Preoperative surgical planning system and method

Abstract

Improved surgical planning systems and methods are provided for planning orthopedic surgical procedures, including creating, editing, executing, and / or reviewing surgical plans pre-operatively, intra-operatively, and / or post-operatively. The surgical planning systems and methods may be utilized to plan and implement orthopedic surgical procedures to restore joint function. The systems and methods may provide / influence pre-operative surgical plans based on anatomical configuration classifications that characterize anatomical variations within a representative patient population, deviations from previous pre-operative surgical plans, post-operative patient outcome data, range of motion simulations, and / or survival prediction indexes that are percentiles of confidence levels that the surgical plan will result in successful surgical outcomes for at least a predetermined time.

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This disclosure claims priority to U.S. Patent Application No. 17 / 474,639, filed September 14, 2021, U.S. Patent Application No. 17 / 474,664, filed September 14, 2021, U.S. Patent Application No. 17 / 474,697, filed September 14, 2021, U.S. Patent Application No. 17 / 474,723, filed September 14, 2021, and U.S. Patent Application No. 17 / 474,744, filed September 14, 2021, the disclosures of which are incorporated by reference herein in their entireties.

[0002] The present disclosure relates to improved surgical planning systems and methods. [Background technology]

[0003] The present disclosure is directed to surgical planning, and more particularly, to improved surgical planning systems and methods for planning orthopaedic surgical procedures.

[0004] Arthroplasty is a type of orthopedic surgical procedure performed to repair or replace a diseased joint. Prior to performing arthroplasty, surgeons may wish to establish a surgical plan for preparing the surgical site, selecting an implant, and placing the implant at the surgical site in order to improve outcomes. The surgical plan may include capturing an image of the surgical site and determining the location of the implant based on the image. Summary of the Invention [Means for solving the problem]

[0005] The surgical planning systems and methods of the present disclosure may be utilized in some implementations for planning orthopedic surgical procedures, including pre-operative, intra-operative, and / or post-operative, to create, edit, execute, and / or review surgical plans. The surgical planning systems and methods may be utilized for planning and implementing orthopedic surgical procedures to restore function of a joint.

[0006] The surgical planning system may include a processor configured to generate a plurality of anatomical configuration classifications based on a plurality of predefined modes characterizing anatomical variances within a representative patient population and a plurality of standard deviations of anatomical variances within each of the plurality of predefined modes. A memory device of the system may be operatively coupled to the processor and configured to store the plurality of anatomical configuration classifications.

[0007] In a further embodiment, the processor is configured to analyze a representative patient population within the statistical shape model.

[0008] In a further embodiment, the processor is configured to identify a plurality of predefined modes and / or a plurality of anatomical landmarks in the statistical shape model to characterize the anatomical differences.

[0009] In a further embodiment, the processor is configured to identify a plurality of anatomical landmarks in the statistical shape model to characterize the anatomical variance.

[0010] In a further embodiment, the plurality of predefined modes includes a size, inclination, angle, or length associated with a bone or joint.

[0011] In a further embodiment, the processor is configured to establish a plurality of standard deviations of the anatomical variance included in each of a plurality of predefined modes to verify percentile coverage of a representative patient population.

[0012] In a further embodiment, the processor is configured to combine the multiple standard deviations with the multiple predefined modes to establish multiple anatomical configuration classifications.

[0013] In a further embodiment, the processor is configured to integrate multiple anatomical configuration classifications to represent variance within a representative patient population.

[0014] In a further embodiment, the processor is configured to virtually position the surgical implant in each of the integrated anatomical configuration classifications to establish a default starting position and a default orientation of the surgical implant.

[0015] In a further embodiment, each of the plurality of anatomical configuration classifications is a numerical classification of the anatomical configuration of a bone or joint of a representative patient population.

[0016] The computer-implemented surgical planning method includes, inter alia, identifying a plurality of predefined modes in a statistical shape model of a representative patient population, establishing a plurality of standard deviations of anatomical variances contained in each of the plurality of predefined modes, creating a plurality of anatomical configuration classifications based on the plurality of predefined modes and the plurality of standard deviations of anatomical variances via a processor of a surgical planning system configured to interface with the statistical shape model, and storing the plurality of anatomical configuration classifications in a memory device of the surgical planning system.

[0017] In a further embodiment, the plurality of predefined modes characterizes anatomical variations within a representative patient population.

[0018] In a further embodiment, the plurality of predefined modes includes sizes, inclinations, angles, or lengths associated with bones or joints of a representative patient population.

[0019] In a further embodiment, establishing the multiple standard deviations of the anatomical variance comprises examining percentile coverage of a representative patient population.

[0020] In a further embodiment, creating the multiple anatomical configuration classifications includes combining the multiple standard deviations with the multiple predefined modes to establish the multiple anatomical configuration classifications.

[0021] In a further embodiment, creating the multiple anatomical configuration classifications includes aggregating the multiple anatomical configuration classifications to represent variance within a representative patient population.

[0022] In a further embodiment, creating the multiple anatomical configuration classifications includes virtually positioning a surgical implant in each of the integrated anatomical configuration classifications to establish a default starting position and a default orientation of the surgical implant.

[0023] In a further embodiment, each of the plurality of anatomical configuration classifications is a numerical classification of the anatomical configuration of a bone or joint of a representative patient population.

[0024] In a further embodiment, a method includes receiving image data associated with a patient, generating a three-dimensional model of a bone or joint of the patient based on the image data, and assigning one of a plurality of anatomical configuration classifications to the three-dimensional model of the bone or joint.

[0025] In a further embodiment, the method includes querying a surgical outcomes database of the surgical planning system for previous surgical procedures with significantly comparable anatomical configuration classifications.

[0026] Another surgical planning system includes, inter alia, a storage device configured to store computer-executable instructions; and a processor operatively coupled to the storage device and configured to execute the computer-executable instructions to: search a pre-operative surgical plan approved by a surgeon from a database; determine whether the surgeon has deviated from the previous pre-operative surgical plan by less than a predetermined percentage of the previous surgical procedure; and, if the surgeon has deviated from the previous pre-operative surgical plan by less than a predetermined percentage of the previous surgical procedure, recommend a first surgical kit including only the implants and instruments necessary to execute the pre-operative surgical plan.

[0027] In a further embodiment, the predetermined percentage is five (5) percent of the previous surgical procedure.

[0028] In a further embodiment, the processor is configured to recommend a second surgical kit including a greater number of implants and instruments than the first surgical kit if the surgeon has deviated from the past pre-operative surgical plan by more than a predetermined percentage of previous surgical procedures.

[0029] In a further embodiment, the processor is configured to receive image data related to a patient to which the pre-operative surgical plan is associated, generate a three-dimensional model of a bone or joint of the patient based on the image data, and assign an anatomical configuration classification to the three-dimensional model of the bone or joint.

[0030] In a further embodiment, the processor is configured to query a surgical outcomes database of the surgical planning system for previous surgical procedures involving anatomical structure classifications significantly comparable to the anatomical configuration classification assigned to the three-dimensional model.

[0031] In a further embodiment, the processor is configured to recommend to the patient a surgical implant that is most compatible with the anatomical configuration classification assigned to the three-dimensional model.

[0032] In a further embodiment, prior to recommending the surgical implant, the processor is configured to determine a survival prediction index associated with use of the surgical implant for the patient.

[0033] In a further embodiment, the survival prediction index is a percentile representation of the confidence level that use of the surgical implant will result in a successful surgical outcome for at least a predetermined time period.

[0034] In a further embodiment, the processor is configured to receive post-operative patient outcome data associated with the patient and update the surgical outcome database with the post-operative patient outcome data.

[0035] In a further embodiment, the pre-operative surgical plan is at least partially informed by a survival prediction index calculated by the processor.

[0036] Another computer-implemented surgical planning method may include, inter alia, retrieving a pre-operative surgical plan approved by the surgeon from a cloud-based database, determining via a processor of the surgical planning system whether the surgeon has deviated from the past pre-operative surgical plan by less than a predetermined percentage of the previous surgical procedure, and recommending a first surgical kit including only the implants and instruments necessary to execute the pre-operative surgical plan if the surgeon has deviated from the past pre-operative surgical plan by less than a predetermined percentage of the previous surgical procedure.

[0037] In a further embodiment, the predetermined percentage is five (5) percent of the previous surgical procedure.

[0038] In a further embodiment, the method includes recommending a second surgical kit including a greater number of implants and instruments than the first surgical kit if the surgeon has deviated from the past pre-operative surgical plan by more than a predetermined percentage of previous surgical procedures.

[0039] In a further embodiment, a method includes receiving image data associated with a patient to which the pre-operative surgical plan is associated, generating a three-dimensional model of a bone or joint of the patient based on the image data, and assigning an anatomical configuration classification to the three-dimensional model of the bone or joint.

[0040] In a further embodiment, a surgical outcome database of the surgical planning system is queried for previous surgeries with anatomical structure classifications significantly comparable to the anatomical configuration classification assigned to the three-dimensional model.

[0041] In a further embodiment, the method includes receiving post-operative patient outcome data associated with the patient and updating a surgical outcome database with the post-operative patient outcome data.

[0042] In a further embodiment, the method includes recommending to the patient a surgical implant that is most compatible with the anatomical configuration classification assigned to the three-dimensional model.

[0043] In a further embodiment, the method includes determining a survival prediction index associated with use of the surgical implant in the patient.

[0044] In a further embodiment, the survival prediction index is a percentile representation of the confidence level that use of the surgical implant will result in a successful surgical outcome for at least a predetermined time period.

[0045] In a further embodiment, the pre-operative surgical plan is at least partially informed by a survival prediction index calculated by the processor.

[0046] Another surgical planning system may include, among other things, a memory device configured to store computer-executable instructions and a processor configured to execute the computer-executable instructions to receive post-operative patient outcome data from a user of the surgical planning system, assign anatomical configuration classifications to anatomical structures associated with the post-operative patient outcome data, and update a surgical outcome database of the surgical planning system based on the post-operative patient outcome data for the assigned anatomical configuration classifications.

[0047] In a further embodiment, the processor is configured to update the surgical outcomes database with the sizes and types of surgical implants identified in the post-operative patient outcome data.

[0048] In a further embodiment, the processor is configured to input the size and type of surgical implant into a range of motion database of the surgical planning system for the assigned anatomical configuration classification.

[0049] In a further embodiment, the processor is configured to update the range of motion database based on the input.

