WO2016118521A1 - Systems and methods for orthopedic analysis and treatment designs - Google Patents

Systems and methods for orthopedic analysis and treatment designs Download PDF

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Publication number
WO2016118521A1
WO2016118521A1 PCT/US2016/013949 US2016013949W WO2016118521A1 WO 2016118521 A1 WO2016118521 A1 WO 2016118521A1 US 2016013949 W US2016013949 W US 2016013949W WO 2016118521 A1 WO2016118521 A1 WO 2016118521A1
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Prior art keywords
model
module
implant
patient
treatment
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PCT/US2016/013949
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French (fr)
Inventor
Sok Gek LIM
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Advanced Ortho-Med Technology, Inc.
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Priority to CN201680004562.0A priority Critical patent/CN107106104B/en
Publication of WO2016118521A1 publication Critical patent/WO2016118521A1/en

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/40—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/40—ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/20—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
    • A61B2034/101—Computer-aided simulation of surgical operations
    • A61B2034/102—Modelling of surgical devices, implants or prosthesis
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
    • A61B2034/101—Computer-aided simulation of surgical operations
    • A61B2034/102—Modelling of surgical devices, implants or prosthesis
    • A61B2034/104—Modelling the effect of the tool, e.g. the effect of an implanted prosthesis or for predicting the effect of ablation or burring
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
    • A61B2034/101—Computer-aided simulation of surgical operations
    • A61B2034/105—Modelling of the patient, e.g. for ligaments or bones
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
    • A61B2034/108—Computer aided selection or customisation of medical implants or cutting guides

Definitions

  • Orthopedic treatments require extensive pre-treatment planning, whether for surgery or non-surgery treatments.
  • the invention disclosed here automates the precision treatment planning process through personalized procedure that takes into account each individual patient's orthopedic profiles and other related information. It provides an all- inclusive suite solution for physicians.
  • the invention has been implemented using patient information from different sources combined with 3D printing to facilitate patient/physician education and understanding and to provide precision treatment solutions for better patient care.
  • the system streamlines all aspects of orthopedic care: diagnosis, treatment planning and evaluation, pre-surgical planning, and post-treatment follow-up and evaluation for optimal clinical workflow.
  • One form of the present invention is a system for planning orthopedic treatments.
  • One basic embodiment of such system comprises two major components: a modeling module that constructs a 3D model of a body section relevant to the planned treatment, from radiographic images of the body section, and an analytical module that comprises the following analytical tools: (1) An interactive visualization tool that allows a user of the system to visualize and edit the 3D model, (2) a quantification tool for obtaining measurements of the 3D model relevant to the treatment, (3) a planning tool for generating a personalized surgery plan according to the measurements, and (4) an evaluation tool for evaluating the surgery plan using one or more biomechanical analyses.
  • the planning tool allows the modification of the surgery plan using the output of the evaluation tool.
  • the system comprises an implant design tool for designing implant models according to the measurements obtained from the patient's 3D models, an evaluation tool that allows the evaluation of the implant models using one or more biomechanical analyses, and a planning tool that allows the modification of the implant models using the output of the evaluation tool.
  • One embodiment of the invention comprises an evaluation tool for non-surgical treatment evaluation and post-treatment evaluation.
  • the system may also comprise other analytical tools including: (1) a diagnostic tool which renders orthopedic diagnosis based on the radiographic images and other related information according to predefined criteria, and (2) a construction tool which allows the construction of a physical object based on a 3D model of the patient or an implant model.
  • the system may also comprise a disease module which allows the user to select a predefined workflow for a specific orthopedic disease, which automatically invokes one or more analytical tools in a predefined order suitable for treatment planning for the disease.
  • Fig, 1 depicts a high-level system structure of an embodiment of the present invention.
  • Fig. 2 shows one form of implementation for the acquisition component of the present invention.
  • Fig. 3 illustrates the exemplary components of the 3D modeling function of the present invention.
  • Fig. 4 illustrates the disease type thread and analysis functionality thread of a particular implementation of the present invention.
  • FIG. 5 illustrates the exemplary parts of the visualization component of the present invention, Interactive Visualization 320
  • Fig. 6 shows the exemplary parts of an embodiment of the surgery planning component of the present invention, Pre-surgical Planning 330.
  • Fig. 7 shows the exemplary parts of an embodiment of the evaluation component of the present invention, Biomechanics Analysis 340.
  • Fig. 8 shows the exemplary parts of an embodiment of the implant design component of the present invention. Personalization 350.
  • Fig. 9 shows the exemplar ⁇ ' parts of an embodiment of the construction component of the present invention, 3D Printing 360.
  • Fig. 10 shows the exemplar ⁇ - parts of the output component of the present invention.
  • Fig. 11 illustrates one embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION
  • the present invention is an interactive and quantitative analytical system that provides orthopedic doctors with automatic or semi-automatic tools for rendering patient- specific treatment decisions and solutions.
  • the system 100 in Fig. 1 illustrates an embodiment for the components of the present inventions.
  • the system consists of an Acquisition module 110 for acquiring orthopedic images, an Archive module 120, and a Patient Record module 130 for handling the patient input information for further processing. Pre-processing of the input information is accomplished through the Related Input Information module 140, the Radiographic Images module 150, and the Modeling module 160,
  • the personalized decision and treatment solutions are based on the User Selection module 170 from one of the two threads, the Disease Type Thread 173 and the Analysis Functionality Thread 175.
  • the outputs are generated from the Output 180 mechanism and the Report module 190.
  • the user may select an orthopedic disease, for example, from the Disease Type Thread 173, to initiate an interactive workflow based on the disease type that has been developed to ensure optimal clinical workflow.
  • Each disease type selection corresponds typically to a workflow stored in a workflow library.
  • the predefined workflow automatically invokes one or more analytical functions or tools in the analytical module in a suitable order for the disease.
  • the user may select a function or tool from the Analysis Functionality Thread 175 to perform a specific analysis for different types of diseases.
  • the physicians can make a selection from either thread to reach a personalized decision and treatment solution for the patient.
  • the physicians can leverage from Output 180 to facilitate physician/patient education and understanding, and also precision treatment solution.
  • the Report module 190 will generate reports and archive the data using the Archive 120 and the Patient Record 130 mechanism.
  • the report functionalities can also be designed to be a tool of the analytical module.
  • Fig. 2 illustrates the schematic of an exemplary embodiment depicting the general approach for accessing and retrieving patient information from different sources for further processing.
  • the embodiment consists of three major components: the Acquisition 110, Archive 120, and Patient Record 130.
