.

Once the procedure is complete, all patient data and available outcome data, including the implant size, position and orientation determined by the CASS 200, are collected and stored in the historical database. Any subsequent calculation of the target equation via the RNN will include the data from the previous patient in this manner, allowing for continuous improvement of the system.

In addition to, or as an alternative to determining implant positioning, in some embodiments, the predictor equation and associated optimization can be used to generate the resection planes for use with a PSKI system. When used with a PSKI system, the predictor equation computation and optimization are completed prior to surgery. Patient anatomy is estimated using medical image data (x-ray, CT, MRI). Global optimization of the predictor equation can provide an ideal size and position of the implant components. Boolean intersection of the implant components and patient anatomy is defined as the resection volume. PSKI can be produced to remove the optimized resection envelope. In this embodiment, the surgeon cannot alter the surgical plan intraoperatively.

The surgeon may choose to alter the surgical case plan at any time prior to or during the procedure. If the surgeon elects to deviate from the surgical case plan, the altered size, position, and/or orientation of the component(s) is locked, and the global optimization is refreshed based on the new size, position, and/or orientation of the component(s) (using the techniques previously described) to find the new ideal position of the other component(s) and the corresponding resections needed to be performed to achieve the newly optimized size, position and/or orientation of the component(s). For example, if the surgeon determines that the size, position and/or orientation of the femoral implant in a TKA needs to be updated or modified intraoperatively, the femoral implant position is locked relative to the anatomy, and the new optimal position of the tibia will be calculated (via global optimization) considering the surgeon's changes to the femoral implant size, position and/or orientation. Furthermore, if the surgical system used to implement the case plan is robotically assisted (e.g., as with NAVIO® or the MAKO Rio), bone removal and bone morphology during the surgery can be monitored in real time. If the resections made during the procedure deviate from the surgical plan, the subsequent placement of additional components may be optimized by the processor taking into account the actual resections that have already been made.

FIG. 5A illustrates how the Operative Patient Care System 420 may be adapted for performing case plan matching services. In this example, data is captured relating to the current patient 410 and is compared to all or portions of a historical database of patient data and associated outcomes 415. For example, the surgeon may elect to compare the plan for the current patient against a subset of the historical database. Data in the historical database can be filtered to include, for example, only data sets with favorable outcomes, data sets corresponding to historical surgeries of patients with profiles that are the same or similar to the current patient profile, data sets corresponding to a particular surgeon, data sets corresponding to a particular aspect of the surgical plan (e.g., only surgeries where a particular ligament is retained), or any other criteria selected by the surgeon or medical professional. If, for example, the current patient data matches or is correlated with that of a previous patient who experienced a good outcome, the case plan from the previous patient can be accessed and adapted or adopted for use with the current patient. The predictor equation may be used in conjunction with an intra-operative algorithm that identifies or determines the actions associated with the case plan. Based on the relevant and/or preselected information from the historical database, the intra-operative algorithm determines a series of recommended actions for the surgeon to perform. Each execution of the algorithm produces the next action in the case plan. If the surgeon performs the action, the results are evaluated. The results of the surgeon's performing the action are used to refine and update inputs to the intra-operative algorithm for generating the next step in the case plan Once the case plan has been fully executed all data associated with the case plan, including any deviations performed from the recommended actions by the surgeon, are stored in the database of historical data. In some embodiments, the system utilizes preoperative, intraoperative, or postoperative modules in a piecewise fashion, as opposed to the entire continuum of care. In other words, caregivers can prescribe any permutation or combination of treatment modules including the use of a single module. These concepts are illustrated in FIG. 5B and can be applied to any type of surgery utilizing the CASS 200.

Surgery Process Display

As noted above with respect to FIGS. 2-3C, the various components of the CASS 200 generate detailed data records during surgery. The CASS 200 can track and record various actions and activities of the surgeon during each step of the surgery and compare actual activity to the pre-operative or intraoperative surgical plan. In some embodiments, a software tool may be employed to process this data into a format where the surgery can be effectively “played-back.” For example, in one embodiment, one or more GUIs may be used that depict all of the information presented on the Display 225 during surgery. This can be supplemented with graphs and images that depict the data collected by different tools. For example, a GUI that provides a visual depiction of the knee during tissue resection may provide the measured torque and displacement of the resection equipment adjacent to the visual depiction to better provide an understanding of any deviations that occurred from the planned resection area. The ability to review a playback of the surgical plan or toggle between different aspects of the actual surgery vs, the surgical plan could provide benefits to the surgeon and/or surgical staff, allowing such persons to identify any deficiencies or challenging aspects of a surgery so that they can be modified in future surgeries. Similarly, in academic settings, the aforementioned GUIs can be used as a teaching tool for training future surgeons and/or surgical staff. Additionally, because the data set effectively records many aspects of the surgeon's activity, it may also be used for other reasons (e.g., legal or compliance reasons) as evidence of correct or incorrect performance of a particular surgical procedure.

Over time, as more and more surgical data is collected, a rich library of data may be acquired that describes surgical procedures performed for various types of anatomy (knee, shoulder, hip, etc.) by different surgeons for different patients. Moreover, aspects such as implant type and dimension, patient demographics, etc. can further be used to enhance the overall dataset. Once the dataset has been established, it may be used to train a machine learning model (e.g., RNN) to make predictions of how surgery will proceed based on the current state of the CASS 200.

Training of the machine learning model can be performed as follows. The overall state of the CASS 200 can be sampled over a plurality of time periods for the duration of the surgery. The machine learning model can then be trained to translate a current state at a first time period to a future state at a different time period. By analyzing the entire state of the CASS 200 rather than the individual data items, any causal effects of interactions between different components of the CASS 200 can be captured. In some embodiments, a plurality of machine learning models may be used rather than a single model. In some embodiments, the machine learning model may be trained not only with the state of the CASS 200, but also with patient data (e.g., captured from an EMR) and an identification of members of the surgical staff. This allows the model to make predictions with even greater specificity. Moreover, it allows surgeons to selectively make predictions based only on their own surgical experiences if desired.