[0050] In a further embodiment, the processor is configured to update the surgical outcomes database with the positions and orientations of the surgical implants identified in the post-operative patient outcome data.

[0051] In a further embodiment, the processor is configured to input the position and orientation of the surgical implant into a range of motion database of the surgical planning system for the assigned anatomical configuration classification.

[0052] In a further embodiment, the processor is configured to update the range of motion database based on the input.

[0053] In a further embodiment, the processor is configured to receive a pre-operative surgical plan for the patient, assign a second anatomical configuration classification to an anatomical structure associated with the patient, query a surgical outcomes database for previous surgeries with anatomical configuration classifications significantly equivalent to the second anatomical configuration classification, and confirm the position and orientation of the patient's surgical implants based on the previous surgeries.

[0054] In a further embodiment, the pre-operative surgical plan is at least partially informed by a survival prediction index calculated by the processor, the survival prediction index being a percentile representation of a confidence level that the pre-operative surgical plan will result in a successful surgical outcome for at least a predetermined time period.

[0055] In a further embodiment, the anatomical configuration classification is a numerical classification of the anatomical configuration of the anatomical structure.

[0056] Another computer-implemented surgical planning method may include, inter alia, receiving post-operative patient outcome data from a user of the surgical planning system via a processor of the surgical planning system; assigning, via the processor, an anatomical configuration classification to an anatomical structure associated with the post-operative patient outcome data; and automatically updating a surgical outcome database of the surgical planning system based on the post-operative patient outcome data for the assigned anatomical configuration classification.

[0057] In a further embodiment, automatically updating the surgical outcome database includes updating the surgical outcome database with the size and type of surgical implant identified in the post-operative patient outcome data for the assigned anatomical configuration classification.

[0058] In a further embodiment, the method includes entering the size and type of surgical implant into a range of motion database of the surgical planning system for the assigned anatomical configuration classification.

[0059] In a further embodiment, the method includes updating the range of motion database in response to the input.

[0060] In a further embodiment, automatically updating the surgical outcome database includes updating the surgical outcome database with the positions and orientations of the surgical implants identified in the post-operative patient outcome data relative to the assigned anatomical configuration classification.

[0061] In a further embodiment, the method includes entering the position and orientation of the surgical implant into a range of motion database of the surgical planning system for the assigned anatomical configuration classification.

[0062] In a further embodiment, the method includes updating the range of motion database in response to the input.

[0063] In a further embodiment, the method includes receiving a pre-operative surgical plan for the patient, assigning a second anatomical configuration classification to an anatomical structure associated with the patient, querying a surgical outcomes database for previous surgeries with anatomical configuration classifications significantly equivalent to the second anatomical configuration classification, and confirming a position and orientation of the patient's surgical implant based on the previous surgeries.

[0064] In a further embodiment, the pre-operative surgical plan is at least partially informed by a survival prediction index calculated by the processor, the survival prediction index being a percentile representation of a confidence level that the pre-operative surgical plan will result in a successful surgical outcome for at least a predetermined time period.

[0065] In a further embodiment, the anatomical configuration classification is a numerical classification of the anatomical configuration of the anatomical structure.

[0066] Another surgical planning system may include, among other things, a processor configured to classify a representative patient population into a plurality of anatomical configuration classifications and to perform a range of motion simulation for each of the plurality of anatomical configuration classifications. A memory device of the system may be operatively coupled to the processor and may be configured to store range of motion data derived from the range of motion simulation for each of the plurality of anatomical configuration classifications.

[0067] In a further embodiment, the range of motion simulation is configured to simulate motion-related characteristics associated with a virtual joint derived from a representative patient population, further comprising one or more bones and a virtual surgical implant positioned relative to the one or more bones.

[0068] In further embodiments, the motion-related characteristic includes abduction, adduction, extension, flexion, internal rotation, external rotation, or any combination thereof.

[0069] In a further embodiment, the processor is configured to identify a collision point exhibiting a maximum range of motion associated with the motion-related characteristic.

[0070] In a further embodiment, the processor is configured to identify an angular arc and a collision mode associated with the collision point.

[0071] In a further embodiment, the processor is configured to adjust the position of the virtual surgical implant relative to the one or more bones in a plurality of offset directions.

[0072] In a further embodiment, the processor is configured to identify a second angular arc and a second collision mode associated with the second impact point based on the adjusted position of the virtual surgical implant.

[0073] In a further embodiment, the processor is configured to receive image data related to the patient, generate a three-dimensional model of a bone or joint of the patient based on the image data, assign one of a plurality of anatomical configuration classifications to the three-dimensional model of the bone or joint, and display range of motion data for the assigned anatomical configuration classification.

[0074] In a further embodiment, the processor is configured to receive input of a patient's activity of daily living goal and adjust a position of the virtual surgical implant within the three-dimensional model to achieve the activity of daily living goal.

[0075] In a further embodiment, the processor is configured to query a surgical outcome database of the surgical planning system for post-operative surgical outcome data, assign one of a plurality of anatomical configuration classifications to an anatomical structure associated with the post-operative surgical outcome data, and update range of motion data associated with the assigned anatomical configuration classification based on the post-operative surgical outcome data.

[0076] Another computer-implemented surgical planning method may include, inter alia, classifying a representative patient population into a plurality of anatomical configuration classifications via a processor of a surgical planning system, performing a range of motion simulation for each of the plurality of anatomical configuration classifications, and storing in a memory device of the surgical planning system range of motion data derived from the range of motion simulation for each of the plurality of anatomical configuration classifications.

[0077] In a further embodiment, the range of motion simulation is configured to simulate motion-related characteristics associated with a virtual joint derived from a representative patient population, further comprising one or more bones and a virtual surgical implant positioned relative to the one or more bones.

[0078] In a further embodiment, performing the range of motion simulation includes identifying a collision point that exhibits a maximum range of motion associated with the motion-related characteristic within the virtual joint.

[0079] In a further embodiment, performing the range of motion simulation includes identifying an angular arc and a collision mode associated with the collision point.

[0080] In a further embodiment, performing the range of motion simulation includes adjusting a position of the virtual surgical implant relative to the one or more bones in a plurality of offset directions.

[0081] In a further embodiment, performing the range of motion simulation includes identifying a second angular arc and a second impact mode associated with the second impact point based on the adjusted position of the virtual surgical implant.

[0082] In further embodiments, the motion-related characteristic includes abduction, adduction, extension, flexion, internal rotation, external rotation, or any combination thereof.

[0083] In a further embodiment, a method includes receiving image data associated with a patient, generating a three-dimensional model of a bone or joint of the patient based on the image data, assigning one of a plurality of anatomical configuration classifications to the three-dimensional model of the bone or joint, and displaying range of motion data for the assigned anatomical configuration classification.

[0084] In a further embodiment, the method includes receiving input of a patient's daily living goal and adjusting a position of the virtual surgical implant within the three-dimensional model to achieve the patient's daily living goal.

[0085] In a further embodiment, the method includes querying a surgical outcome database of the surgical planning system for post-operative surgical outcome data, assigning one of a plurality of anatomical configuration classifications to an anatomical structure associated with the post-operative surgical outcome data, and updating range of motion data associated with the assigned anatomical configuration classification based on the post-operative surgical outcome data.

[0086] Another surgical planning system may include, among other things, a storage device configured to store computer-executable instructions; and a processor operatively coupled to the storage device and configured to execute the computer-executable instructions to assign an anatomical configuration classification to a patient's anatomical structure, obtain surgical outcome data for an equivalent anatomical configuration classification, receive information regarding a plurality of variables related to a surgical plan for operating on the patient, determine a survival prediction index based on the surgical outcome data and the plurality of variables, receive an input of a correction for at least one of the plurality of variables, and update the survival prediction index in response to the correction.

[0087] In a further embodiment, the survival prediction index is a percentile representation of the confidence level that the surgical plan will result in a successful surgical outcome for at least a predetermined time.

[0088] In a further embodiment, the plurality of variables includes a surgical implant type, a surgical implant size, a surgical implant orientation, a surgical procedure type, a surgical implant back sheet configuration, a fastener orientation, or any combination thereof.

[0089] In a further embodiment, the processor is configured to estimate an average bone mineral density of a bone associated with the anatomical structure.

[0090] In a further embodiment, the processor is configured to query a surgical outcomes database of the surgical planning system for previous surgeries involving patients with comparable average bone density, and recommend surgical implants for use within the surgical plan that are not incompatible with the average bone density of the bone.

[0091] In a further embodiment, the processor is configured to receive a second input of an additional correction to the surgical plan to accommodate the recommended surgical implant, and update the survival prediction index in response to the additional correction.

[0092] In a further embodiment, the processor is configured to receive a second input of the approved surgical plan from the surgeon and recommend a surgical kit that includes only the surgical implants and instruments necessary to execute the approved surgical plan.

[0093] In a further embodiment, the processor is configured to recommend a surgical kit only if the surgeon has deviated from a previous approved surgical plan by less than a predetermined percentage of the previous surgical procedure.

[0094] In a further embodiment, the predetermined percentage is five (5) percent.

[0095] In a further embodiment, the processor is configured to instruct displaying the survival prediction index on a graphical user interface of a display module of the surgical planning system.

[0096] Another computer-implemented surgical planning method may include, inter alia, assigning an anatomical configuration classification to a patient's anatomical structure via a processor of the surgical planning system, obtaining surgical outcome data for an equivalent anatomical configuration classification, receiving information regarding a plurality of variables related to a surgical plan for operating on the patient, determining a survival prediction index via the processor based on the surgical outcome data and the plurality of variables, receiving an input of a correction for at least one of the plurality of variables, and updating the survival prediction index in response to the correction.

[0097] In a further embodiment, the survival prediction index is a percentile representation of the confidence level that the surgical plan will result in a successful surgical outcome for at least a predetermined time.

[0098] In a further embodiment, the plurality of variables includes a surgical implant type, a surgical implant size, a surgical implant orientation, a surgical procedure type, a surgical implant back sheet configuration, a fastener orientation, or any combination thereof.

[0099] In a further embodiment, the method includes estimating an average bone mineral density of a bone associated with the anatomical structure.

[0100] In a further embodiment, the method includes querying a surgical outcomes database of the surgical planning system for previous surgeries involving patients with comparable average bone density, and recommending surgical implants for use within the surgical plan that are compatible with the average bone density of the bone.

[0101] In a further embodiment, the method includes receiving a second input of an additional correction to the surgical plan to accommodate the recommended surgical implant, and updating the survival prediction index in response to the additional correction.