  • the Acquisition 110 is to acquire patient input data for further processing.
  • Patient input data such as medical images are acquired from different acquisition modalities including, but not limited to, X-rays, CT, MR imaging, functional MRI, perfusion MRI, bone density measurement and electromyography (EMG). Patient data may also be retrieved from archives or other databases.
  • the Archive 120 may comprise Internet Cloud 123 storage, a local Offline archive 125, and/or a picture archiving and communication system (PACS) 127 where patient radiographic information can be retrieved and archived for analysis.
  • the physicians can also conduct collaborative research using the data from the Internet Cloud 123.
  • the Patient Record Module 130 may comprise a number of patient record systems, including for example Hospital Information System (HIS) 133, Electronic Medical Record (EMR) 135, Radiology Information System (RIS) 137, and/or Laboratory Information System (LIS) 139. Patient clinical data can be retrieved from one or more of these databases to assist in the analysis process. The data retrieval process may be facilitated using input devices such as Barcode Reader 131.
  • the Acquisition module can also facilitate the storage of new patient data generated by the system (e.g., a personalized 3D model or implant model) back to the patient databases.
  • Fig. 3 illustrates an exemplary embodiment for the Modeling module 160.
  • the Modeling module creates a 3D digital model 270 for a selected bony structure.
  • 3D model is used in this patent to refer to the 3D digital, computer, or virtual model of an orthopedic structure.
  • the 3D model can be automatically created by using the module Automatic Model Processing 210. For that purpose, the system automatically segments and labels the 3D model based on the radiographic images of the patient.
  • Segmenting here means the process that partitions a 2D image into different regions by delineating or contouring the region of interest (ROI) of the 3D model.
  • Labeleling means labeling the delineated regions that form the different parts of the structure of the 3D model.
  • the 3D model can also be semi-automatically created by using the module Semi- Automatic Model Processing 230, which allows the user to either select a ROI for the automatic segmentation or manually (with the aid of the system) segment the 2D images. For example, the system could project the 2D images onto a touch screen and the user could visually contour the bone segment using a stylus. After the system has completed the segmentation, the user can manually or automatically label the segment of the 3D model.
  • the 3D model so generated can be manually edited using the tools from Interactive Model Processing 250 and the module 3D model.
  • the Interactive Model Processing module is provided for users to ensure that the model that is constructed is realistic and accurate.
  • the module includes a set of editing tools for manual editing to refine the 3D model in a real-time interactive environment. This is achieved through the interplay between the Interactive Model Processing module and the 3D Model 270, with the latter module displaying the edited 3D model in real time. The process can be continued iteratively until satisfactory results are achieved.
  • the Interactive Model Processing module allows the editing of the 3D model in the 2D, 3D or higher dimensional space.
  • editing tools including, for examples without limitation, tools for adding or removing contours, connecting or disconnecting contours, editing points on the contours, auto-propagating curves, smoothing curves, and manual labeling.
  • the User Selection module 170 in Fig. 1 is an important workflow direction module.
  • Fig. 4 illustrates the various exemplary components of the module that may be selected by the user (i.e., physicians or clinicians) to perform various clinical workflows.
  • the Disease Type Thread 173 consists of a number of pre-determined clinical workflows, each of which has been designed for a specific disease, Orthopedic Disease 1 to Orthopedic Disease N, to provide personalized treatment solutions for patients. Examples of orthopedic disease including, but not limited to, Osteonecrosis, Osteoarthritis, different types of Fracture, and Scoliosis,
  • the pre-determined clinical workflow may include one or more analysis functionalities from Analysis Functionality Thread 175 and other customized functionalities specific for the disease.
  • the Analysis Functionality Thread enables physicians to select from a range of specific analysis tools including, but not limited to, Diagnosis 310, Interactive Visualization 320, Pre-surgieal Planning 330, Biomechanics Analysis 340, Personalization 350 and 3D Printing 360, which can be applied to patient information in order to perform certain specific analysis function(s) for certain patient's data or certain condition of the diseases.
  • specific analysis tools including, but not limited to, Diagnosis 310, Interactive Visualization 320, Pre-surgieal Planning 330, Biomechanics Analysis 340, Personalization 350 and 3D Printing 360, which can be applied to patient information in order to perform certain specific analysis function(s) for certain patient's data or certain condition of the diseases.
  • the Diagnosis tool 310 in Fig. 4 is a 2D diagnostic tool for detecting and differentiating orthopedic abnormalities associated with various diseases. Such diagnosis is based on the patient's imaging data retrieved from Radiographic Images 150, with or without other clinical data from Related Input Information 140.
  • Various kinds of technology tools are used to detect and highlight diseased regions of bone tissue, which is referred to as the "conspicuous regions.” Examples of such technology tools include artificial intelligence algorithms such as artificial neural networks for computer vision, machine learning, and statistical pattern recognition and digital image processing. These technologies are employed to extract the characteristics and features of the conspicuous regions associated with a bone disease for diagnosis purposes. Either the whole image or a selected ROI from the image may be used by the Diagnosis tool.
  • the conspicuous regions can be permanently saved in Archive 120 and/or Patient Record 130; and may be used for future machine diagnostics after they have been approved by the physicians as disease-related abnormalities.
  • the Interactive Visualization tool 320 in Fig. 4 allows the users to perform realtime interactive visualization and editing of 3D models and/or 2D images.
  • An exemplary embodiment for the Interactive Visualization tool is illustrated in Fig. 5. It includes a Manipulation module 470, which allows the visualization and manipulation of both 2D images retrieved from Radiographic Image 150 and various 3D models such as 3D Surface Rendered Model 410, 3D Anatomy Model 430 and 3D Volume Rendered Model 450. It also allows the user to correlate the 3D models to the 2D images.
  • the Interactive Model Editing module 490 further allows editing of the 3D models, if needed, for various purposes.
  • Surgical planning is an important aspect of the present invention, an embodiment of which is the Pre-surgical Planning tool 330 in Fig. 4.
  • Pre-Surgical Planning 330 is a platform for real-time interactive pre-surgical planning.
  • Fig. 6 illustrates an exemplary embodiment of the Pre-Surgical Planning Module 330, which includes Modeling 160, Quantification 500, Automatic Planning 510, Interactive Personalized Planning 520 and Biomechanics Analysis 340.
  • the surgical planning module contains a quantification tool 500 which extracts quantitative measurements required for the surgery from the 3D models for the patient generated by Modeling 160.
  • quantification tool can be an independent tool that can be utilized by the surgical planning and other tools.