In some embodiments, predictions or recommendations made by the aforementioned machine learning models can be directly integrated into the surgical workflow. For example, in some embodiments, the Surgical Computer 250 may execute the machine learning model in the background making predictions or recommendations for upcoming actions or surgical conditions. A plurality of states can thus be predicted or recommended for each period. For example, the Surgical Computer 250 may predict or recommend the state for the next 5 minutes in 30 second increments. Using this information, the surgeon can utilize a “process display” view of the surgery that allows visualization of the future state. For example, FIG. 5C depicts a series of images that may be displayed to the surgeon depicting the implant placement interface. The surgeon can cycle through these images, for example, by entering a particular time into the display 225 of the CASS 200 or instructing the system to advance or rewind the display in a specific time increment using a tactile, oral, or other instruction. In one embodiment, the process display can be presented in the upper portion of the surgeon's field of view in the AR HMD. In some embodiments, the process display can be updated in real-time. For example, as the surgeon moves resection tools around the planned resection area, the process display can be updated so that the surgeon can see how his or her actions are affecting the other aspects of the surgery.

In some embodiments, rather than simply using the current state of the CASS 200 as an input to the machine learning model, the inputs to the model may include a planned future state. For example, the surgeon may indicate that he or she is planning to make a particular bone resection of the knee joint. This indication may be entered manually into the Surgical Computer 250 or the surgeon may verbally provide the indication. The Surgical Computer 250 can then produce a film strip showing the predicted effect of the cut on the surgery. Such a film strip can depict over specific time increments how the surgery will be affected, including, for example, changes in the patient's anatomy, changes to implant position and orientation, and changes regarding surgical intervention and instrumentation, if the contemplated course of action were to be performed. A surgeon or medical professional can invoke or request this type of film strip at any point in the surgery to preview how a contemplated course of action would affect the surgical plan if the contemplated action were to be carried out.

It should be further noted that, with a sufficiently trained machine learning model and robotic CASS, various aspects of the surgery can be automated such that the surgeon only needs to be minimally involved, for example, by only providing approval for various steps of the surgery. For example, robotic control using arms or other means can be gradually integrated into the surgical workflow over time with the surgeon slowly becoming less and less involved with manual interaction versus robot operation. The machine learning model in this case can learn what robotic commands are required to achieve certain states of the CASS-implemented plan. Eventually, the machine learning model may be used to produce a film strip or similar view or display that predicts and can preview the entire surgery from an initial state. For example, an initial state may be defined that includes the patient information, the surgical plan, implant characteristics, and surgeon preferences. Based on this information, the surgeon could preview an entire surgery to confirm that the CASS-recommended plan meets the surgeon's expectations and/or requirements. Moreover, because the output of the machine learning model is the state of the CASS 200 itself, commands can be derived to control the components of the CASS to achieve each predicted state. In the extreme case, the entire surgery could thus be automated based on just the initial state information.

Using the Point Probe to Acquire High-Resolution of Key Areas During Hip Surgeries

Use of the point probe is described in U.S. patent application Ser. No. 14/955,742 entitled “Systems and Methods for Planning and Performing Image Free Implant Revision Surgery,” the entirety of which is incorporated herein by reference. Briefly, an optically tracked point probe may be used to map the actual surface of the target bone that needs a new implant. Mapping is performed after removal of the defective or worn-out implant, as well as after removal of any diseased or otherwise unwanted bone. A plurality of points is collected on the bone surfaces by brushing or scraping the entirety of the remaining bone with the tip of the point probe. This is referred to as tracing or “painting” the bone. The collected points are used to create a three-dimensional model or surface map of the bone surfaces in the computerized planning system. The created 3D model of the remaining bone is then used as the basis for planning the procedure and necessary implant sizes. An alternative technique that uses X-rays to determine a 3D model is described in U.S. Provisional Patent Application No. 62/658,988, filed Apr. 17, 2018 and entitled “Three Dimensional Guide with Selective Bone Matching,” the entirety of which is incorporated herein by reference.

For hip applications, the point probe painting can be used to acquire high resolution data in key areas such as the acetabular rim and acetabular fossa. This can allow a surgeon to obtain a detailed view before beginning to ream. For example, in one embodiment, the point probe may be used to identify the floor (fossa) of the acetabulum. As is well understood in the art, in hip surgeries, it is important to ensure that the floor of the acetabulum is not compromised during reaming so as to avoid destruction of the medial wall. If the medial wall were inadvertently destroyed, the surgery would require the additional step of bone grafting. With this in mind, the information from the point probe can be used to provide operating guidelines to the acetabular reamer during surgical procedures. For example, the acetabular reamer may be configured to provide haptic feedback to the surgeon when he or she reaches the floor or otherwise deviates from the surgical plan. Alternatively, the CASS 200 may automatically stop the reamer when the floor is reached or when the reamer is within a threshold distance.

As an additional safeguard, the thickness of the area between the acetabulum and the medial wall could be estimated. For example, once the acetabular rim and acetabular fossa has been painted and registered to the pre-operative 3D model, the thickness can readily be estimated by comparing the location of the surface of the acetabulum to the location of the medial wall. Using this knowledge, the CASS 200 may provide alerts or other responses in the event that any surgical activity is predicted to protrude through the acetabular wall while reaming.

The point probe may also be used to collect high resolution data of common reference points used in orienting the 3D model to the patient. For example, for pelvic plane landmarks like the ASIS and the pubic symphysis, the surgeon may use the point probe to paint the bone to represent a true pelvic plane. Given a more complete view of these landmarks, the registration software has more information to orient the 3D model.