[0102] In a further embodiment, the method includes receiving a second input of the approved surgical plan from the surgeon and recommending a surgical kit including only the surgical implants and instruments necessary to execute the approved surgical plan.

[0103] In a further embodiment, the method includes recommending performing the surgical kit only if the surgeon has deviated from a previous approved surgical plan by less than a predetermined percentage of the previous surgical procedure.

[0104] In a further embodiment, the predetermined percentage is five (5) percent.

[0105] In a further embodiment, the method includes displaying the survival prediction index on a graphical user interface of a display module of the surgical planning system.

[0106] The embodiments, examples, and alternatives of the preceding paragraphs, claims, or the following description and drawings, including any of their various aspects or respective individual features, may be taken independently or in any combination. Features described in relation to one embodiment are applicable to all embodiments, unless such features are incompatible.

[0107] The various features and advantages of the present disclosure will become apparent to those skilled in the art from the following detailed description. The drawings that accompany the detailed description can be briefly described as follows. [Brief description of the drawings]

[0108] [Figure 1] FIG. 1 illustrates generally an exemplary surgical planning system. [Diagram 2] FIG. 2 illustrates generally an exemplary embodiment of the surgical planning system of FIG. [Diagram 3] FIG. 3 illustrates generally an exemplary cloud-based database that can be accessed by the surgical planning system. [Figure 4] FIG. 4 generally illustrates a further exemplary embodiment of the surgical planning system of FIG. [Diagram 5] FIG. 5 illustrates generally exemplary anatomical configuration classifications that may be assigned by a surgical planning system. [Figure 6] FIG. 6 illustrates generally a method for establishing an anatomical configuration classification database of a surgical planning system. [Figure 7] FIG. 7 illustrates generally a method for establishing a range of motion database of a surgical planning system. [Figure 8] FIG. 8 generally illustrates a further exemplary embodiment of the surgical planning system of FIG. [Figure 9] FIG. 9 generally illustrates a method for planning an orthopaedic surgical procedure for a respective patient using a surgical planning system. [Figure 10]FIG. 10 illustrates an exemplary user interface of a surgical planning system. [Figure 11] FIG. 11 generally illustrates another exemplary method for planning an orthopaedic surgical procedure for a respective patient using a surgical planning system. [Figure 12] FIG. 12 illustrates another exemplary user interface of a surgical planning system. [Figure 13A] FIG. 13A generally illustrates yet another exemplary method for planning an orthopaedic surgical procedure for a respective patient using a surgical planning system. [Figure 13B] FIG. 13B illustrates yet another exemplary user interface of the surgical planning system. [Figure 14] FIG. 14 generally illustrates an exemplary method for post-operatively updating one or more databases associated with a surgical planning system. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0109] The present disclosure is directed to improved surgical planning systems and methods for planning orthopedic surgical procedures, including creating, editing, executing, and / or reviewing surgical plans pre-operatively, intra-operatively, and / or post-operatively. The surgical planning systems and methods may be utilized to plan and implement orthopedic surgical procedures to restore function to a joint. These and other features of the present disclosure are discussed in more detail in the following paragraphs of the detailed description.

[0110] 1 illustrates an exemplary surgical planning system 10 (hereinafter referred to as "system 10"). System 10 may be used to plan orthopedic surgical procedures, including pre-operative, intra-operative, and / or post-operative, to create, edit, review, refine, and / or execute surgical plans. System 10 may be utilized for a variety of orthopedic and other surgical procedures, such as, for example, arthroplasty to repair a joint.

[0111] Shoulder arthroplasty may be referenced periodically throughout this disclosure to illustrate or highlight certain features of system 10. However, the teachings of the present disclosure are not intended to be limited to any particular joint of the human musculoskeletal system and, therefore, should be understood as applicable to the shoulder, knee, hip, ankle, wrist, etc. Furthermore, the teachings of the present disclosure are not intended to be limited to arthroplasty procedures and, therefore, are applicable to the repair of fractures and / or other deformities within the scope of the present disclosure.

[0112] System 10 may include, among other things, at least one host computer 12, one or more client computers 14, one or more imaging devices 16, a cloud-based storage system 18, and a network 20. System 10 may include a greater or lesser number of subsystems within the scope of this disclosure.

[0113] Host computer 12 may be configured to execute one or more software programs, in some implementations host computer 12 may be two or more computers configured in cooperation to process software instructions serially or in parallel.

[0114] The host computer 12 may be in communication with a network 20, which may itself include one or more computing devices. The network 20 may be, for example, a private local area network (LAN), a private wide area network (WAN), the Internet, or a mesh network.

[0115] The host computer 12 and each client computer 14 may include one or more of a computer processor, memory, storage means, network devices, and input and / or output devices and / or interfaces. Input devices may include a keyboard, mouse, etc. Output devices may include a monitor, speaker, printer, etc. Memory may include, for example, UVPROM, EEPROM, FLASH, RAM, ROM, DVD, CD, hard drive, or other computer readable medium that may store data and / or other information related to the surgical planning and performing techniques disclosed herein. The host computer 12 and each client computer 14 may be a desktop computer, a laptop computer, a smartphone, a tablet, a virtual machine, or any other computing device. Interfaces may facilitate communication with other systems and / or components of the network 20.

[0116] Each client computer 14 may be configured to communicate with the host computer 12 either directly, such as via a direct client interface 22, or through the network 20. In other implementations, the client computers 14 are configured to communicate directly with each other via a peer-to-peer interface 24.

[0117] Each client computer 14 may be coupled to one or more of the imaging devices 16. Each imaging device 16 may be configured to capture or acquire one or more images 26 of the patient's anatomy present within a scan field (e.g., window) of the imaging device 16. The imaging devices 16 may be configured to capture or acquire two-dimensional (2D) and / or three-dimensional (3D) grayscale and / or color images 26. A variety of imaging devices 16 may be utilized, including, but not limited to, X-ray devices, computed tomography (CT) devices, or magnetic resonance imaging (MRI) devices, to acquire the one or more images 26 of the patient.

[0118] The client computers 14 may also be configured to execute one or more software programs, such as those associated with various surgical planning tools. Each client computer 14 may be operable to access and locally and / or remotely execute a planning environment 28 for creating, editing, executing, refining, and / or reviewing one or more surgical plans 36 during the pre-operative, intra-operative, and / or post-operative phases of a surgical procedure. The planning environment 28 may be a stand-alone software package or may be incorporated into another surgical tool. The planning environment 28 may be configured to communicate with the host computer 12 either through the network 20 or directly through a direct client interface 22.

[0119] The planning environment 28 may be further configured to interact with one or more of the imaging devices 16 to capture or acquire images 26 of the patient's anatomy. The planning environment 28 may provide for display or visualization of one or more of the images 26, bone model 30, implant model 32, transfer model 34, and / or surgical plan 36 via one or more graphical user interfaces (GUIs). Each image 26, bone model 30, implant model 32, transfer model 34, surgical plan 36, and other data and / or information may be stored in one or more files or records according to a specified data structure.

[0120] The planning environment 28 may include various modules for performing desired planning functions. For example, as discussed further below, the planning environment 28 includes a data module for accessing, acquiring, and / or storing data related to the surgical plan 36, a display module for displaying the data (e.g., in one or more GUIs), a spatial module for modifying the data displayed by the display module, and a comparison module for determining one or more relationships between, for example, a selected bone model and a selected implant model. However, a greater or lesser number of modules may be utilized and / or one or more of the modules may be combined to provide the disclosed functionality.

[0121] Storage system 18 may be operable to store or otherwise provide data to / from other computing devices, such as host computer 12 and / or one or more client computers 14 of system 10. Storage system 18 may be, for example, a storage area network device (SAN) configured to communicate with host computer 12 and / or client computers 14 over network 20. Although shown as a separate device in system 10, in some implementations storage system 18 may be incorporated within or directly coupled to host computer 12 and / or client computer 14. Storage system 18 may be configured to store one or more of computer software instructions, data, database files, configuration information, and the like.

[0122] In some implementations, system 10 may be a client-server architecture configured to execute computer software on host computer 12, which may be accessible by client computer 14 using either a thin client application or a web browser that may be executed on client computer 14. Host computer 12 may load computer software instructions into memory from local storage or from storage system 18 and may execute the computer software using one or more computer processors.

[0123] The system 10 may further include one or more databases 38. The database 38 may be stored in a central location, such as on the storage system 18. In another implementation, the one or more databases 38 may be stored in the host computer 12 and / or may be distributed databases provided by one or more of the client computers 14. Each database 38 may be a relational database configured to associate one or more of the images 26, bone models 30, implant models 32, and / or transfer models 34 with each other and / or with a respective surgical plan 36. Each surgical plan 36 may be associated with a respective patient anatomy. Each image 26, bone model 30, implant model 32, transfer model 34, and surgical plan 36 may be assigned a unique identifier or database entry for storage on the storage system 18. Each database 38 may be configured to store data and other information corresponding to the images 26, bone models 30, implant models 32, transfer models 34, and surgical plans 36 in one or more database records or entries, and / or may be configured to link or otherwise associate one or more files corresponding to each respective image 26, bone models 30, implant models 32, transfer models 34, and surgical plans 36. The various data stored in the databases 38 may correspond to the respective patient's anatomy from previous surgical cases, and may be arranged into one or more predefined classifications, such as gender, age, race, defect classification, procedure type, anatomical configuration classification, surgeon, facility or organization, etc.

[0124] Each image 26 and bone model 30 may include data and other information obtained from one or more medical devices or tools, such as imaging device 16. Bone model 30 may include one or more digital images and / or coordinate information related to the patient's anatomy obtained or derived from images 26 captured or otherwise obtained by imaging device 16.

[0125] Each implant model 32 and transfer model 34 may include coordinate information associated with a design established or modified by a given design or planning environment 28. A given design may correspond to one or more components. The planning environment 28 incorporates and / or interfaces with one or more modeling packages, such as a computer-aided design (CAD) package, to render the models 30, 32, 34 as two-dimensional (2D) and / or three-dimensional (3D) volumes or constructs, which may overlay one or more of the images 26 within a display screen of the GUI.

[0126] The implant models 32 may correspond to implants and components of various shapes and sizes. Each implant may include one or more components that may be placed at a surgical site, including screws, anchors, grafts, etc. Each implant model 32 may correspond to a single component or may include two or more components that may be configured to establish an assembly. Each implant and associated components may be formed of various materials, including metallic and / or non-metallic materials. Each bone model 30, implant model 32, and transfer model 34 may correspond to 2D and / or 3D geometric shapes and may be utilized to generate wireframe, mesh, and / or solid constructs within the GUI.