  • the quantitative measurements and the 3D models are then used for the Automatic Planning 510.
  • the Automatic Planning 510 generates the pre-surgical plan according to the standard care protocol.
  • the Interactive Personalized Planning 520 provides the interactive editing tools for the users to modify the pre-surgical plan to a more precise personalized pre-surgical plan according to the patient specific data.
  • Biomechanics Analysis 340 is to provide evaluation for the pre-surgical plan. This enables the physician to evaluate the precision of the surgery for example the stability criteria of the THE. surgery (see below).
  • Automatic Planning tool 510 in Fig. 6 is a planning tool based on the 3D models built by the Modeling module 160 and the quantitative measurements extracted by Quantification 500, It then automatically generates a pre-surgical plan according to the standard care protocol. For example, in a particular embodiment for total hip replacement (THR) surgery, a precise match is required between the implants and the patient's anatomical structure, in terms of type and size of the implants, the positioning and orientation of the components, and the leg length and other size measurements of the patient. For a THR surgery, Automatic Planning 510 takes the 3D model of the patient's hip and leg segment from Modeling 160 and extracts the relevant quantitative measurements of the patient based on the 3D model.
  • THR total hip replacement
  • the automatic planning tool then generates the pre-surgical plan for the THR, which includes the standard implant model and the surgery procedure, using the standard THE. protocol. Then, the physician user of the system uses the Interactive Personalized Planning 520 to inspect and, if desired, to edit the pre-surgical plan to generate a precise and personalized pre-surgical plan for the patient.
  • the precision personalized pre- surgical plan, especially the implant model, are then simulated and tested using the Biomechanics Analysis 340.
  • the Biomechanics Analysis tool may generate recommendations for modifications for the pre-surgical plan based on the biomechanical tests.
  • the feedback from the Biomechanics Analysis 340 may be used by the Interactive Personalized Planning 520 to further modify the personalized pre-surgical plan.
  • Biomechanics Analysis tool 340 in Fig. 4 is an embodiment of the evaluation tool which evaluates the soundness of the treatment plans generated by the system, including the implant designs.
  • the kind of analyses employed by Biomechanics Analysis 340 may include orthopedic stress analysis of the bone/prosthesis structures, orthopedic fixation devices and other tissues.
  • Fig. 7 illustrates an exemplary embodiment for Biomechanics Analysis 340.
  • the Numerical Analysis 610 function may include, among other tools, Finite Element Analysis (FEA), which evaluates structural stability of the bone anatomy where the stress distributions are used to compare with the material property of the bone. Different numerical analysis approaches are used to assess the structural integrity of orthopedic implants.
  • FEA Finite Element Analysis
  • Numerical Analysis 610 can be used to assist surgical and nonsurgical treatment for the patients.
  • Numerical Analysis Model Library 630 is a library that stores the reference models, for example FEA reference models, to provide real-time analysis and evaluation for pre-surgical planning and personalized implant design.
  • Non- Surgical Treatment Evaluation 650 uses the evaluation outcome to assist in non-surgical treatment planning.
  • the physicians use FEA analysis, based on the patient's 3D model, to evaluate the condition of the patients, and based on the outcome to decide an appropriate non-surgical treatment, and to follow-up with before and after treatment evaluation. Post-treatment Evaluation 690.
  • the FEA stress and displacement distributions of the necrotic region can be used to predict the collapse of the femoral head for early stage Osteonecrosis, therefore, it can be used to assist in non-surgical treatment such as medications, taking weight off the joint, range-of-motion exercises and electrical stimulation.
  • Pre-surgical Planning Evaluation 670 provides interactive analysis to ensure the stability criteria of the pre-surgical planning from Pre-surgical Planning 330, together with the reference models from the Numerical Analysis Model Library 630 to achieve real-time analysis and evaluation. For example, the correct positioning of the acetabular cup ensures implant stability, and bearing surface wear and longevity.
  • Post-treatment Evaluation 690 provides the before and after treatment evaluation for both non-surgical and surgical treatment. This is to provide evaluation for follow-up to monitor the progress of the treatment outcome.
  • the analytical module of the invention may include an implant design tool for designing 3D models of personalized implants and surgical accessories such as guide plates.
  • the Personalization tool 350 in Fig. 4 is one form of embodiment of the personalized implant design tool .
  • the word "implant” is used broadly in the written description and the claims of this patent to cover an implant, a moid for an implant, a surgical accessory for an implant such as a guide plate, and a mold for such surgical accessor ⁇ ', unless otherwise specified.
  • Fig. 8 illustrates some exemplary components of Personalization 350. It takes the 3D Models generated by Modeling 160 to design personalized implant models. It may- include Standard Implant Selection 710, Personalized Implant Design 730, Personalized Qualification Process 750, Customized/Personalized Implant Model 770, and Customized/Personalized Guide Plate Model 790.
  • the patient specific 3D models are used by the Standard Implant Selection 710 to select the closest matched standard implant model. Then, the physician user of the system uses the Personalized Implant Design 730 to inspect and, if desired, to edit the standard implant model to generate a precise and personalized implant model for the patient.
  • Customized/Personalized Implant Model 770 generates a customized/personalized implant model and/or a mold thereof for 3D printing.
  • Customized/Personalized Guide Plate Model 790 allows users to create the guide-plate models (or molds thereof) for 3D printing which are to be used during surgery.
  • the process for generating customized/personalized implant models comprises the following steps: Standard Implant Selection 710 automatically selects the closest matched standard implant based on the type of surgery; a set of editing tools is provided to modify the standard implant to generate the customized/personalized implant model that best fits the 3D model of the specific patient via Personalized Implant Design 730; validating the customized/personalized implant model that meets the standard implant requirements through the Personalized Qualification Process 750.
  • the qualifying process may generate recommendations for modifications for the personalized implant design based on the testing outcome generated from testing such as biomechanical tests or other requirement tests.
  • the feedback from the testing outcome may be used by the Personalized Implant Design 730 to further modify the personalized implant design.
  • the implants include, for example, joint surgery implants, prostheses, pins, rods, screws, and plates.
  • the process for generating customized/personalized guide plate models comprises the following steps: ROI is selected for the surgery; the 3D stencil model is automatically generated from the patient's 3D model; a set of editing tools is provided to incorporate the pre-surgical planning from Pre-Surgical Planning 330 to the 3D stencil to generate the customized/personalized guide plate via Personalized Implant Design 730; validating the customized/personalized guide plate model that meet the stability requirements through the Personalized Qualification Process 750.