The point probe may also be used to collect high-resolution data describing the proximal femoral reference point that could be used to increase the accuracy of implant placement. For example, the relationship between the tip of the Greater Trochanter (GT) and the center of the femoral head is commonly used as reference point to align the femoral component during hip arthroplasty. The alignment is highly dependent on proper location of the GT; thus, in some embodiments, the point probe is used to paint the GT to provide a high resolution view of the area. Similarly, in some embodiments, it may be useful to have a high-resolution view of the Lesser Trochanter (LT). For example, during hip arthroplasty, the Dorr Classification helps to select a stem that will maximize the ability of achieving a press-fit during surgery to prevent micromotion of femoral components post-surgery and ensure optimal bony ingrowth. As is generated understood in the art, the Dorr Classification measures the ratio between the canal width at the LT and the canal width 10 cm below the LT. The accuracy of the classification is highly dependent on the correct location of the relevant anatomy. Thus, it may be advantageous to paint the LT to provide a high-resolution view of the area.

In some embodiments, the point probe is used to paint the femoral neck to provide high-resolution data that allows the surgeon to better understand where to make the neck cut. The navigation system can then guide the surgeon as they perform the neck cut. For example, as understood in the art, the femoral neck angle is measured by placing one line down the center of the femoral shaft and a second line down the center of the femoral neck. Thus, a high-resolution view of the femoral neck (and possibly the femoral shaft as well) would provide a more accurate calculation of the femoral neck angle.

High-resolution femoral head neck data could also be used for a navigated resurfacing procedure where the software/hardware aids the surgeon in preparing the proximal femur and placing the femoral component. As is generally understood in the art, during hip resurfacing, the femoral head and neck are not removed; rather, the head is trimmed and capped with a smooth metal covering. In this case, it would be advantageous for the surgeon to paint the femoral head and cap so that an accurate assessment of their respective geometries can be understood and used to guide trimming and placement of the femoral component.

Registration of Pre-Operative Data to Patient Anatomy Using the Point Probe

As noted above, in some embodiments, a 3D model is developed during the pre-operative stage based on 2D or 3D images of the anatomical area of interest. In such embodiments, registration between the 3D model and the surgical site is performed prior to the surgical procedure. The registered 3D model may be used to track and measure the patient's anatomy and surgical tools intraoperatively.

During the surgical procedure, landmarks are acquired to facilitate registration of this pre-operative 3D model to the patient's anatomy. For knee procedures, these points could comprise the femoral head center, distal femoral axis point, medial and lateral epicondyles, medial and lateral malleolus, proximal tibial mechanical axis point, and tibial A/P direction. For hip procedures these points could comprise the anterior superior iliac spine (ASIS), the pubic symphysis, points along the acetabular rim and within the hemisphere, the greater trochanter (GT), and the lesser trochanter (LT).

In a revision surgery, the surgeon may paint certain areas that contain anatomical defects to allow for better visualization and navigation of implant insertion. These defects can be identified based on analysis of the pre-operative images. For example, in one embodiment, each pre-operative image is compared to a library of images showing “healthy” anatomy (i.e., without defects). Any significant deviations between the patient's images and the healthy images can be flagged as a potential defect. Then, during surgery, the surgeon can be warned of the possible defect via a visual alert on the display 225 of the CASS 200. The surgeon can then paint the area to provide further detail regarding the potential defect to the Surgical Computer 250.

In some embodiments, the surgeon may use a non-contact method for registration of bony anatomy intra-incision. For example, in one embodiment, laser scanning is employed for registration. A laser stripe is projected over the anatomical area of interest and the height variations of the area are detected as changes in the line. Other non-contact optical methods, such as white light inferometry or ultrasound, may alternatively be used for surface height measurement or to register the anatomy. For example, ultrasound technology may be beneficial where there is soft tissue between the registration point and the bone being registered (e.g., ASIS, pubic symphysis in hip surgeries), thereby providing for a more accurate definition of anatomic planes.

This disclosure describes example systems and methods of implementing a navigation system to facilitate ligament graft placement in an operative joint. The disclosed systems and methods advantageously enable enhanced planning capabilities that allow a surgeon to make more informed operative decisions, which can lead to better outcomes, less variability, and improved confidence. In addition, the use of surgical robotics may allow for a precise implementation of a pre-defined plan that would be difficult to replicate with non-robotic techniques. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of example embodiments. It will be evident to one skilled in the art, however, that embodiments can be practiced without these specific details.

The surgical navigation system employed in certain embodiments of the present disclosure can track a patient's operative bones throughout a full range of motion. In addition, the surgical navigation system can track a drilling device and align and/or guide the drilling device in cutting the bones to receive implants in a manner consistent with a surgical plan. More specifically, the surgical navigation system not only can be configured to assist the surgeon in planning and performing a surgical procedure such as an ACL reconstruction, but also can be configured to verify that the implants are installed in a manner consistent with the plan.

In certain embodiments, the surgical navigation system can be used in the planning stages of the surgery. Where it is desirable to maintain the same laxity in the joint post-operatively as existed prior to the surgery, the surgeon may employ imageless registration of the involved bones by touching sufficient points on the bones with a tracked probe to register them in the system so they can be tracked. In certain embodiments, the surgeon may stress the joint and track its relative location throughout a full range of motion to determine the pre-operative laxity profile that becomes a goal for the post-operative condition.

Developments in robotically enhanced surgical systems allow for extreme precision during bone removal and subsequent placement of implant components. Additionally, these systems provide surgical planning tools that visualize implant position and aid in properly balancing the joint. The NAVIO@ surgical navigation system, for example, provides imageless and intraoperative surgical planning by mapping the patient's joint with an instrumented probe. Once the bony anatomy is defined, the surgeon virtually manipulates an implant to a desired position and orientation prior to removing tissue. NAVIO is a registered trademark of BLUE BELT TECHNOLOGIES, INC. of Pittsburgh, Pa., now a subsidiary of SMITH & NEPHEW, INC. of Memphis, Tenn.