[0127] Each surgical plan 36 may be associated with one or more of the images 26, the bone models 30, the implant models 32, and / or the transfer models 34. The surgical plans 36 may include various parameters associated with the images 26, the bone models 30, the implant models 32, and / or the transfer models 34. For example, the surgical plans 36 may include parameters related to bone density and bone quality associated with the patient's anatomy captured in the images 26. The surgical plans 36 may include parameters including spatial information related to the relative positioning and coordinate information of the selected bone models 30, the implant models 32, and / or the transfer models 34.

[0128] The surgical plan 36 may define one or more corrections to the bone model 30 and information related to the position of the implant model 32 and / or the transfer model 34 relative to the original and / or corrected bone model 30. The surgical plan 36 may include coordinate information related to the corrected bone model 30 and the relative positions of the implant model 32 and / or the transfer model 34 in one or more predefined data structures. The planning environment 28 may be configured to implement one or more corrections to the various models either automatically or in response to user interaction with a user interface. The corrections to each bone model 30, implant model 32, transfer model 34, and / or surgical plan 36 may be stored in one or more of the databases 38 either automatically and / or in response to user interaction with the system 10.

[0129] One or more surgeons and / or other staff users may be presented with the planning environment 28 via the client computers 14 and may simultaneously access the images 26, bone models 30, implant models 32, transfer models 34, and surgical plans 36 stored in the database 38. Each user may interact with the planning environment 28 to create, view, refine, and / or modify various aspects of the surgical plan 36. Each client computer 14 may be configured to store local instances of the images 26, bone models 30, implant models 32, transfer models 34, and / or surgical plans 36, which may be synchronized in real time or periodically with the database 38. The planning environment 28 may be a stand-alone software package executing on the client computers 14 or may be provided as one or more web-based services executing on the host computer 12, for example.

[0130] The above-described system 10 may be configured to pre-plan a surgical procedure. The pre-operative planning provided by the system 10 may include features such as, but not limited to, constructing a virtual model of the patient's anatomy, classifying the virtual model, identifying landmarks within the virtual model, and selecting and orienting virtual implants within the virtual model.

[0131] With continued reference now to FIGURE 1, and with reference to FIGURE 2, the system 10 may include a computing device 40 including at least one processor 42 coupled to a memory 44 having the capacity to store computer executable instructions. The computing device 40 may be considered representative of any of the computing devices disclosed herein, including but not limited to the host computer 12 and / or the client computer 14. The processor 42 may be configured to execute one or more of the planning environments 28 for creating, editing, executing, refining, and / or reviewing one or more surgical plans 36 and any associated bone models 30, implant models 32, and transfer models 34 during pre-operative, intra-operative, and / or post-operative phases of a surgical procedure.

[0132] The processor 42 may be a custom or commercially available processor, a central processing unit (CPU), or generally any device for executing software instructions. The memory 44 may include any one or combination of volatile and / or non-volatile memory elements. The processor 42 may be operatively coupled to the memory 44 and may be configured to execute one or more programs stored in the memory 44 based on various inputs received from other devices or data sources.

[0133] Planning environment 28 may include at least a data module 46, a display module 48, a spatial module 50, and a comparison module 52. Although four modules are shown, it will be appreciated that a greater or lesser number of modules may be utilized and / or further, one or more of the modules may be combined to provide the disclosed functionality.

[0134] The data module 46 may be configured to access, retrieve, and / or store data and other information corresponding to one or more images 26 of the patient's anatomy, bone model 30, implant model 32, transfer model 34, and / or surgical plan 36 in a database 38. The data and other information may be stored in the one or more databases 38 as one or more records or entries 54. In some implementations, the data and other information may be stored in one or more files accessible by referencing one or more objects or memory locations referenced by the entries 54.

[0135] The memory 44 may be configured to access, load, edit, and / or store instances of one or more images 26, bone models 30, implant models 32, transmission models 34, and / or surgical plans 36 in response to one or more commands from the data module 46. The data module 46 may be configured to cause the memory 44 to store local instances of the images 26, bone models 30, implant models 32, transmission models 34, and / or surgical plans 36, which may be synchronized with entries 54 stored in the database 38.

[0136] The data module 46 may be configured to receive data and other information corresponding to at least one or more images 26 of the patient's anatomy from various sources, such as the imaging device 16. The data module 46 may be further configured to command the imaging device 16 to capture or acquire the images 26 automatically or in response to user interaction.

[0137] The display module 48 may be configured to display data and other information related to the one or more surgical plans 36 in at least one graphical user interface (GUI) 56, including one or more of the images 26, bone model 30, implant model 32, and / or transfer model 34. The computing device 40 may incorporate or be coupled to the display 58. The display module 48 may be configured to cause the display 58 to display information in the user interface 56. A surgeon or other user may interact with the user interface 56 in the planning environment 28 to view one or more images 26 of the patient's anatomy and / or any associated bone model 30, implant model 32, and transfer model 34. A surgeon or other user may interact with the user interface 56 via the planning environment 28 to create, edit, execute, refine, and / or review one or more surgical plans 36.

[0138] User interface 56 may include one or more viewing windows 60 and one or more objects 62 that may be presented within viewing windows 60. Viewing windows 60 may include any number of windows and objects 62 may include any number of objects within the scope of this disclosure.

[0139] A surgeon or user may interact with the user interface 56, including the objects 62 and / or the viewing windows 60, to retrieve, display, edit, store, etc., various aspects of the respective surgical plan 36, which may include information from the selected image 26, bone model 30, implant model 32, and / or transfer model 34. The objects 62 may include graphics such as menus, tabs, buttons, drop-down lists, directional indicators, etc. The objects 62 may be organized into one or more menu items associated with the respective viewing windows 60. Geometric objects including the selected image 26, bone model 30, implant model 32, transfer model 34, and / or other information regarding the surgical plan 36 may be displayed in one or more of the viewing windows 60. Each transfer model 34 may include one or more surgical instruments used to implant the implant selected as part of the surgical plan 36.

[0140] The surgeon may interact with the object 62 to specify various aspects of the surgical plan 36. For example, the surgeon may select one of the tabs to view or specify an aspect of the surgical plan 36 for one portion of the joint, such as the glenoid, and may select another of the tabs to view or specify an aspect of the surgical plan 36 for another portion of the joint, such as the humerus. The surgeon further takes various measurements of the joint (e.g., alignment, angle, tissue density, etc.) as part of specifying an aspect of the surgical plan 36.

[0141] The surgeon may interact with the menu items to select and specify various aspects of the bone model 30, implant model 32, and / or transfer model 34 from the database 38. For example, the display module 48 may be configured to display one or more bone models 30 along with respective images 26 of the patient's anatomy and implant model 32 selected in response to the user's interaction with the user interface 56. The user may interact with drop-down lists of objects 62 in the display window 60 to specify the implant type, resection angle, and implant size. The resection angle menu item may be further associated with a resection plane.

[0142] The user may also interact with various buttons to change (e.g., increase or decrease) the resection angle. The user may interact with buttons adjacent to the selected implant model 32 to change (e.g., increase or decrease) the size of a component of the selected implant model 32. The buttons may be superimposed on or located adjacent to the viewing window 60.

[0143] The user may further interact with a directional indicator to move a portion of the selected implant model 32 in different directions (e.g., up, down, left, right) within one viewing window 60. The surgeon may drag or otherwise move the selected implant model 32 to a desired location in the viewing window 60, for example, using a mouse or other input device. The surgeon may interact with one of the drop down lists to specify the type and / or size of a component of the selected implant model 32.

[0144] The display module 48 may be configured to superimpose one or more of the bone model 30, the implant model 32, and the transfer model 34 over one or more of the images 26 in one or more of the viewing windows 60. The implant model 32 may include one or more components that establish an assembly. At least a portion of the implant model 32 may be configured to be at least partially received in a selected one of the volumes of the bone model 30. In some implementations, the implant model 32 may have an articular surface sized to mate with an articular surface of an opposing bone or implant.

[0145] The viewing windows 60 may be configured to display the image 26, the bone model 30, the implant model 32, and / or the transfer model 34 in various orientations. The display module 48 may be configured to display a two-dimensional (2D) representation of the selected bone model 30, the implant model 32, and / or the transfer model 34 in some viewing windows 60, and may be configured to display a 3D representation of the selected bone model 30, the implant model 32, and / or the transfer model 34 in other viewing windows 60, for example. The surgeon may interact with the user interface 56 to move (e.g., up, down, left, right, rotate, etc.) the selected bone model 30, the selected implant model 32, and / or the selected transfer model 34 in 2D and / or 3D space. Other implementations for displaying 2D and / or 3D representations in the various viewing windows 60 are further contemplated within the scope of the present disclosure.

[0146] The display module 48 may further be configured such that a selected image 26, bone model 30, implant model 32, and / or transfer model 34 may be selectively displayed and hidden (e.g., toggled) in one or more of the display windows 60 in response to a user interaction with the user interface 56, which may provide the surgeon with improved flexibility when reviewing aspects of the surgical plan 36. For example, the surgeon may interact with a drop-down list of objects 62 to selectively display and hide components of the selected implant model 32 in one of the display windows 60.

[0147] The selected bone model 30 may correspond to a bone associated with a joint, including any of the example joints disclosed herein. The display module 48 may be configured to display a cross-sectional view of the selected bone model 30 and the selected implant model 32, for example, in one or more of the viewing windows 60. The cross-sectional view of the bone model 30 may be presented or displayed along with the associated image 26 of the patient's anatomy.

[0148] The spatial module 50 may be configured to establish one or more resection planes along the selected bone model 30. A volume of the selected implant model 32 may be at least partially received in the selected volume of the bone model 30 along the resection planes. The resection planes may be defined by resection angles.

[0149] The spatial module 50 may further be configured to cause the display module 48 to display the resected portion of the selected bone model 30 in one of the viewing windows 60 in a manner different from the remaining portion of the bone model 30 on the opposite side of the resection plane. For example, the resected portion of the bone model 30 may be hidden from view in the viewing windows 60 such that the 26 respective portions of the patient's anatomy are shown. In other implementations, the resected portion of the selected bone model 30 may be displayed in a relatively darker shade. The spatial module 50 may determine the resected portion by, for example, comparing the coordinates of the bone model 30 to the location of the resection plane. A user may interact with one or more buttons on the object 62 to toggle between a previous state and a modified (e.g., resected) state of a volume of the selected bone model 30.