  • ROI is selected for the surgery
  • the 3D stencil model is automatically generated from the patient's 3D model
  • a set of editing tools is provided to incorporate the pre-surgical planning from Pre-Surgical Planning 330 to the 3D stencil to generate the customized/personalized guide plate via Personalized Implant Design 730; validating the customized/personalized guide plate model that meet the stability requirements through the Personalized Qualification Process 750.
  • the qualifying process may generate recommendations for modifications for the personalized guide plate design based on the testing outcome generated from testing such as biomechanical tests or other requirement tests.
  • the feedback from the testing outcome may be used by the Personalized Implant Design 730 to further modify the personalized guide plate design.
  • guide plates include guide plates for pedicle screw placement with the positioning and angle of the screws from Pre-Surgical Planning 330.
  • the 3D Printing module 360 is an embodiment of a physical construction tool responsible for constructing physical models corresponding to virtual models generated from Personalization 350.
  • Fig. 9 illustrates exemplary components for 3D Printing 360, wherein a 3D printer is used to produce the Customized/Personalized Implant 810, Customized/Personalized Implant Mold 830, Customized/Personalized Guide Plate Mold 850 and/or 3D Model Mold 870 to be used before, during, or after the treatment.
  • Other embodiments for the physical construction function may include computerized numerical control (CNC) machining and injection molding.
  • CNC computerized numerical control
  • Fig. 10 illustrates the various embodiments of the 2D, 3D Output 180.
  • the 2D 181 provides output in Digital 182 form and/or Hardcopy 183.
  • the 3D 184 includes, but is not limited to, 3D display with/without 3D glasses 185, Google Glasses 186, Virtual Display 187, Tactile Display 188 and 3D Printing Model 189.
  • the 2D and 3D output can be displayed on hardware including, but not limited to, Monitor Display 190, Tablet/ Phone 191, Smart Device 192.
  • 3D Glasses 185 and Google Glasses 186 are merely examples of wearable technologies that may be deployed for the display module of the invention.
  • Fig.11 illustrates the overall operation of the system according to one embodiment of the invention. It begins with the physician selecting a specific disease from User Selection Thread 170. The physician ensures the accuracy of the 3D model through the Interactive Visualization 320 and prints the 3D Model Mold 870 if needed. Diagnosis is performed via Diagnosis 310 and/or combined with 3D Model Mold 870 for treatment planning. It illustrates how the system, based on the different diagnosed stages, decides where surgery is or is not required.
  • the System further analyzes the conditions using Biomechanics Analysis 340 and the physicians can come out with Targeted Treatment 935 and follow-up with Post-treatment Follow-up 940 based on the evaluation. There may be a number of follow-ups before the treatment is completed.
  • the physicians utilize Pre-surgical Planning 330 for pre-surgical planning and Personalization 350 for personalized implant and/or personalized guide-plate followed by Biomechanics Analysis 340 to evaluate the implant fitting based on the criteria specified by the users.
  • the 3D Printing 360 mechanism utilizes the personalized model from Personalization 350 for printing the necessary Customized/Personalized Implant 810, and/or Customized/Personalized Guide Plates Mold 850 for Surgery 945.
  • Post-surgery follow-up 950 might involve evaluation using Biomechanics Analysis 340. If revision surger is required after Post-surgery Follow-up 950 then repeats the procedure again.

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Abstract

The present invention covers systems and methods for improving efficiency of treatment planning for orthopedic diseases. The invention provides various analytical tools. One such analytical tool allows design of personalized treatment plan using quantitative measurements of the relevant orthopedic structures as well as related information about the patient, where the quantitative measurements are obtained from 3D models of the orthopedic structures constructed using radiographic images of the structures. Another analytical tool allows the design of personalized implant models based on the patient's measurements. The personalized treatment plan and implant models can be evaluated by using another analytical tool based on biomechanical analyses. The evaluation results can be used by the system to modify and improve the treatment plan and implant models. A construction tool can be used to construct implant models by, for example, 3D printing. The system also has the capacity to generate reports for treatment planning.

Description

SYSTEMS AND METHODS FOR ORTHOPEDIC ANALYSIS AND TREATMENT
DESIGNS
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This Application claims priority to U.S. provisional patent application No. 62107296 filed on January 23, 2015 in United State Patent and Trademark Office (USPTO).
BACKGROUND OF INVENTION
[0002] Orthopedic treatments require extensive pre-treatment planning, whether for surgery or non-surgery treatments. The invention disclosed here automates the precision treatment planning process through personalized procedure that takes into account each individual patient's orthopedic profiles and other related information. It provides an all- inclusive suite solution for physicians. The invention has been implemented using patient information from different sources combined with 3D printing to facilitate patient/physician education and understanding and to provide precision treatment solutions for better patient care. The system streamlines all aspects of orthopedic care: diagnosis, treatment planning and evaluation, pre-surgical planning, and post-treatment follow-up and evaluation for optimal clinical workflow.
BRIEF SUMMARY OF THE INVENTION
[0003] One form of the present invention is a system for planning orthopedic treatments. One basic embodiment of such system comprises two major components: a modeling module that constructs a 3D model of a body section relevant to the planned treatment, from radiographic images of the body section, and an analytical module that comprises the following analytical tools: (1) An interactive visualization tool that allows a user of the system to visualize and edit the 3D model, (2) a quantification tool for obtaining measurements of the 3D model relevant to the treatment, (3) a planning tool for generating a personalized surgery plan according to the measurements, and (4) an evaluation tool for evaluating the surgery plan using one or more biomechanical analyses. In this basic embodiment of the invention, the planning tool allows the modification of the surgery plan using the output of the evaluation tool. [0004] In another embodiment, the system comprises an implant design tool for designing implant models according to the measurements obtained from the patient's 3D models, an evaluation tool that allows the evaluation of the implant models using one or more biomechanical analyses, and a planning tool that allows the modification of the implant models using the output of the evaluation tool.
[0005] One embodiment of the invention comprises an evaluation tool for non-surgical treatment evaluation and post-treatment evaluation. The system may also comprise other analytical tools including: (1) a diagnostic tool which renders orthopedic diagnosis based on the radiographic images and other related information according to predefined criteria, and (2) a construction tool which allows the construction of a physical object based on a 3D model of the patient or an implant model.
[0006] The system may also comprise a disease module which allows the user to select a predefined workflow for a specific orthopedic disease, which automatically invokes one or more analytical tools in a predefined order suitable for treatment planning for the disease.