Using the NAVIO@ surgical navigation system, a surgeon can “paint” the surface of a bone, such as the condyles, epicondyles, and patellar surface of a femur, using a probe in order to generate an approximation of the patient's anatomy in three dimensions. Approximations of other anatomical surfaces, such as the tibia, the humerus, the acetabular socket, or the like, can be similarly generated depending upon the surgical procedure being performed.

In an alternate embodiment, an image-based surgical system may be used. For example, a surgical system may construct a digital representation of a portion of a patient's anatomy from actual scans of the target patient, such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), or ultrasound scanning of the joint and surrounding structure. The images may be intraoperatively registered to the patient's anatomy using, for example, fiducial markers and a pointer probe.

Furthermore, the NAVIO@ surgical navigation system detects fiducial markers using passive infrared tracking technology. However, one of ordinary skill in the art will be aware that alternate means of tracking the location of portions of a patient's anatomy are possible, including, without limitation, active infrared tracking, electromagnetic tracking, inertial tracking, video-based tracking, such as with QR codes, depth camera tracking, and ultrasound tracking.

As described further herein, methods and systems for planning and performing ligament reconstruction surgery are disclosed. Portions of a patient's anatomy can be recognized by a robotic surgical system during a ligament reconstruction surgery. The location and trajectory of a tunnel that receives a ligament graft can be determined by the robotic system to assist a surgeon in performing the ligament reconstruction surgery. In addition, a robotic surgical system can be used to more precisely bore the tunnel for the ligament reconstruction surgery as is described further below. Additionally or alternatively, the methods and systems disclosed herein may be utilized to plan a meniscal root repair procedure and to bore the tunnel for the procedure.

FIG. 6 is a block diagram depicting a system 600 for providing navigation and control to a surgical tool 630 according to an embodiment. For example, the system 600 can include a control system 610, a tracking system 620, and a surgical tool 630. In some embodiments, the system 600 may further include a display device 640 and a database 650. In an example, these components can be combined to provide navigation and control of the surgical tool 630 during an orthopedic (or similar) prosthetic implant surgery or a ligament reconstruction surgery.

The control system 610 can include one or more computing devices configured to coordinate information received from the tracking system 620 and provide control to the surgical tool 630. In an example, the control system 610 can include a planning module 612, a navigation module 614, a control module 616, and a communication interface 618. The planning module 612 can provide pre-operative planning services that enable clinicians to plan a procedure virtually prior to entering the operating room.

In an example, such as an ACL reconstruction, the planning module 612 can be used to manipulate a virtual model of the implant in reference to a virtual implant host model. The implant host model can be constructed from actual scans of the target patient, such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomographic (PET), or ultrasound scanning of the joint and surrounding structure. Alternatively, pre-operative planning can be performed by selecting a predefined implant host model from a group of models based on patient measurements or other clinician-selected inputs. In certain examples, pre-operative planning is refined intra-operatively by measuring the patient's (target implant host's) actual anatomy. In an example, a point probe tracked by the tracking system 620 can be used to measure the target implant host's actual anatomy.

In an example, the navigation module 614 can coordinate tracking the location and orientation of the implant, such as a ligament grafi, the implant host, and the surgical tool 630. In certain examples, the navigation module 614 can also coordinate tracking of the virtual models used during pre-operative planning within the planning module 612. Tracking the virtual models can include operations such as alignment of the virtual models with the implant host through data obtained via the tracking system 620. In these examples, the navigation module 614 receives input from the tracking system 620 regarding the physical location and orientation of the surgical tool 630 and an implant host. Tracking of the implant host can include tracking multiple individual bone structures. For example, the tracking system 620 can individually track the femur and the tibia using tracking devices anchored to the individual bones.

In an example, the control module 616 can process information provided by the navigation module 614 to generate control signals for controlling the surgical tool 630. In certain examples, the control module 616 can also work with the navigation module 614 to produce visual animations to assist the surgeon during an operative procedure. Visual animations can be displayed via a display device, such as display device 640. In an example, the visual animations can include real-time 3-D representations of the implant, the implant host, and the surgical tool 630, among other things. In certain examples, the visual animations are color-coded to further assist the surgeon with positioning and orientation of the implant.

In an example, the communication interface 618 facilitates communication between the control system 610 and external systems and devices. The communication interface 618 can include both wired and wireless communication interfaces, such as Ethernet. IEEE 802.11 wireless, or Bluetooth, among others. As illustrated in FIG. 6, in this example, the primary external systems connected via the communication interface 618 include the tracking system 620 and the surgical tool 630. Although not shown, the database 650 and the display device 640, among other devices, can also be connected to the control system 610 via the communication interface 618. In an example, the communication interface 618 communicates over an internal bus to other modules and hardware systems within the control system 610.

In an example, the tracking system 620 provides location and orientation information for surgical devices and parts of an implant host's anatomy to assist in navigation and control of semi-active robotic surgical devices. The tracking system 620 can include a tracker that includes or otherwise provides tracking data based on at least three positions and at least three angles. The tracker can include one or more first tracking markers associated with the implant host and one or more second markers associated with the surgical device (e.g., surgical tool 630). The markers or some of the markers can be one or more of infrared sources, Radio Frequency (RF) sources, ultrasound sources, electromagnetic sources, and/or transmitters. The tracking system 620 can thus be, without limitation, an infrared tracking system, an optical tracking system, an ultrasound tracking system, an electromagnetic tracking system, an inertial tracking system, a wired system, and/or a RF tracking system. One illustrative tracking system is the OPTOTRAK® 3-D motion and position measurement and tracking system, although those of ordinary skill in the art will recognize that other tracking systems of other accuracies and/or resolutions can be used. OPTOTRAK is a registered trademark of NORTHERN DIGITAL INC. of Waterloo, Ontario, Canada.