[0150] Planning environment 28 may further be configured such that changes in one of the viewing windows 60 are synchronized with each of the other windows 60. The switching may be synchronized automatically and / or manually between the viewing windows 60 in response to user interaction.

[0151] The surgeon may utilize various instruments and devices to perform each surgical plan 36, including creating a surgical site and securing one or more implants to bone or other tissue to restore function to the respective joint. Each of the transfer models 34 may be associated with a respective surgical instrument or device (e.g., a transfer guide, etc.), or a respective implant model 32.

[0152] The surgical plan 36 may be associated with one or more positioning objects, such as guide pins (e.g., guide wires or Kirschner wires) sized to be anchored within tissue to position and orient various instruments, devices, and / or implants. The display module 48 may be configured to display virtual positions and virtual axes in one or more of the display windows 60. The virtual positions may be associated with specified positions of the positioning objects relative to the patient's anatomy (as represented by the image 26). The virtual axes may extend through the virtual positions and may be associated with specified orientations of the positioning objects relative to the patient's anatomy. The spatial module 50 may be configured to set the virtual positions and / or virtual axes in response to placement of the respective implant models 32 relative to the bone model 30 and the associated patient's anatomy. The virtual positions and / or virtual axes may be automatically set and / or adjusted based on the position and orientation of the selected implant model 32 relative to the selected bone model 30 and / or in response to user interaction with the user interface 56.

[0153] The spatial module 50 may further be configured to determine one or more collision or contact points associated with the patient's anatomy. The contact points may be associated with one or more landmarks or other surface features along the bone model 30 and / or other portions of the patient's anatomy. Each contact point may be established along an articular or non-articular surface of a joint. The spatial module 50 may be configured to set the contact points based on a virtual position, a virtual axis, and / or a position and orientation of each implant model 32 relative to the patient's anatomy. The spatial module 50 may be configured to cause the display module 48 to display the contact points in one or more of the display windows 60. In some implementations, the contact points may be automatically set and / or adjusted based on the position of the implant model 32 and / or in response to user interaction with the user interface 56. The virtual positions, virtual axes, and / or contact points may be stored in one or more entries 54 in the database 38 and associated with the respective surgical plan 36.

[0154] The comparison module 52 may be configured to generate or set one or more parameters associated with the implementation of the surgical plan 36. The parameters may include one or more settings or dimensions associated with each transfer model 34. The parameters may be based on a virtual position, a virtual axis, and / or a contact point. The comparison module 52 may be configured to determine one or more settings or dimensions associated with each transfer model 34 relative to the patient's anatomy, the bone model 30, the implant model 32, the virtual position, the virtual axis, and / or the contact point CP. The dimensions and settings may be utilized to form a physical instance of each respective transfer model 34. The settings may be utilized to specify the position and orientation of each respective transfer model 34 relative to the implant model 32 and / or the bone model 30. The settings may be utilized to configure one or more transfer members (e.g., objects) and associated instruments or devices associated with the transfer model 34. The comparison module 52 may be configured to generate settings and / or dimensions such that the transfer model 34, when coupled to the respective implant model 32, will contact one or more predetermined locations on or along the bone model 30 or the patient's anatomy at the attachment location. The predetermined locations may include one or more of the contact points. The settings and dimensions may be communicated utilizing a variety of techniques, including one or more images in the user interface 56 or an output file. The settings and / or dimensions may be stored in one or more entries 54 in the database 38 associated with the transfer model 34.

[0155] A user may interact with a list of objects 62 associated with one of the viewing windows 60 to select a transmission model 34 from the database 38. The display module 48 may be configured to display the selected transmission model 34 in the viewing window 60 at various positions and orientations. The spatial module 50 may be configured to set an initial position of the selected transmission model 34 according to a virtual position, a virtual axis, and / or a contact point.

[0156] The user may interact with the user interface 56 to set or adjust the position and / or orientation of the selected transfer model 34. The user may interact with the directional indicators of the object 62 to move the selected transfer model 34 and / or virtual position in different directions (e.g., up, down, left, right) in the viewing window 60. The surgeon may, for example, utilize a mouse or other input device to drag or otherwise move the selected transfer model 34 and / or virtual position to a desired position in the viewing window 60. The user may interact with the rotation indicators of the object to adjust the position and / or orientation of the transfer model 34 about a virtual axis relative to the selected bone model 30 and / or implant model 32. The user may interact with the tilt indicators of the object 62 to adjust the orientation of the selected transfer model 34 and associated virtual axis in a virtual position relative to the selected bone model 30 and / or implant model 32. The user may interact with other buttons and / or directional indicators to articulate or otherwise move the transfer model 34. The transfer model 34 may be articulated or otherwise moved independently or synchronously, which may occur manually in response to user interaction and / or automatically in response to positioning the transfer model 34 relative to the bone model 30 and / or implant model 32. Movement of the transfer model 34 may automatically adjust the respective contact points.

[0157] Various transmission members may be utilized in the planning environment 28 to implement the surgical plan 36. Each transmission member may be associated with a respective transmission model 34. The transmission members may be incorporated into transmission guides, implants, and / or assemblies to set the position and orientation of the respective implants prior to fixing or otherwise affixing the implants to the surgical site.

[0158] Now referring to FIG. 3 with continuing reference to FIG. 2, a computing device 40 may interface with the storage system 18 through the network 20 to access various databases 38 stored thereon in order to establish and implement a surgical plan 36.

[0159] The databases 38 of the storage system 18 may include a patient profile database 64, a surgeon profile database 65, a surgical outcomes database 66, a range of motion database 68, and an anatomical configuration classification database 70. Additional databases may be stored on and accessed from the storage system 18 within the scope of the present disclosure. Moreover, although shown as separate databases, one or more of the databases may be combined or linked together. For example, the anatomical configuration classification database 70 may be combined or linked with the surgical outcomes database 66, the range of motion database 68, or both.

[0160] The patient profile database 64 may include information that is part of the indexed and stored records or entries related to one or more current patients associated with the system 10. Information stored on the patient profile database 64 may include, for each patient, gender, age, race, height, weight, defect category, procedure type, surgeon, facility or organization, major joints, activities of daily living / lifestyle goal profile (e.g., desired post-operative range of motion for abduction, adduction, external rotation, internal rotation, extension, flexion, external rotation combined with 60° abduction, internal rotation with 60° abduction, etc.), current surgical planning information, etc. The patient profile database 64 may further store or link to images 26 for a given patient.

[0161] The Surgeon Profile Database 65 may include information that is part of the indexed and stored records or entries related to one or more surgeon users associated with the system 10. The information stored on the Surgeon Profile Database 65 may include the surgeon's name, facility or organization, historical data regarding the types of previous surgeries planned by the surgeon using the system 10, data regarding the types of implants included in the surgeon's pre-operative surgical plan, data regarding the actual implants utilized in the surgeon's previous surgeries, etc. In some implementations, the Surgeon Profile Database 65 may interface with the Patient Profile Database 64 to link each surgeon from the Surgeon Profile Database 65 to that surgeon's patients listed in the Patient Profile Database 64.

[0162] The surgical outcome database 66 may include information that is part of the indexed and stored records or entries related to one or more previous patients associated with the system 10. The surgical outcome database 66 may be created based on information logged by the surgeon and / or other staff users after performing each surgical procedure and at each follow-up visit to show the progress of the previous patients. The information stored on the surgical outcome database 66 may include for each previous patient the gender, age, race, height, weight, defect category, type of procedure, specific implants used, surgeon, institution or organization, major joint, visual analog pain score, ASES score, achieved activities of daily living / lifestyle profile (e.g., desired achieved postoperative range of motion for abduction, adduction, external rotation, internal rotation, extension, flexion, external rotation combined with 60° abduction, internal rotation with 60° abduction, etc.), surgical planning information, etc. The surgical outcome database 66 may additionally store or link to pre- and post-operative images 26 for each previous patient.

[0163] The range of motion database 68 may include information that is part of the indexed and stored records or entries associated with one or more current and previous patients associated with the system 10. The range of motion database 68 may store range of motion data resulting from range of motion simulations performed by the computing device 40 for each surgical plan 36. The range of motion data may include information related to simulated joint movements (e.g., abduction / adduction, flexion / extension, internal / external rotation, etc.), identified contact or collision points for various implant locations, angular arcs and collision modes (e.g., implant-to-implant, implant-to-bone, bone-to-bone, etc.) for various implant locations, adjusted centers of rotation of the implants at multiple incremental and offset orientations for various implant locations, etc.

[0164] The anatomical configuration classification database 70 may store a plurality of anatomical configuration classifications that characterize the anatomical variances and anatomical variances within a representative patient population for one or more intended surgical procedures (e.g., total shoulder, reverse shoulder arthroplasty, etc.). In some implementations, the representative patient population may be derived by analyzing image data, such as images from previous patients stored in the surgical outcomes database 66 and / or any other imaging source, associated with a plurality of previous patients who have already undergone the intended surgical procedure. Each of the plurality of anatomical configuration classifications is a numerical classification of the anatomical configuration of a bone or joint of the representative patient population.

[0165] 1-3, and now referring to FIG 4, computing device 40 may interface with a statistical shape modeler 72 to create an anatomical configuration classification database 70. Statistical shape modeler 72 may be a software package that may be stored in memory 44 or storage system 18 of computing device 40 and executed by processor 42.

[0166] The statistical shape modeler 72 may receive multiple sets of image data 74 associated with a target bone or joint. In some implementations, the sets of image data 74 consist of tens of thousands of sets of image data. Each set of image data 74 may include 2D and / or 3D anatomical images that are prior patient-specific for a representative patient population for the target bone or joint and associated with a given type of surgical procedure. The statistical shape modeler 72 may analyze the multiple sets of image data 74 to construct a statistical shape model 75.

[0167] As input, statistical shape modeler 72 may receive a number of pre-defined modes 76 used to analyze the multiple sets of image data 74. Each of the modes 76 is a descriptor configured to characterize anatomical variations within a bone or joint associated with the statistical shape model 75. Exemplary modes 76 that may be provided to the statistical shape modeler 72 may include, but are not limited to, glenoid size, scapular size, amount of tilt, number of versions, predicted amount of glenoid and sagittal neck length, glenoid angle relative to scapular neck, critical shoulder angle, acromion and / or coracoid prediction, humeral head size, humeral head varus / valgus, femoral and / or tibial varus / valgus, femoral and / or tibial internal / external rotation, subscapularis, deltoid, and / or supraspinatus integrity, ML and AP widths, intercondylar notch depth, tibial slope, knee Q angle, ACL / PCL stability, MCL / LCL stability, amount of flexion, amount of extension, quality and amount of soft tissue surrounding the joint, patellar tracking angle, bone density, bony subluxation rate, anatomical landmarks, joint cavity, pre-operative range of motion, any combination of the foregoing, and the like.