[0007] The present invention also covers various methods for computer-assisted treatment planning for orthopedic ailments, and many other variations that this summary does not cover. The exact scope of the invention is set forth in the claims.
BRIEF DESCRIPTION OF FIGURES
[0008] Fig, 1 depicts a high-level system structure of an embodiment of the present invention.
[0009] Fig. 2 shows one form of implementation for the acquisition component of the present invention.
[0010] Fig. 3 illustrates the exemplary components of the 3D modeling function of the present invention.
[0011] Fig. 4 illustrates the disease type thread and analysis functionality thread of a particular implementation of the present invention.
[0012] Fig. 5 illustrates the exemplary parts of the visualization component of the present invention, Interactive Visualization 320
[0013] Fig. 6 shows the exemplary parts of an embodiment of the surgery planning component of the present invention, Pre-surgical Planning 330.
[0014] Fig. 7 shows the exemplary parts of an embodiment of the evaluation component of the present invention, Biomechanics Analysis 340. [0015] Fig. 8 shows the exemplary parts of an embodiment of the implant design component of the present invention. Personalization 350.
[0016] Fig. 9 shows the exemplar}' parts of an embodiment of the construction component of the present invention, 3D Printing 360.
[0017] Fig. 10 shows the exemplar}- parts of the output component of the present invention.
[0018] Fig. 11 illustrates one embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION
[0019] The present invention is an interactive and quantitative analytical system that provides orthopedic doctors with automatic or semi-automatic tools for rendering patient- specific treatment decisions and solutions. The system 100 in Fig. 1 illustrates an embodiment for the components of the present inventions. The system consists of an Acquisition module 110 for acquiring orthopedic images, an Archive module 120, and a Patient Record module 130 for handling the patient input information for further processing. Pre-processing of the input information is accomplished through the Related Input Information module 140, the Radiographic Images module 150, and the Modeling module 160, The personalized decision and treatment solutions are based on the User Selection module 170 from one of the two threads, the Disease Type Thread 173 and the Analysis Functionality Thread 175. The outputs are generated from the Output 180 mechanism and the Report module 190.
[0020] The user may select an orthopedic disease, for example, from the Disease Type Thread 173, to initiate an interactive workflow based on the disease type that has been developed to ensure optimal clinical workflow. Each disease type selection corresponds typically to a workflow stored in a workflow library. The predefined workflow automatically invokes one or more analytical functions or tools in the analytical module in a suitable order for the disease. Alternatively, the user may select a function or tool from the Analysis Functionality Thread 175 to perform a specific analysis for different types of diseases. The physicians can make a selection from either thread to reach a personalized decision and treatment solution for the patient. The physicians can leverage from Output 180 to facilitate physician/patient education and understanding, and also precision treatment solution. The Report module 190 will generate reports and archive the data using the Archive 120 and the Patient Record 130 mechanism. The report functionalities can also be designed to be a tool of the analytical module.
[0021] Fig. 2 illustrates the schematic of an exemplary embodiment depicting the general approach for accessing and retrieving patient information from different sources for further processing. The embodiment consists of three major components: the Acquisition 110, Archive 120, and Patient Record 130. The Acquisition 110 is to acquire patient input data for further processing. Patient input data such as medical images are acquired from different acquisition modalities including, but not limited to, X-rays, CT, MR imaging, functional MRI, perfusion MRI, bone density measurement and electromyography (EMG). Patient data may also be retrieved from archives or other databases. The Archive 120 may comprise Internet Cloud 123 storage, a local Offline archive 125, and/or a picture archiving and communication system (PACS) 127 where patient radiographic information can be retrieved and archived for analysis. The physicians can also conduct collaborative research using the data from the Internet Cloud 123. The Patient Record Module 130 may comprise a number of patient record systems, including for example Hospital Information System (HIS) 133, Electronic Medical Record (EMR) 135, Radiology Information System (RIS) 137, and/or Laboratory Information System (LIS) 139. Patient clinical data can be retrieved from one or more of these databases to assist in the analysis process. The data retrieval process may be facilitated using input devices such as Barcode Reader 131. The Acquisition module can also facilitate the storage of new patient data generated by the system (e.g., a personalized 3D model or implant model) back to the patient databases.
[0022] Fig. 3 illustrates an exemplary embodiment for the Modeling module 160. The Modeling module creates a 3D digital model 270 for a selected bony structure. Unless otherwise specified, the term "3D model" is used in this patent to refer to the 3D digital, computer, or virtual model of an orthopedic structure. The 3D model can be automatically created by using the module Automatic Model Processing 210. For that purpose, the system automatically segments and labels the 3D model based on the radiographic images of the patient. "Segmenting" here means the process that partitions a 2D image into different regions by delineating or contouring the region of interest (ROI) of the 3D model. "Labeling" means labeling the delineated regions that form the different parts of the structure of the 3D model. There are various segmentation algorithms that are used for the purpose of the present invention, including for example thresholding, region growing methods, clustering algorithms, edge detection, and model based segmentation. Labeling is achieved through connected-component analysis that uses different optimization techniques, [0023] The 3D model can also be semi-automatically created by using the module Semi- Automatic Model Processing 230, which allows the user to either select a ROI for the automatic segmentation or manually (with the aid of the system) segment the 2D images. For example, the system could project the 2D images onto a touch screen and the user could visually contour the bone segment using a stylus. After the system has completed the segmentation, the user can manually or automatically label the segment of the 3D model.
[0024] If necessary or desirable, the 3D model so generated can be manually edited using the tools from Interactive Model Processing 250 and the module 3D model. The Interactive Model Processing module is provided for users to ensure that the model that is constructed is realistic and accurate. The module includes a set of editing tools for manual editing to refine the 3D model in a real-time interactive environment. This is achieved through the interplay between the Interactive Model Processing module and the 3D Model 270, with the latter module displaying the edited 3D model in real time. The process can be continued iteratively until satisfactory results are achieved.
[0025] The Interactive Model Processing module allows the editing of the 3D model in the 2D, 3D or higher dimensional space. There are a variety of editing tools including, for examples without limitation, tools for adding or removing contours, connecting or disconnecting contours, editing points on the contours, auto-propagating curves, smoothing curves, and manual labeling.