FIG. 7 is a diagram illustrating an environment for operating a system 700 for navigation and control of a surgical tool (e.g., surgical tool 630 as described in regard to FIG. 6) during a surgical procedure according to an embodiment. In an example, the system 700 can include components similar to those discussed above in reference to system 600. For example, the system 700 can include a control system 610, a tracking system 620, and one or more display devices, such as display devices 640A and 640B. The system 700 also illustrates an implant host 601, tracking markers 660, 662, and 664, and a foot control 670.

In an example, the tracking markers 660, 662, and 664 can be used by the tracking system 620 to track the location and orientation of the implant host 601, one or more surgical tools (including, for example, similar tracking markers), and a reference, such as an operating table (tracking marker 664). In this example, the tracking system 620 uses optical tracking to monitor the location and orientation of tracking markers 660, 662, and 664. Each of the tracking markers 660, 662, and 664 includes three or more tracking spheres that provide easily processed targets to determine location and orientation in up to six degrees of freedom. The tracking system 620 can be calibrated to provide a localized 3-D coordinate system within which the implant host 601 and one or more surgical tools can be spatially tracked. For example, as long as the tracking system 620 can image three of the tracking spheres on a tracking marker, such as tracking marker 660, the tracking system 620 can utilize image processing algorithms to generate points within the 3-D coordinate system. Subsequently, the tracking system 620 (or the navigation module 614 (FIG. 6) within the control system 610) can use the three points to triangulate an accurate 3-D position and orientation associated with the item to which the tracking marker is affixed, such as the implant host 601 or a surgical tool. Once the precise location and orientation of a surgical tool is known, the system 700 can use the known properties of the surgical tool to accurately calculate a position and orientation of the surgical tool relative to the implant host 601.

FIG. 8 depicts an illustrative flow diagram of an exemplary method of performing a surgical procedure according to an embodiment. As shown in FIG. 8, tracking instrumentation may be affixed 805 to a patient. The tracking instrumentation may enable tracking of a portion of a patient's body, such as a joint on which a surgical procedure is to be performed.

A kinematic assessment may be performed 810. The kinematic assessment may include testing one or more of a passive range of motion and a stressed range of motion for a joint on which the surgical procedure is to be performed.

In an embodiment, a plurality of landmarks on the patient's anatomy may be located using a point probe and a tracking system, such as the NAVIO@ surgical navigation system described above. The tracking system may track one or more tracking arrays that are positioned on the patient. In some cases, the tracking arrays may be affixed to one or more bones of the patient. For example, if an ACL reconstruction is to be performed, the one or more tracking arrays may be positioned on one or more bones of the patient's leg. The mechanical axis of the tibia may be defined by capturing a location of the malleoli, which defines the ankle center, and the center of the knee on the tibia using a point probe. In an embodiment, a mechanical axis of the patient's femur may be defined by rotating the patient's hip joint to identify the hip center and using the point probe to record the center of the knee on the femur.

The patient's limb may be extended, and a neutral position for the patient's joint may be recorded based on the positions of the tracking arrays. A passive range of motion may be captured by flexing and extending the joint through a range of motion. Additionally, the joint may be rotated in order to capture additional range of motion information. Similarly, a load may be applied to a portion of the joint (e.g., a tensile load on the ACL) in order to determine a stressed range of motion measurement for the joint. The stressed range of motion may be assessed by flexing, extending, and/or rotating the joint through a similar range of motion as for the passive range of motion. Additional and/or alternate operations may be performed and additional and/or alternate measurements may be taken within the scope of this disclosure. In some embodiments, for example, a passive and/or stressed range of motion may be similarly assessed on the patient's non-operated joint by flexing, extending, and/or rotating the joint through a range of motion. The range of motion may be quantified and recorded by various methods, including but not limited to capturing the position of affixed tracking arrays utilizing a tracking system, capturing the motion of the limb utilizing an ultrasound system or other imaging modality, and observing gait and performing gait analysis in a pre-operative setting.

In some embodiments, software programs may be used to simulate in vivo functional activities (e.g., LifeModeler, which is a software package written and distributed by LIFEMODELER. INC. of San Clemente, Calif., now a subsidiary of SMITH & NEPHEW, INC.). Such software programs have been used to assess kinematics using a three-dimensional, dynamics-oriented, physics-based modeling methodology. Such programs may receive pre-operative images, such as magnetic resonance imaging (MRI) images, computed tomography (CT) scans, or the like, and use such images to determine the operation of the joint in advance of a surgical procedure. For example, the model can include a standard three-dimensional (3D) model representing a virtual knee created based upon various information contained within the preoperative inputs. In certain implementations, the model can be simulated to perform various movements under similar load regimes and movement/bending cycles. The results of the simulation can then be analyzed to determine various relationships between one or more input factors and various responses. In some cases, the information may be supplemented with intraoperative information, such as tracking information from a surgical navigation system, to supplement the kinematic assessment of the operative joint.

Referring back to FIG. 8, at least a portion of the patient's anatomy may be registered 815 with the surgical navigation system to facilitate further planning and bone removal. In an embodiment, a footprint for the native ACL (or a portion of a bony surface of the patient at which the femoral tunnel is planned to be initiated) may be “painted” using the point probe. The painting process includes moving the tip of the point probe across the surface of a portion of interest of the bone. As the point probe is in contact with the bony surface, the surgical navigation system detects a tracking array associated with the point probe and determines the location of the tip in reference to the tracking array. In this manner, the surgical navigation system (or a processor associated therewith) may determine the location of the bony surface in three-dimensional space.