[0168] In some implementations, at least seven different modes may be utilized by statistical shape modeler 72 to characterize statistical shape model 75. However, a greater or lesser number of modes may be provided within the scope of this disclosure.

[0169] In some implementations, the modes 76 may not be pre-defined. Rather, the statistical shape modeler 72 may be programmed to utilize artificial intelligence (e.g., neural networks) or machine learning to estimate the modes that are best associated with the bones or joints modeled in the statistical shape model 75.

[0170] As another input, the statistical shape modeler 72 may receive a number of predefined standard deviations 78 used to analyze the multiple sets 74 of image data. Each standard deviation 78 may be representative of the anatomical variance (e.g., distance between features, orientation of features, relative features, etc.) contained within each of the multiple predefined modes 76. The standard deviations 78 may be used to verify percentile coverage of a representative patient population represented within the statistical shape model 75. In some implementations, at least seven different standards of deviation (e.g., -3, -2, -1, 0, 1, 2, and 3) may be utilized by the statistical shape modeler 72 to further characterize all anatomical variance contained within the anatomical structures described within the statistical shape model 75. However, a larger or smaller number of standard deviations may be utilized within the scope of the present disclosure.

[0171] The statistical shape modeler 72, in response to commands from the processor 42, combines the plurality of standard deviations 78 with the plurality of predetermined modes 76 to generate a plurality of anatomical feature classifications 80 into bones or joints associated with the statistical shape model 75 in order to classify the anatomical features across the patient population represented within the statistical shape model 75. N , where N is any number. Then, each anatomical configuration classification 80 N may be stored in the anatomical structure classification database 70 of the storage system 18.

[0172] 5 illustrates an example anatomical configuration classification 80 that has been assigned to a particular bone model 82 derived from statistical shape model 75. In one embodiment, bone model 82 is a 3D model of the scapula of the shoulder joint, however, other bones and joints may be classified in a similar manner.

[0173] 4 may analyze bone model 82 with respect to each of a number of modes 761-767 to characterize any anatomical differences in bone model 82 compared to other similar bones / joints associated with statistical shape model 75. Of course, a greater or lesser number of modes are possible.

[0174] The statistical shape modeler 72 may further characterize any anatomical variance contained within each of the plurality of predefined modes 761-767 by analyzing each of the modes against a plurality of standard deviations 781-787. Of course, greater or lesser numbers of standard deviations are possible.

[0175] 5, bone model 82 has been assigned the numeric value 0213120 as its anatomical configuration classification 80. This numeric value represents a standard of 0 deviations in a first mode 761, a standard of 2 deviations in a second mode 762, a standard of 1 deviation in a third mode 763, a standard of 3 deviations in a fourth mode 764, a standard of 1 deviation in a fifth mode 765, a standard of 2 deviations in a sixth mode 766, and a standard of 0 deviations in a seventh mode 767. Anatomical configuration classification 80 is a unique numerical identifier to describe the anatomical structure associated with bone model 82.

[0176] 6, with continued reference to FIGS. 1-5, generally illustrates a method 84 for creating the anatomical configuration classification database 70 described above. The method 84 may be implemented as part of a surgical planning procedure. Fewer or additional steps than those listed below may be implemented within the scope of the present disclosure, and the order of the steps listed is not intended to limit the present disclosure. The system 10 may be configured to execute each of the steps of the method 84 via any of its associated computing devices and modules. In an exemplary implementation, the computing device 40 of the host computer 12 may be programmed to execute the method 84. However, other implementations are still contemplated within the scope of the present disclosure.

[0177] A statistical shape model 75 representing a patient population having pathological anatomy relevant to the intended surgery may be constructed at step 86. A number of modes 76 may be identified within the statistical shape model 75 at step 88. The modes 76 may characterize anatomical variations within the statistical shape model 75.

[0178] Next, at step 90, a number of standard deviations 78 of the anatomical variance contained within each of the modes 76 may be established. The standard deviations 78 may be used to validate percentile coverage of a representative patient population associated with the statistical shape model 75.

[0179] The standard deviation 78 may be combined with the mode 76 to create multiple unique anatomical configuration classifications 80 at step 92. At step 94, the anatomical configuration classifications 80 may be combined to form the anatomical configuration classification database 70. Thus, the anatomical configuration classification database 70 may represent a large variance within a representative patient population that may affect implant function.

[0180] As a further part of the method 84, an appropriately sized implant model 32 may be selected and positioned in a default starting position and orientation relative to the bone or joint associated with each of the multiple anatomical configuration classifications 80 at step 96. Accordingly, the default starting position and orientation of the implant model 32 may also be linked to and stored as part of the anatomical configuration classifications 80 as part of the anatomical configuration classification database 70 at step 97.

[0181] Once established, anatomical configuration classification database 70 may enable additional features, processes, and / or capabilities to be implemented within or performed by system 10 to enhance surgical planning. Exemplary implementations of such features are detailed below.

[0182] FIG. 7 illustrates a method 98 for augmenting range of motion database 68, for example, with information contained within anatomical configuration classification database 70. Method 98 may be implemented as part of a surgical planning procedure. Fewer or additional steps than those listed below may be implemented within the scope of the present disclosure, and the order of the steps listed is not intended to limit the present disclosure. System 10 may be configured to perform each of the steps of method 98 via any of its associated computing devices and modules. In an exemplary implementation, computing device 40 of host computer 12 may be programmed to perform method 98. However, other implementations are still contemplated within the scope of the present disclosure.

[0183] First, at step 100, one or more motion simulations may be performed for each anatomical configuration classification 80 stored in the anatomical configuration classification database 70. The motion simulations may be performed within a range of motion modeler 101, which may be a software package stored in memory 44 or storage system 18 of the computing device 40 and executed by the processor 42 (see, for example, FIG. 8 ). When performing the motion simulations, the range of motion modeler 101 may receive each of the anatomical configuration classifications 80 (as well as each associated bone model 30 and implant model 32, including default implant starting positions and orientations) as input from the anatomical configuration classification database 70.

[0184] The actual range of motion simulation performed in step 100 will depend on the type of bone or joint being analyzed, among other criteria. Examples of the types of movements that may be simulated as part of step 100 of method 98 include, but are not limited to, abduction / adduction, flexion / extension, internal / external rotation, etc.

[0185] Contact or collision points may be identified in step 102 to identify range of motion end points for each range of motion simulation performed on each anatomical configuration classification 80. The angular arc and collision mode (e.g., implant-to-implant, implant-to-bone, bone-to-bone, etc.) for each contact point may be recorded in step 104.

[0186] The center of rotation of the implant models 32 positioned within the bone models 30 for each anatomical configuration classification 80 may be adjusted in step 106. In some implementations, this step may include adjusting each implant model 32 in at least three offset directions (e.g., medial, medial, and posterior) relative to the respective bone models 30 to simulate different positions of the implant models 32.

[0187] At step 108, the center of rotation of the implant model 32 for each anatomical configuration classification 80 may be adjusted in multiple increments relative to the respective bone model 30 to record the angular arc and impact mode associated with the adjusted position. All range of motion data derived from the simulations performed at steps 100-108 may then be stored in the range of motion database 68 at step 110.

[0188] FIG. 9 illustrates a method 112 for planning an orthopaedic surgical procedure for a respective patient using the system 10. The method 112 may be implemented as part of a surgical planning procedure to prepare a surgical plan for the patient. Fewer or additional steps than those listed below may be implemented within the scope of the present disclosure, and the order of the steps listed is not intended to limit the present disclosure. The system 10 may be configured to execute each of the steps of the method 112 via any of its associated computing devices and modules. In an exemplary implementation, one or more computing devices 40 of the client computer 14 may be programmed to execute the method 112. However, other implementations are also contemplated within the scope of the present disclosure.

[0189] Image data of a bone or joint of a patient target may be received at step 114. The image data may be received directly from the imaging device 16 or may be obtained by accessing a record or entry associated with the patient from the patient profile database 64.

[0190] A 3D model of the target bone or joint may be generated in step 116. Planning environment 28 of computing device 40 may incorporate and / or interface with one or more modeling packages, such as a computer-aided design (CAD) package, to render the 3D model of the target bone or joint.

[0191] Next, at step 118, the computing device 40 may query the anatomical configuration classification database 70 to find bone models stored therein that have similar anatomical configuration classifications. The anatomical configuration classification that is closest to the anatomical structure encompassed by the 3D model may then be assigned to the 3D model at step 120 and displayed on the range of motion user interface of the computing device 40 at step 122. As part of displaying the anatomical configuration classifications, a confidence level indicator may be displayed within the range of motion user interface to visually indicate the similarity between the assigned anatomical configuration classification and the anatomical structure being analyzed. The confidence level indicator may be displayed as a percentage or any other visual indicator.

[0192] The range of motion database 68 may be queried at step 124 to obtain range of motion data associated with the assigned anatomical configuration classification. The range of motion data associated with the assigned anatomical configuration classification, including information such as angle arc and impact mode, may be displayed on a range of motion user interface at step 126.

[0193] At step 128, the surgeon or other staff user of system 10 may be queried to select the patient's desired activity of daily living goal. The positioning of the implant model may be automatically adjusted relative to the bone model based on the activity of daily living selected at step 130. System 10 may then output a recommended implant size / type and position and orientation to satisfy the activity of daily living selected at step 132.

[0194] The surgeon may be prompted to modify the recommended implant type, positioning, and / or orientation according to his / her clinical judgment at step 134. The method 112 may end at step 136 in response to receiving the surgeon's approval of the surgical plan. As part of this step, a comparison of the simulated range of motion stored in the ROM database 68 and the range of motion achieved by the surgeon's planned position and orientation may be presented to the user within the graphical user interface. This step may further include informing the surgeon within the graphical user interface of any potential impact the proposed changes may have based on past surgical outcome data associated with previous patients having similar anatomical configuration classifications.

[0195] 10 illustrates an exemplary range of motion user interface 105 that may be provided during the method 112 discussed above. The range of motion user interface 105 may be presented within the planning environment 28, for example.