[0026] The User Selection module 170 in Fig. 1 is an important workflow direction module. Fig. 4 illustrates the various exemplary components of the module that may be selected by the user (i.e., physicians or clinicians) to perform various clinical workflows. The Disease Type Thread 173 consists of a number of pre-determined clinical workflows, each of which has been designed for a specific disease, Orthopedic Disease 1 to Orthopedic Disease N, to provide personalized treatment solutions for patients. Examples of orthopedic disease including, but not limited to, Osteonecrosis, Osteoarthritis, different types of Fracture, and Scoliosis, The pre-determined clinical workflow may include one or more analysis functionalities from Analysis Functionality Thread 175 and other customized functionalities specific for the disease. The Analysis Functionality Thread enables physicians to select from a range of specific analysis tools including, but not limited to, Diagnosis 310, Interactive Visualization 320, Pre-surgieal Planning 330, Biomechanics Analysis 340, Personalization 350 and 3D Printing 360, which can be applied to patient information in order to perform certain specific analysis function(s) for certain patient's data or certain condition of the diseases.
[0027] The Diagnosis tool 310 in Fig. 4 is a 2D diagnostic tool for detecting and differentiating orthopedic abnormalities associated with various diseases. Such diagnosis is based on the patient's imaging data retrieved from Radiographic Images 150, with or without other clinical data from Related Input Information 140. Various kinds of technology tools are used to detect and highlight diseased regions of bone tissue, which is referred to as the "conspicuous regions." Examples of such technology tools include artificial intelligence algorithms such as artificial neural networks for computer vision, machine learning, and statistical pattern recognition and digital image processing. These technologies are employed to extract the characteristics and features of the conspicuous regions associated with a bone disease for diagnosis purposes. Either the whole image or a selected ROI from the image may be used by the Diagnosis tool. The conspicuous regions can be permanently saved in Archive 120 and/or Patient Record 130; and may be used for future machine diagnostics after they have been approved by the physicians as disease-related abnormalities.
[0028] Many characteristics of a conspicuous region may be analyzed for diagnostic purposes, such as (1) quantitative measurements, (2) texture descriptors, (3) anatomical spatial descriptors, and (4) other specific domain information descriptors. Quantitative measurements are a set of quantifiable features that can be used to assess the existence or degree of bone abnormality, such as size, shape, intensity and various statistics of such measurements. The texture descriptors characterize the homogeneity of an area that can be used as diagnostic indicators, for example, degeneration or sclerosis. The anatomical spatial descriptors can be used to indicate precise, relative positions of structures of the anatomy. For example, Osteonecrosis treatment varies with location, and the size and location of the necrotic lesion are important factors that are used to predict the collapse of the femoral head in the early stages of the disease.
[0029] The Interactive Visualization tool 320 in Fig. 4 allows the users to perform realtime interactive visualization and editing of 3D models and/or 2D images. An exemplary embodiment for the Interactive Visualization tool is illustrated in Fig. 5. It includes a Manipulation module 470, which allows the visualization and manipulation of both 2D images retrieved from Radiographic Image 150 and various 3D models such as 3D Surface Rendered Model 410, 3D Anatomy Model 430 and 3D Volume Rendered Model 450. It also allows the user to correlate the 3D models to the 2D images. The Interactive Model Editing module 490 further allows editing of the 3D models, if needed, for various purposes.
[0030] Surgical planning is an important aspect of the present invention, an embodiment of which is the Pre-surgical Planning tool 330 in Fig. 4. Pre- Surgical Planning 330 is a platform for real-time interactive pre-surgical planning. Fig. 6 illustrates an exemplary embodiment of the Pre-Surgical Planning Module 330, which includes Modeling 160, Quantification 500, Automatic Planning 510, Interactive Personalized Planning 520 and Biomechanics Analysis 340.
[0031] One important aspect of surgical planning is to obtain the specific quantitative measurements of the patient for whom the surgery is being planned. For that purpose, in one embodiment as shown in Fig. 6, the surgical planning module contains a quantification tool 500 which extracts quantitative measurements required for the surgery from the 3D models for the patient generated by Modeling 160. In other embodiments, such quantification tool can be an independent tool that can be utilized by the surgical planning and other tools. The quantitative measurements and the 3D models are then used for the Automatic Planning 510. The Automatic Planning 510 generates the pre-surgical plan according to the standard care protocol. The Interactive Personalized Planning 520 provides the interactive editing tools for the users to modify the pre-surgical plan to a more precise personalized pre-surgical plan according to the patient specific data. Biomechanics Analysis 340 is to provide evaluation for the pre-surgical plan. This enables the physician to evaluate the precision of the surgery for example the stability criteria of the THE. surgery (see below).
[0032] Automatic Planning tool 510 in Fig. 6 is a planning tool based on the 3D models built by the Modeling module 160 and the quantitative measurements extracted by Quantification 500, It then automatically generates a pre-surgical plan according to the standard care protocol. For example, in a particular embodiment for total hip replacement (THR) surgery, a precise match is required between the implants and the patient's anatomical structure, in terms of type and size of the implants, the positioning and orientation of the components, and the leg length and other size measurements of the patient. For a THR surgery, Automatic Planning 510 takes the 3D model of the patient's hip and leg segment from Modeling 160 and extracts the relevant quantitative measurements of the patient based on the 3D model. The automatic planning tool then generates the pre-surgical plan for the THR, which includes the standard implant model and the surgery procedure, using the standard THE. protocol. Then, the physician user of the system uses the Interactive Personalized Planning 520 to inspect and, if desired, to edit the pre-surgical plan to generate a precise and personalized pre-surgical plan for the patient. The precision personalized pre- surgical plan, especially the implant model, are then simulated and tested using the Biomechanics Analysis 340. The Biomechanics Analysis tool may generate recommendations for modifications for the pre-surgical plan based on the biomechanical tests. The feedback from the Biomechanics Analysis 340 may be used by the Interactive Personalized Planning 520 to further modify the personalized pre-surgical plan.