In some embodiments, the locations of other areas of the femur may also be determined, such as a portion of the lateral metaphyseal bone in an area at which the ACL graft will exit. In some embodiments, further location information pertaining to the tibia may be identified, such as the native ligament footprint, the planned entry point or exit point of the tunnel in the tibia, and/or the posterior metaphysis where the graft will be inserted. Defining these locations may provide reference information for planning a ligament graft tunnel. In some embodiments, further definition of the bony anatomy may be accomplished by collecting position information pertaining to additional surfaces.

In some embodiments, the registration of the surface areas of the patient's anatomy may be used to generate a three-dimensional model of the underlying structure of the joint. For example, the surgical navigation system and/or a processor may use the surface information in conjunction with an atlas of knee models to determine a three-dimensional model that approximates the structure of the patient's knee.

In an embodiment, the three dimensional model may be used to determine 820 an initial position and trajectory of the tunnel for the ligament graft. This determination 820 may be made based on the three-dimensional model, the kinematic assessment, and historical information regarding the desired position of the tunnel for a ligament graft.

In some embodiments, the determination 820 may use musculoskeletal simulation information, such as information output from the LifeModeler software package, to inform the optimal position, trajectory, and depth of the tunnel. In some embodiments, one or more properties of the ligament graft may be estimated. For example, the one or more properties may include, without limitation, a cross-sectional area, a cross-sectional geometry, an elasticity, a length, a number of bundles in the graft, or the like. For example, the graft may include anteromedial and posterolateral bundles. Additionally or alternatively, a reconstruction procedure may include ACL reconstruction as well as anterolateral ligament (ALL) reconstruction. By estimating the one or more properties and placing a virtual representation of the ligament graft, a dynamic simulation can be conducted that is driven or trained using information from the joint kinematics assessment.

In an embodiment, a number of factors may be considered by the joint simulation. For example, the position, trajectory and depth of the tunnel may be optimized in order to minimize the amount of strain experienced by an engrafted ligament. Furthermore, the simulation may minimize the amount of contact and/or stress applied to the entrance of the tunnel by the ligament graft throughout the range of motion in order to prevent tunnel widening. In addition, an ideal graft tension that is required to restore a desired knee laxity may be determined and reported to a surgeon. Still further, stress relaxation properties of the graft may be estimated based on an empiric or simulated assessment of the graft material. The determination of stress relaxation properties may result in direction to the surgeon to over-stress the ligament graft during the surgical procedure in order to compensate for changes in the behavior of the ligament that are likely to occur over time. Additional and/or alternate factors may also be considered within the scope of this disclosure.

In some embodiments, an initial position, trajectory, and depth for the tunnel may be suggested based on the results of past procedures conducted using the same or related systems. In some embodiments, the proposed planning system may record information pertaining to a patient's anatomy, a patient's kinematics, and a tunnel position and trajectory for every patient for which a surgical procedure is performed. In some embodiments, information may be shared between similar systems, such as by uploading the information described above or similar information to a remote or centralized data repository. In this manner, information regarding the tunnel position and trajectory and patient outcomes for a larger pool of past ligament reconstructions may be considered when performing a simulation for a present ligament reconstruction. Past simulation information may be distilled using machine learning techniques to determine a tunnel position, trajectory, and depth for the present ligament reconstruction procedure. The determined tunnel position, trajectory, and depth may be most advantageous for the patient as determined based on positive outcomes for other patients having similar anatomy and kinematics. The machine learning models may be trained to relate procedural metrics to outcomes data and may indicate which tunnel position and trajectory will most likely be successful for a particular patient.

In some embodiments, additional parameters for the tunnel for the ligament graft may be determined by the proposed planning system during the determination 820, based on the three-dimensional model, the kinematic assessment, and historical information regarding the desired position of the tunnel for a ligament graft. Non-limiting examples of such additional parameters for the tunnel include the size of the graft tunnel, shape of the graft tunnel, orientation of the graft tunnel, and method of fixation of the graft therethrough.

In some embodiments, the path for the tunnel may be displayed on a display screen that is visible to a surgeon performing or intending to perform the surgical procedure. An exemplary display for use in planning the tunnel is depicted in FIG. 9. Augmented reality headsets are a further example of the types of displays that are contemplated herein. In some embodiments, the proposed planning system may output a plurality of possible paths for the tunnel, each including a tunnel position, trajectory and depth. Each of the plurality of the possible paths for the tunnel may optimize one or more different parameters of the surgical tunnel. Based on the order of priority of the various parameters as determined by the surgeon, the plurality of possible paths for the tunnel may be displayed on the display screen in the order of priority such that the surgeon may select a preferred path for the tunnel.

In some embodiments, the tunnel may include multiple segments, such as a first segment through a first bone and a second segment through a second bone. For example, in the case of an ACL graft, two tunnel segments may be placed through the femur and the tibia, respectively. Each of the tunnel segments may have a different trajectory depending upon the angle of flexion of the knee, such as is shown in FIG. 9.

The initial position and trajectory of the tunnel may be intraoperatively modifiable by a surgeon in, for example, six degrees of freedom. In some embodiments, modifications to the position and trajectory of the tunnel may be made using a touch screen, although other methods known to those of ordinary skill in the art are also considered to be within the scope of this disclosure.

In some embodiments, the anisometry of the tunnel's trajectory may be assessed based at least in part upon a distance between the lateral femoral tunnel exit point (point A in FIG. 9) and a posterior tibia tunnel entrance point (Point B in FIG. 9). This distance may be determined for a plurality of degrees of flexion or extension based on the stressed range of motion calculation from the kinematic assessment. In some embodiments, the tunnel position and trajectory may be modified to reduce the amount of anisometry. In addition, because the length of the ligament graft and the expected kinematics of the stressed joint are known, any potential graft impingement risk may be identified during the determination of the placement and trajectory of the tunnel. The optimized parameters of the tunnel for the ligament graft may reduce or minimize graft impingement as well as anisometry of the tunnel.