[0196] The range of motion user interface 105 may include a range of motion dashboard 107, a display window 109, and a control panel 111. The range of motion dashboard 107 may present various range of motion data to the user. The range of motion dashboard 107 may include a number of selectable buttons 113 related to basic joint motion expectations for the patient. Basic joint motion expectations that may be represented by the buttons 113 may include, but are not limited to, desired post-operative range of motion for abduction, adduction, external rotation, internal rotation, extension, flexion, external rotation combined with 60° abduction, and internal rotation combined with 60° abduction.

[0197] The range of motion dashboard 107 may further include a bar graph 115 to illustrate the range of motion data for each of the underlying joint motion expectations. For example, the bar graph 115 may provide a visual display of the range of motion achieved for a selected underlying joint motion expectation for one or more AMCs that are closest to the patient's anatomy for which the surgical plan is being created.

[0198] The viewing window 109 may include a 3D window 117 and multiple 2D windows 119. A virtual bone model 121 of the patient's anatomy may be displayed within the 3D window 117 and the 2D window 119. The positioning of both virtual guide pins 123 and virtual implants 125 required to achieve the desired joint motion expectations may be displayed relative to the virtual bone model 121 to provide the user with information on how best to approach the planned surgery.

[0199] The display window 109 may be manipulated using the control panel 111. For example, the control panel 111 may include a number of toggles, buttons, sliders, etc. that allow the user to modify various settings, such as the positioning of the virtual guide pins 123 and / or virtual implants 125 relative to the virtual bone model 121. In one embodiment, the back sheet volume 127 and a color-coded back sheet map 129 are provided on the display window 109 and may be automatically updated as adjustments are made to the virtual positions of the virtual guide pins 123 and virtual implants 125 relative to the virtual bone model 121. The information presented in the display window 109 may also be automatically updated as a user page through each of the buttons 113.

[0200] FIG. 11 illustrates generally another method 138 for planning an orthopaedic surgical procedure for a respective patient using the system 10. The method 138 may be implemented as part of a surgical planning procedure to prepare a surgical plan for the patient. Fewer or additional steps than those listed below may be implemented within the scope of the present disclosure, and the order of the steps listed is not intended to limit the present disclosure. The system 10 may be configured to execute each of the steps of the method 138 via any of its associated computing devices and modules. In an exemplary implementation, one or more computing devices 40 of the client computer 14 may be programmed to execute the method 138. However, other implementations are also contemplated within the scope of the present disclosure.

[0201] Image data of a bone or joint of a patient target may be received at step 140. The image data may be received directly from the imaging device 16 or may be obtained by accessing a record or entry associated with the patient from the patient profile database 64.

[0202] A 3D model of the target bone or joint may be generated in step 142. Planning environment 28 of computing device 40 may incorporate and / or interface with one or more modeling packages, such as a computer-aided design (CAD) package, to render the 3D model of the target bone or joint.

[0203] Next, at step 144, the computing device 40 may query the anatomical configuration classification database 70 to find bone models stored therein that have an anatomical configuration classification similar to that of the patient's bone or joint. The anatomical configuration classification that is closest to the anatomical structure encompassed by the 3D model may then be assigned to the 3D model at step 146 and displayed on the surgical outcome user interface of the computing device 40 at step 148. As part of displaying the anatomical configuration classification, a confidence level indicator may be displayed within the graphical user interface to visually indicate the similarity between the assigned anatomical configuration classification and the anatomical structure being analyzed. The confidence level indicator may be displayed as a percentage or any other visual indicator.

[0204] The surgical outcome database 66 may be queried at step 150 to obtain the surgical outcome data most relevant to the assigned anatomical configuration classification. The surgical outcome data associated with the assigned anatomical configuration classification may be displayed on a surgical outcome user interface at step 152. The surgical outcome data displayed to the user may be automatically updated in response to a user prompt, such as when the user changes the planned procedure type.

[0205] In one embodiment, the surgical outcomes database 66 may be queried to find previous surgeries involving patients with average bone density comparable to the estimated average bone density of the bone associated with the patient's anatomy. This comparison may be used, for example, to recommend a particular surgical implant that is incompatible with the average bone density of the bone under study.

[0206] Next, at step 154, one or more survival prediction indexes may be determined utilizing data from the surgical outcomes database 66 for equivalent anatomical configuration classifications and a number of variables associated with the surgical plan for operating on the patient. The variables may include factors such as surgical implant type, surgical implant size, surgical implant orientation, surgical procedure type, surgical implant back seat configuration, fastener orientation, or any combination thereof. The variables are inputs to the system 10 that may be selected by the surgeon or staff user within the surgical outcomes user interface.

[0207] The determined survival prediction index may be displayed on the surgical outcome user interface at step 156. Each survival prediction index may represent a percentile of the confidence level that the surgical plan will result in a successful surgical outcome for at least a predetermined time. For example, based on the data of the comparable anatomical configuration classification and relevant variables selected / set by the surgeon, the system 10 may determine and display a three-year postoperative survival prediction index of 40% for a comparable patient undergoing a standard total shoulder arthroplasty and a three-year postoperative survival prediction index of 85% for a comparable patient undergoing a reverse shoulder arthroplasty, thus indicating to the surgeon that a more successful patient outcome is likely to be obtained by performing a reverse shoulder arthroplasty rather than a standard total shoulder arthroplasty.

[0208] After displaying the displayed survival prediction index at step 156, the system 10 may prompt the surgeon to make any corrections to the variables associated with the current surgical plan at step 158. If corrections are received as inputs to the system 10, an updated survival prediction index may be displayed at step 160.

[0209] System 10 may output a recommended procedure type, implant size / type, and implant position / orientation to best match the equivalent anatomical configuration classification at step 162. The surgeon may be prompted to modify the recommended implant type, positioning, and / or orientation according to his or her clinical judgment at step 164. Method 138 may end after receiving the surgeon's approval of the surgical plan at step 166.

[0210] 12 illustrates an exemplary surgical outcome user interface 141 that may be provided during the method 138 discussed above. The surgical outcome user interface 141 may be presented within the planning environment 28, for example.

[0211] The surgical outcome user interface 141 may include a graphical list 143 for displaying the anatomical configuration classifications 80 that are most similar to the anatomical configuration classification of the patient's bone or joint, a display window 145, and a control panel 147.

[0212] The graphical list 143 may include a graph 149 of ASES score versus time for each of the listed equivalent anatomical configuration classifications 80. Although two anatomical configuration classifications 80 are shown listed in FIG. 12, the graphical list 143 may provide a greater or lesser number of anatomical configuration classifications 80 within the scope of this disclosure.

[0213] The graphical list 143 may further include a confidence level indicator 151 that may be displayed adjacent to each equivalent anatomical configuration classification 80. The confidence level indicator 151 may be a percentage or any other visual indicator to visually indicate the similarity between the assigned anatomical configuration classification and the anatomical structure being analyzed. A user may select a desired equivalent anatomical configuration classification 80 using, for example, the input selector 153.

[0214] The viewing window 145 may include a 3D window 155 and multiple 2D windows 157. A virtual bone model 159 of the patient's anatomy may be displayed within the 3D window 155 and the 2D window 157. Virtual guide pins 161 and virtual implants 163 associated with the selected equivalent anatomical configuration classification 80 may be displayed against the virtual bone model 159 to provide the user with information about how previous surgeries have been performed on patients having the equivalent anatomical configuration classification 80.

[0215] The viewing window 145 may be manipulated using a control panel 147. For example, the control panel 147 may include a number of toggles, buttons, sliders, etc. that allow a user to modify various settings, such as the positioning of the virtual guide pins 161 and / or virtual implants 163 relative to the virtual bone model 159. In one embodiment, the back sheet volume 165 and a color-coded back sheet map 167 may be displayed on the viewing window 145 and automatically updated as adjustments are made to the virtual positions of the virtual guide pins 161 and virtual implants 163 relative to the virtual bone model 159.

[0216] The surgical outcomes user interface 141 may further include a schedule consultation button 199. A user may press or otherwise actuate the schedule consultation button 199 to arrange a consultation with a surgeon who performed a previous procedure for a comparable anatomical configuration classification 80. When the schedule consultation button 199 is actuated, the user and the associated surgeon may be presented with a series of prompts for coordinating and conducting the consultation. The consultation may be conducted via chat room, telephone, video conference, etc. If desired, the identity of one or both of the requesting surgeon and consulting surgeon may be kept confidential during the consultation.

[0217] FIG. 13A illustrates generally another method 168 for planning an orthopedic surgical procedure for a respective patient using the system 10. The method 168 may be implemented as part of a surgical planning procedure to prepare a surgical plan for the patient. Fewer or additional steps than those listed below may be implemented within the scope of the present disclosure, and the order of the steps listed is not intended to limit the present disclosure. The system 10 may be configured to execute each of the steps of the method 168 via any of its associated computing devices and modules. In an exemplary implementation, the computing device 40 of the host computer 12 may be programmed to execute the method 168. However, other implementations are also contemplated within the scope of the present disclosure.

[0218] Method 168 may begin at step 170 in response to receiving a pre-operative surgical plan approved by a respective surgeon. Surgeon profile database 65 may then be queried at step 172 for data regarding the surgeon's previous surgeries planned using system 10 for the procedure indicated by the approved pre-operative surgical plan. The data analyzed from surgeon profile database 65 may include the types and amounts of implants actually used in the surgeon's previous surgeries, as well as the types and amounts of implants included as part of the pre-operative surgical plan for each of the surgeon's relevant previous surgeries.

[0219] At step 174, the system 10 may determine, for example, whether the surgeon has deviated from his / her past preoperative surgical plan by less than a predetermined percentage of his / her previous surgical procedure based on a comparison of the preoperative and postoperative data analyzed at step 172. In some implementations, the predetermined percentage may be defined as 5% of the previous surgical procedure. However, other thresholds may be established within the scope of the present disclosure. In one embodiment, a "deviation" is presumed to have occurred when the surgeon changes a pre-planned procedure type, changes a pre-planned implant type, or uses a size deviation of more than one size during a previous surgical procedure.

[0220] If a YES flag is returned at step 174, a first surgical kit that includes only the implants and instruments necessary to perform the approved pre-operative surgery may be recommended at step 176. Alternatively, if a NO flag is returned at step 174, a second surgical kit that includes a greater number of implants and instruments than the first surgical kit may be recommended at step 178. An order to assemble the associated surgical kit may then be issued at step 180.

[0221] 13B illustrates an example deviation user interface 169 that may be provided during the method 168 discussed above. The deviation user interface 169 may be presented within the planning environment 28, for example.