[0033] Biomechanics Analysis tool 340 in Fig. 4 is an embodiment of the evaluation tool which evaluates the soundness of the treatment plans generated by the system, including the implant designs. The kind of analyses employed by Biomechanics Analysis 340 may include orthopedic stress analysis of the bone/prosthesis structures, orthopedic fixation devices and other tissues. Fig. 7 illustrates an exemplary embodiment for Biomechanics Analysis 340. The Numerical Analysis 610 function may include, among other tools, Finite Element Analysis (FEA), which evaluates structural stability of the bone anatomy where the stress distributions are used to compare with the material property of the bone. Different numerical analysis approaches are used to assess the structural integrity of orthopedic implants. For example, the analysis of the stress and displacement distributions of the hip joint implant are used to assess the integrity of the THR surgery plan. The analytical outcome of Numerical Analysis 610 can be used to assist surgical and nonsurgical treatment for the patients. Numerical Analysis Model Library 630 is a library that stores the reference models, for example FEA reference models, to provide real-time analysis and evaluation for pre-surgical planning and personalized implant design. Non- Surgical Treatment Evaluation 650 uses the evaluation outcome to assist in non-surgical treatment planning. For example, the physicians use FEA analysis, based on the patient's 3D model, to evaluate the condition of the patients, and based on the outcome to decide an appropriate non-surgical treatment, and to follow-up with before and after treatment evaluation. Post-treatment Evaluation 690. For example, the FEA stress and displacement distributions of the necrotic region can be used to predict the collapse of the femoral head for early stage Osteonecrosis, therefore, it can be used to assist in non-surgical treatment such as medications, taking weight off the joint, range-of-motion exercises and electrical stimulation. Pre-surgical Planning Evaluation 670 provides interactive analysis to ensure the stability criteria of the pre-surgical planning from Pre-surgical Planning 330, together with the reference models from the Numerical Analysis Model Library 630 to achieve real-time analysis and evaluation. For example, the correct positioning of the acetabular cup ensures implant stability, and bearing surface wear and longevity. Post-treatment Evaluation 690 provides the before and after treatment evaluation for both non-surgical and surgical treatment. This is to provide evaluation for follow-up to monitor the progress of the treatment outcome.
[0034] The analytical module of the invention may include an implant design tool for designing 3D models of personalized implants and surgical accessories such as guide plates. The Personalization tool 350 in Fig. 4 is one form of embodiment of the personalized implant design tool . For convenience, the word "implant" is used broadly in the written description and the claims of this patent to cover an implant, a moid for an implant, a surgical accessory for an implant such as a guide plate, and a mold for such surgical accessor}', unless otherwise specified.
[0035] The evaluation tool discussed above may be used to evaluate implant models designed by the implant design tool, based on biomechanical simulations and tests, to ensure it meets the qualifying requirements of the implant. The evaluation results for an implant model may be fed back to the implant design tool to improve the implant model. The Biomechanics Analysis tool also serves as an evaluation for the requirement qualifying process for the personalized implant design to meet the requirement standard of the implant, [0036] Fig. 8 illustrates some exemplary components of Personalization 350. It takes the 3D Models generated by Modeling 160 to design personalized implant models. It may- include Standard Implant Selection 710, Personalized Implant Design 730, Personalized Qualification Process 750, Customized/Personalized Implant Model 770, and Customized/Personalized Guide Plate Model 790. The patient specific 3D models are used by the Standard Implant Selection 710 to select the closest matched standard implant model. Then, the physician user of the system uses the Personalized Implant Design 730 to inspect and, if desired, to edit the standard implant model to generate a precise and personalized implant model for the patient. Customized/Personalized Implant Model 770 generates a customized/personalized implant model and/or a mold thereof for 3D printing. Customized/Personalized Guide Plate Model 790 allows users to create the guide-plate models (or molds thereof) for 3D printing which are to be used during surgery.
[0037] In a particular embodiment, the process for generating customized/personalized implant models comprises the following steps: Standard Implant Selection 710 automatically selects the closest matched standard implant based on the type of surgery; a set of editing tools is provided to modify the standard implant to generate the customized/personalized implant model that best fits the 3D model of the specific patient via Personalized Implant Design 730; validating the customized/personalized implant model that meets the standard implant requirements through the Personalized Qualification Process 750. The qualifying process may generate recommendations for modifications for the personalized implant design based on the testing outcome generated from testing such as biomechanical tests or other requirement tests. The feedback from the testing outcome may be used by the Personalized Implant Design 730 to further modify the personalized implant design. Examples of the implants include, for example, joint surgery implants, prostheses, pins, rods, screws, and plates.
[0038] In another embodiment, the process for generating customized/personalized guide plate models comprises the following steps: ROI is selected for the surgery; the 3D stencil model is automatically generated from the patient's 3D model; a set of editing tools is provided to incorporate the pre-surgical planning from Pre-Surgical Planning 330 to the 3D stencil to generate the customized/personalized guide plate via Personalized Implant Design 730; validating the customized/personalized guide plate model that meet the stability requirements through the Personalized Qualification Process 750. For convenience, unless otherwise specified, when the patent uses the word "personalized" to denote a 3D model, an implant model, or a treatment plan, it means that such 3D model, implant model, or treatment plan are custom designed for a patient using the patient's own radiographic images and other related information. The qualifying process may generate recommendations for modifications for the personalized guide plate design based on the testing outcome generated from testing such as biomechanical tests or other requirement tests. The feedback from the testing outcome may be used by the Personalized Implant Design 730 to further modify the personalized guide plate design. Examples of guide plates include guide plates for pedicle screw placement with the positioning and angle of the screws from Pre-Surgical Planning 330.
[0039] The 3D Printing module 360 is an embodiment of a physical construction tool responsible for constructing physical models corresponding to virtual models generated from Personalization 350. Fig. 9 illustrates exemplary components for 3D Printing 360, wherein a 3D printer is used to produce the Customized/Personalized Implant 810, Customized/Personalized Implant Mold 830, Customized/Personalized Guide Plate Mold 850 and/or 3D Model Mold 870 to be used before, during, or after the treatment. Other embodiments for the physical construction function may include computerized numerical control (CNC) machining and injection molding.
[0040] Fig. 10 illustrates the various embodiments of the 2D, 3D Output 180. The 2D 181 provides output in Digital 182 form and/or Hardcopy 183. The 3D 184 includes, but is not limited to, 3D display with/without 3D glasses 185, Google Glasses 186, Virtual Display 187, Tactile Display 188 and 3D Printing Model 189. The 2D and 3D output can be displayed on hardware including, but not limited to, Monitor Display 190, Tablet/ Phone 191, Smart Device 192. 3D Glasses 185 and Google Glasses 186 are merely examples of wearable technologies that may be deployed for the display module of the invention.