Referring back to FIG. 8, once the position and trajectory of the tunnel are determined, one or more tunnel segments can be formed 825 using a surgical tool that is tracked by the surgical navigation system. In an embodiment, the surgical tool, such as a NAVIO® handpiece, may include an attachable tracking array that is detectable and trackable by the surgical navigation system. The surgical tool may include a cutting element, such as a rotatable burr, that can be used to remove bone to form the tunnel for the ligament graft. The tracking array for the surgical tool may be positioned such that the location of the cutting element is known with respect to the position of the tracking array.

In some embodiments, the surgical tool may be activated when the cutting element of the surgical tool is determined to be at a particular location and/or orientation corresponding to a portion of the tunnel. In some embodiments, characteristics of the cutting element may be controlled based on the position of the cutting element with respect to the anticipated location of the tunnel. For example, as the surgical tool is tracked relative to the patient's anatomy, the cutting element may be engaged only when the surgical tool is aligned with the planned tunnel trajectory. In some embodiments, the cutting element may be extended from a sheath when the surgical tool is aligned with the planned tunnel trajectory. Control signals may be sent from a control unit to the surgical tool in order to engage the surgical tool in such embodiments. Other methods of engaging the cutting tool may also be performed based upon the proximity of the cutting element to the planned tunnel trajectory within the scope of this disclosure.

In some embodiments, more than one tunnel segment may be formed 825. For example, a first tunnel segment may be formed 825 in the femur from a posterior side of the knee joint, and a second tunnel segment may be formed in the tibia from an anterior side of the knee joint. After the tunnel or tunnel segments have been created, a surgeon can place, tension, and fix the ligament graft using conventional surgical techniques.

In some embodiments, a stability assessment may be performed 830 after the ligament graft is placed in the tunnel. Performing the stability assessment may include performing one or more of a plurality of protocols. For example, the protocols may include one or more of the Drawer test, the Lachman test, and the Pivot Shift test. The manner in which such protocols and/or other stability assessment tests are performed will be apparent to those of ordinary skill in the art.

In some embodiments, a measurement of joint laxity (e.g. varus/valgus laxity) may also be assessed relative to an expected value or to a pre-operative measurement of the same joint. In some embodiments, the joint laxity for the joint upon which the surgical procedure was performed may be compared with a joint laxity for the corresponding non-operated joint. In some other embodiments, the joint laxity for the joint upon which the surgical procedure was performed may be compared with joint laxity data from past procedures in a remote or centralized data repository, including healthy, non-operated joints and/or successfully repaired joints. In some embodiments, the graft tension can be modified intraoperatively to achieve a desired level of stability.

In some embodiments, a robotically controlled surgical tool may not be used. One of ordinary skill in the art will recognize that the tunnel formation procedure could be performed using conventional navigation systems that do not include robotically controlled tools. Such systems may include a tracked surgical drill.

In some embodiments, the above-listed procedure could be adapted to be performed by a different robotically controlled system. For example, a robotic system may include a system in which a bone removal device is positioned via a robotically controlled arm. In some embodiments, the robotically controlled arm may include haptic feedback for positioning of the surgical tool.

FIG. 10 illustrates a block diagram of an illustrative data processing system 1000 in which aspects of the illustrative embodiments are implemented. The data processing system 1000 is an example of a computer, such as a server or client, in which computer usable code or instructions implementing the process for illustrative embodiments of the present invention are located. In some embodiments, the data processing system 1000 may be a server computing device. For example, data processing system 1000 can be implemented in a server or another similar computing device operably connected to surgical system 700 as described above. The data processing system 1000 can be configured to, for example, transmit and receive information related to a patient and/or a related surgical plan with the surgical system 700.

In the depicted example, data processing system 1000 can employ a hub architecture including a north bridge and memory controller hub (NB/MCH) 1001 and south bridge and input/output (I/O) controller hub (SB/ICH) 1002. Processing unit 1003, main memory 1004, and graphics processor 1005 can be connected to the NB/MCH 1001. Graphics processor 1005 can be connected to the NB/MCH 1001 through, for example, an accelerated graphics port (AGP).

In the depicted example, a network adapter 1006 connects to the SB/ICH 1002. An audio adapter 1007, keyboard and mouse adapter 1008, modem 1009, read only memory (ROM) 1010, hard disk drive (HDD) 1011, optical drive (e.g., CD or DVD) 1012, universal serial bus (USB) ports and other communication ports 1013, and PCI/PCIe devices 1014 may connect to the SB/ICH 1002 through bus system 1016. PCI/PCIe devices 1014 may include Ethernet adapters, add-in cards, and PC cards for notebook computers. ROM 1010 may be, for example, a flash basic input/output system (BIOS). The HDD 1011 and optical drive 1012 can use an integrated drive electronics (IDE) or serial advanced technology attachment (SATA) interface. A super I/O (SIO) device 1015 can be connected to the SB/ICH 1002.

An operating system can run on the processing unit 1003. The operating system can coordinate and provide control of various components within the data processing system 1000. As a client, the operating system can be a commercially available operating system. An object-oriented programming system, such as the Java™ programming system, may run in conjunction with the operating system and provide calls to the operating system from the object-oriented programs or applications executing on the data processing system 1000. As a server, the data processing system 1000 can be an IBM® eServer™ System p® running the Advanced Interactive Executive operating system or the Linux operating system. The data processing system 1000 can be a symmetric multiprocessor (SMP) system that can include a plurality of processors in the processing unit 1003. Alternatively, a single processor system may be employed.

Instructions for the operating system, the object-oriented programming system, and applications or programs are located on storage devices, such as the HDD 1011, and are loaded into the main memory 1004 for execution by the processing unit 1003. The processes for embodiments described herein can be performed by the processing unit 1003 using computer usable program code, which can be located in a memory such as, for example, main memory 1004, ROM 1010, or in one or more peripheral devices.