[0222] The deviation user interface 169 may be configured to present various surgery-related information for a selected surgeon regarding how often the surgeon deviated from their past preoperative surgical plans. The deviation user interface 169 may provide a case list 171 of the surgeon's previous surgeries, and various bar graphs 173A-173F designed to communicate deviation-related information to the user. For example, bar graph 173A may illustrate the percentage of previous surgeries performed as planned, bar graph 173B may illustrate the percentage of implants planned during previous surgeries, bar graph 173C may illustrate planned vs. implanted implants, bar graph 173D may illustrate deviation types, bar graph 173E may illustrate different implant families used in previous surgeries, and bar graph 173F may illustrate different sizes of implants used during previous surgeries. Other deviation-related information may alternatively or additionally be communicated to the user via the deviation user interface 169.

[0223] FIG. 14 diagrammatically illustrates a method 182 for post-operatively updating one or more databases 38 associated with the system 10. The method 182 may be performed after creating a surgical plan for a patient using the system 10 and after implementing the surgical plan during the actual surgery. Fewer or additional steps than those listed below may be performed within the scope of the present disclosure, and the order of the steps listed is not intended to limit the present disclosure. The system 10 may be configured to perform each of the steps of the method 182 via any of its associated computing devices and modules. In an exemplary implementation, the computing device 40 of the host computer 12 may be programmed to perform the method 182. However, other implementations are still contemplated within the scope of the present disclosure.

[0224] The system 10 may receive post-operative patient outcome data from a user at step 184. In some implementations, the post-operative patient outcome data may be manually entered by a surgeon or other staff member after performing a surgical procedure intraoperatively on a patient according to a pre-operative surgical plan previously created within the system 10. In other implementations, the post-operative patient outcome data may be automatically communicated to the system 10 after performing a surgical procedure as part of a closed feedback loop that may be implemented, for example, via a neural network. The post-operative outcome data may include information such as the size and type of implants used during the currently completed surgical procedure, the location and orientation of used implants, implant failure data, data related to the achievement or non-achievement of pre-operative activities of daily living, etc.

[0225] An anatomical configuration classification 80 may be assigned to each anatomical structure associated with the post-operative patient outcome data, at step 186. This may be accomplished, for example, by querying the anatomical configuration classification database 70 to find bone models stored therein that have an anatomical configuration classification similar to that of the anatomical structure represented in the post-operative patient outcome data.

[0226] At step 188, the surgical outcomes database 66 may be updated with information contained within the post-operative patient outcome data. For example, the surgical outcomes database 66 may be updated with the size and type of implants used during the currently completed surgical procedure, the location and orientation of used implants, and the like.

[0227] The size, type, location, and orientation of the implants indicated in the post-operative patient outcome data may be entered into the range of motion database 68 at step 190. One or more motion simulations may then be performed for the anatomical structures and implants associated with the post-operative patient outcome data at step 192. Contact or collision points may be identified at step 194 to identify range of motion end points for each range of motion simulation performed. The angular arc and collision mode (e.g., implant-to-implant, implant-to-bone, bone-to-bone, etc.) for each contact point may be recorded at step 196.

[0228] The implant's center of rotation associated with the post-operative patient outcome data may be adjusted at step 198. At step 200, the implant's center of rotation may be adjusted relative to each bone model in multiple increments to record the angular arc and impact mode associated with the adjusted position. All range of motion data derived from the simulations performed at steps 190-200 may then be stored in range of motion database 68 at step 202.

[0229] The proposed surgical planning system and method of the present disclosure may be utilized to create and implement a surgical plan tailored to an individual patient, which may improve healing. The disclosed system and method may reduce the complexity in implementing a surgical plan, including reduced packaging and instrumentation. In certain implementations, the system and method may utilize a feedback loop to continually improve the recommendations provided during the development of a surgical plan. Thus, the proposed system and method provide improved capabilities compared to prior planning systems.

[0230] Although different non-limiting embodiments are illustrated as having particular components or steps, embodiments of the present disclosure are not limited to those particular combinations. Some of the components or features from any of the non-limiting embodiments can be used in combination with features or components from any of the other non-limiting embodiments.

[0231] It should be understood that like reference numerals identify corresponding or similar elements throughout the several views. Although particular component arrangements are disclosed and illustrated in these exemplary embodiments, it should be further understood that other arrangements can also benefit from the teachings of the present disclosure.

[0232] The foregoing description is illustrative and is not to be construed in any limiting sense. Those skilled in the art will appreciate that certain modifications may fall within the scope of the present disclosure. For these reasons, the following claims should be studied to determine the true scope and content of the present disclosure. [Explanation of symbols]

[0233] 10 Surgical Planning System 12 Host Computer 14 Client Computers 16 Imaging device 18 Memory Systems 20 Network 22 Client Interface 24 Peer-to-Peer Interface 26 Color Images 28 Planning Environment 30 Bone Model 32 Implant Model 34 Transmission Model 36 Surgical Planning 38 Database 40 Computing Devices 42 processors 44 Memory 46 Data Module 48 Display Module 50 Spatial Module 52 Comparison Module 54 entries 56 Graphical User Interface (GUI) 58 Display device 60 Display window 62 Object 64 Patient Profile Database 65 Surgeon Profile Database 66 Surgical Outcomes Database 68 Range of Motion Database 70 Anatomical Structure Classification Database 72 Statistical Shape Modeler 74 Image data 75 Statistical Shape Models 76 Mode 78 standard deviations 80 Anatomical composition classification 82 Bone Model 84 method 85 Survival Prediction Index 101 Range of Motion Modeler 105 Range of Motion User Interface 107 Range of Motion Dashboard 109 Display window 111 Control Panel 113 Button 115 Bar Graph 117 D Window 119 D Window 121 Virtual Bone Model 123 Virtual Guide Pin 125 Virtual Implants 127 Back sheet amount 129 Back seat map 141 Surgical Outcomes User Interface 143 Graphical List 145 Display window 147 Control Panel 149 Graphs 151 Confidence Level Indicator 153 Input Selector 155 D Window 157 D Window 159 Virtual Bone Model 161 Virtual Guide Pin 163 Virtual Implants 165 Back sheet amount 167 Back seat map 169 Deviation User Interface 171 Case List 173 Bar Graph 199 Consultation Schedule Button 761 First Mode 762 Second Mode 763 Third Mode 764 The Fourth Mode 765 Fifth Mode 766 The Sixth Mode 767 Seventh Mode 781~787 standard deviation

Claims

1. 1. A surgical planning system comprising: a processor configured to generate a plurality of anatomical configuration classifications based on a plurality of predetermined modes characterizing anatomical variations within a representative patient population and a plurality of standard deviations of anatomical variances within each of the plurality of predetermined modes; a storage system operatively connected to the processor and configured to store the plurality of anatomical configuration classifications; A surgical planning system comprising:

2. The surgical planning system of claim 1 , wherein the processor is configured to analyze the representative patient population within a statistical shape model.

3. The surgical planning system of claim 2 , wherein the processor is configured to identify the plurality of predetermined modes and / or a plurality of anatomical landmarks in the statistical shape model to characterize the anatomical variations.

4. The surgical planning system of claim 2 , wherein the processor is configured to identify a plurality of anatomical landmarks in the statistical shape model to characterize the anatomical variance.

5. The surgical planning system of claim 1 , wherein the plurality of predetermined modes includes a size, inclination, angle, or length associated with a bone or joint.

6. 2. The surgical planning system of claim 1, wherein the processor is configured to establish the plurality of standard deviations of the anatomical variance contained within each of the plurality of predetermined modes to verify percentile coverage of the representative patient population.

7. The surgical planning system of claim 6 , wherein the processor is configured to combine the plurality of standard deviations with the plurality of predetermined modes to establish the plurality of anatomical configuration classifications.

8. The surgical planning system of claim 7 , wherein the processor is configured to integrate the plurality of anatomical configuration classifications to represent variance within the representative patient population.

9. 9. The surgical planning system of claim 8, wherein the processor is configured to virtually position a surgical implant in each of the integrated anatomical configuration classifications to establish a default starting position and a default orientation for the surgical implant.

10. The surgical planning system of any of claims 1 to 9, wherein each of the plurality of anatomical configuration classifications is a numerical classification of an anatomical configuration of a bone or joint of the representative patient population.

11. 1. A computer-implemented surgical planning method comprising: identifying a plurality of predetermined modes within a statistical shape model of a representative patient population; establishing a plurality of standard deviations of the anatomical variance contained within each of the plurality of predetermined modes; generating, via a processor of a surgical planning system configured to interface with the statistical shape model, a plurality of anatomical configuration classifications based on the plurality of predetermined modes and the plurality of standard deviations of anatomical variance; storing the plurality of anatomical configuration classifications in a storage system of the surgical planning system; 1. A computer-implemented surgical planning method comprising:

12. The computer-implemented surgical planning method of claim 11 , wherein the plurality of predetermined modes characterize anatomical variations within the representative patient population.

13. The computer-implemented surgical planning method of claim 12, wherein the plurality of predetermined modes comprises sizes, inclinations, angles, or lengths associated with bones or joints of the representative patient population.

14. establishing the plurality of standard deviations of the anatomical variances; The computer-implemented surgical planning method of claim 11, further comprising verifying percentile coverage of the representative patient population.

15. generating the plurality of anatomical configuration classifications, The computer-implemented surgical planning method of claim 11 , comprising combining the plurality of standard deviations with the plurality of predetermined modes to establish the plurality of anatomical configuration classifications.

16. generating the plurality of anatomical configuration classifications, The computer-implemented surgical planning method of claim 15, comprising integrating the plurality of anatomical configuration classifications to represent variance within the representative patient population.

17. generating the plurality of anatomical configuration classifications, 17. The computer-implemented surgical planning method of claim 16, comprising virtually positioning a surgical implant in each of the integrated anatomical configuration classifications to establish a default starting position and a default orientation for the surgical implant.

18. The computer-implemented surgical planning method of claim 11 , wherein each of the plurality of anatomical configuration classifications is a numerical classification of an anatomical configuration of a bone or joint of the representative patient population.

19. receiving image data associated with a patient; generating a three-dimensional model of the patient's bone or joint based on the image data; and assigning one of the plurality of anatomical configuration classifications to the three-dimensional model of the bone or joint.

20. 20. The computer-implemented surgical planning method of claim 19, comprising querying a surgical outcomes database of the surgical planning system for previous surgical procedures with significantly comparable anatomical configuration classifications.

Images