A bus system 1016 can be comprised of one or more busses. The bus system 1016 can be implemented using any type of communication fabric or architecture that can provide for a transfer of data between different components or devices attached to the fabric or architecture. A communication unit such as the modem 1009 or the network adapter 1006 can include one or more devices that can be used to transmit and receive data.

Those of ordinary skill in the art will appreciate that the hardware depicted in FIG. 10 may vary depending on the implementation. Other internal hardware or peripheral devices, such as flash memory, equivalent non-volatile memory, or optical disk drives may be used in addition to or in place of the hardware depicted. Moreover, the data processing system 1000 can take the form of any of a number of different data processing systems, including but not limited to, client computing devices, server computing devices, tablet computers, laptop computers, telephone or other communication devices, personal digital assistants, and the like. Essentially, data processing system 1000 can be any known or later developed data processing system without architectural limitation.

While various illustrative embodiments incorporating the principles of the present teachings have been disclosed, the present teachings are not limited to the disclosed embodiments. Instead, this application is intended to cover any variations, uses, or adaptations of the present teachings and use its general principles. Further, this application is intended to cover such departures from the present disclosure as come within known or customary practice in the art to which these teachings pertain.

In the above detailed description, reference is made to the accompanying drawings, which form a part hereof. In the drawings, similar symbols typically identify similar components, unless context dictates otherwise. The illustrative embodiments described in the present disclosure are not meant to be limiting. Other embodiments may be used, and other changes may be made, without departing from the spirit or scope of the subject matter presented herein. It will be readily understood that various features of the present disclosure, as generally described herein, and illustrated in the Figures, can be arranged, substituted, combined, separated, and designed in a wide variety of different configurations, all of which are explicitly contemplated herein.

The present disclosure is not to be limited in terms of the particular embodiments described in this application, which are intended as illustrations of various features. Many modifications and variations can be made without departing from its spirit and scope, as will be apparent to those skilled in the art. Functionally equivalent methods and apparatuses within the scope of the disclosure, in addition to those enumerated herein, will be apparent to those skilled in the art from the foregoing descriptions. It is to be understood that this disclosure is not limited to particular methods, reagents, compounds, compositions or biological systems, which can, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting.

With respect to the use of substantially any plural and/or singular terms herein, those having skill in the art can translate from the plural to the singular and/or from the singular to the plural as is appropriate to the context and/or application. The various singular/plural permutations may be expressly set forth herein for sake of clarity.

It will be understood by those within the art that, in general, terms used herein are generally intended as “open” terms (for example, the term “including” should be interpreted as “including but not limited to,” the term “having” should be interpreted as “having at least,” the term “includes” should be interpreted as “includes but is not limited to,” et cetera). While various compositions, methods, and devices are described in terms of “comprising” vanous components or steps (interpreted as meaning “including, but not limited to”), the compositions, methods, and devices can also “consist essentially of” or “consist of” the various components and steps, and such terminology should be interpreted as defining essentially closed-member groups.

In addition, even if a specific number is explicitly recited, those skilled in the art will recognize that such recitation should be interpreted to mean at least the recited number (for example, the bare recitation of “two recitations,” without other modifiers, means at least two recitations, or two or more recitations). Furthermore, in those instances where a convention analogous to “at least one of A, B, and C, et cetera” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (for example, “a system having at least one of A, B, and C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, et cetera). In those instances where a convention analogous to “at least one of A, B, or C, et cetera” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (for example, “a system having at least one of A, B, or C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, et cetera). It will be further understood by those within the art that virtually any disjunctive word and/or phrase presenting two or more alternative terms, whether in the description, sample embodiments, or drawings, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms. For example, the phrase “A or B” will be understood to include the possibilities of “A” or “B” or “A and B.”

In addition, where features of the disclosure are described in terms of Markush groups, those skilled in the art will recognize that the disclosure is also thereby described in terms of any individual member or subgroup of members of the Markush group.

As will be understood by one skilled in the art, for any and all purposes, such as in terms of providing a written description, all ranges disclosed herein also encompass any and all possible subranges and combinations of subranges thereof. Any listed range can be easily recognized as sufficiently describing and enabling the same range being broken down into at least equal halves, thirds, quarters, fifths, tenths, et cetera. As a non-limiting example, each range discussed herein can be readily broken down into a lower third, middle third and upper third, et cetera. As will also be understood by one skilled in the art all language such as “up to,” “at least.” and the like include the number recited and refer to ranges that can be subsequently broken down into subranges as discussed above. Finally, as will be understood by one skilled in the art, a range includes each individual member. Thus, for example, a group having 1-3 cells refers to groups having 1, 2, or 3 cells. Similarly, a group having 1-5 cells refers to groups having 1, 2, 3, 4, or 5 cells, and so forth.

The term “about,” as used herein, refers to variations in a numerical quantity that can occur, for example, through measuring or handling procedures in the real world; through inadvertent error in these procedures; through differences in the manufacture, source, or purity of compositions or reagents; and the like. Typically, the term “about” as used herein means greater or lesser than the value or range of values stated by 1/10 of the stated values, e.g., +10%. The term “about” also refers to variations that would be recognized by one skilled in the art as being equivalent so long as such variations do not encompass known values practiced by the prior art. Each value or range of values preceded by the term “about” is also intended to encompass the embodiment of the stated absolute value or range of values. Whether or not modified by the term “about,” quantitative values recited in the present disclosure include equivalents to the recited values, e.g., variations in the numerical quantity of such values that can occur, but would be recognized to be equivalents by a person skilled in the art.

Various of the above-disclosed and other features and functions, or alternatives thereof, may be combined into many other different systems or applications. Various presently unforeseen or unanticipated alternatives, modifications, variations or improvements therein may be subsequently made by those skilled in the art, each of which is also intended to be encompassed by the disclosed embodiments.

ROBOTIC ASSISTED LIGAMENT GRAFT PLACEMENT AND TENSIONING

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