[0041] Fig.11 illustrates the overall operation of the system according to one embodiment of the invention. It begins with the physician selecting a specific disease from User Selection Thread 170. The physician ensures the accuracy of the 3D model through the Interactive Visualization 320 and prints the 3D Model Mold 870 if needed. Diagnosis is performed via Diagnosis 310 and/or combined with 3D Model Mold 870 for treatment planning. It illustrates how the system, based on the different diagnosed stages, decides where surgery is or is not required. For early stage, Stage 1 910, Stage 2 915 and some Stage 3 920 where surgery is not required, the System further analyzes the conditions using Biomechanics Analysis 340 and the physicians can come out with Targeted Treatment 935 and follow-up with Post-treatment Follow-up 940 based on the evaluation. There may be a number of follow-ups before the treatment is completed. When Surgery is required, the physicians utilize Pre-surgical Planning 330 for pre-surgical planning and Personalization 350 for personalized implant and/or personalized guide-plate followed by Biomechanics Analysis 340 to evaluate the implant fitting based on the criteria specified by the users. The 3D Printing 360 mechanism utilizes the personalized model from Personalization 350 for printing the necessary Customized/Personalized Implant 810, and/or Customized/Personalized Guide Plates Mold 850 for Surgery 945. Post-surgery Follow-up 950 might involve evaluation using Biomechanics Analysis 340. If revision surger is required after Post-surgery Follow-up 950 then repeats the procedure again.
[0042] The above descriptions are merely exemplary embodiments of the present inventions. All the functional modules described above may be implemented by commonly utilized software or hardware techniques, or a combination thereof, that are within the knowledge of a person of ordinary skill in the art.

Claims

CLAIMS I claim:
1. A system for planning an orthopedic treatment, comprising:
a. A modeling module that constructs a 3D model of a body section of a patient relevant to the treatment based on radiographic images of the body section; and b. An analytical module comprising the following predefined analytical tools: i. An interactive visualization tool that allows a user of the system to visualize and edit the 3D model,
ii. A quantification tool for obtaining measurements of the 3D model relevant to the treatment,
iii. A planning tool for generating a surgery plan in consideration of the measurements and other related information of the patient, and iv. An evaluation tool for evaluating the surgery plan using a biomechanicai analysis;
wherein the planning tool allows the modification of the surgery plan using the output of the evaluation tool.
2. The system of claim 1, wherein the analytical module further comprising an implant design tool for generating an implant model in consideration of the measurements, and wherein the evaluation tool further allows the evaluation of the implant model using a biomechanicai analysis and the planning tool further allows the modification of the implant model using the output of the evaluation tool.
3. The system of claim 2, wherein the evaluation tool further allows one or both of the following functionalities: non-surgical treatment evaluation and post-treatment evaluation.
4. The system of claim 2, wherein the analytical module further comprising one or both of the following analytical tools:
i. A diagnostic tool which renders orthopedic diagnosis based on the radiographic images according to a predefined criteria,
ii, A construction tool which allows the construction of a physical object based on a model.
5. The system of claim 4, further comprising a disease module that contains various predefined workflows designated for specific orthopedic diseases, allowing the user to select a disease which automatically invokes a predefined workflow that contains one or more of the analytical tools in a suitable order for treatment planning for the disease.
6. The system of claim 1, wherein the surgical plan may also be modified manually by user inputs.
7. The system of claim 2, wherein the implant model may also be modified manually by user inputs,
8. The system of claim 1, further comprising an acquisition module which acquires the radiographic images either through an image acquiring device or by retrieving images from a patient database.
9. The system of claim 1, wherein the modeling module allows the storage of a 3D model for a patient into a patient database, and also allows the retrieval of a 3D model from the patient database.
10. The system of claim 1, further comprising a related input module which retrieves from a patient database related patient information to be used by the analytical module.
11. The system of claim 5, further comprising a report module that generates reports based on the operational results of the system.
12. A system for planning an orthopedic implant surgery on a patient comprising:
a. An implant design module for generating an implant model in consideration of a 3D model of the relevant orthopedic structure of the patient, and b. An evaluation module for evaluating the implant model using a biomechanical analysis method,
wherein the results of the evaluation module are sent back to the modeling module to improve the implant model.
13. The system of claim 12, further comprising a surgery design module that generates a pre-surgical plan for the implant surgery in consideration of the 3D model and related information of the patient.
14. The system of claim 13, wherein the evaluation module further allows the evaluation of the pre-surgical plan and the surgery design module further allows the modification of the pre-surgical plan using the results of the evaluation module.
1 5. The system of claim 12, further comprising a construction module which allows the construction of an implant using the implant model.
16. The system of claim 12 wherein the implant design module generates the implant
model in consideration of a quantitative measurement of the 3D model.
17. The system of claim 12, wherein the evaluation module comprising a numerical analysi s model library that enables the numerical evaluation of the implant model.
18. A system for planning an orthopedic treatment, comprising:
a. An analytical module comprising two or more of the following analytical tools; i. An interactive visualization tool that allows a user of the system to visualize and edit a 3D model of a patient' s orthopedic structure, ii. A quantification tool for obtaining measurements of a 3D model, iii. A planning tool for generating a personalized surgery plan,
iv. An evaluation tool for evaluating the surgery plan using a biomechanicai analysis,
v. An implant design tool for generating a personalized implant model, and
vi. An evaluation module for evaluating an implant model using a
biomechanicai analysis;
b. A disease module allowing the user to select a disease which automatically invokes a predefined workflow corresponding to the disease that contains two or more of the analytical tools in a suitable order.
19. The system of claim 1 8, wherein the analytical module further compri sing a
construction tool that allows the constniction of a physical object according to a 3D model or an implant model .
20. The system of claim 19, further comprising a report tool that may be automatically invoked as part of a predefined workflow.
21. A method for computerized planning of an orthopedic treatment of a patient,
comprising:
a. Acquiring two or more radiographic images of a body section of the patient relevant to the treatment,
b. Conducting two or more of the analyses below:
Conducting diagnosis using the images with the aid of a computer system,
Constructing a 3D model of the relevant orthopedic structures using the iii. Measuring quantitative data from the 3D model which are relevant to the treatment; iv. Generating a treatment plan in consideration of the quantitative data; v. Evaluating the treatment plan using a biomechanical analysis; and vi. Modifying the treatment plan using the data from the biomedical
analysis;
c. Reporting the results of the analysis.
22. The method of claim 21 wherein acquiring radiographic images is to retrieve the images from a patient database.
23. The method of claim 21, further comprising acquiring related patient information and using the related patient information in one or more of the analyses,
24. The method of claim 21, wherein the analyses further include the following:
i. Generating an implant model using patient information and treatment requirements;
ii. Evaluating the implant model using a biomechanical analysis;
iii. Modifying the implant model using the output of the biomechanical analysis; and
iv. Constructing an implant using the implant model.
25. The method of claim 24, wherein the analyses further include making orthopedic diagnosis using the radiographic images.
26. The method of claim 25, further comprising invoking a predefined workflow which automatically selects two or more of the analyses in a suitable order for the treatment.
27. A method for computerized planning of an orthopedic implant surgery for a patient, comprising:
a. Constructing a 3D model of a relevant orthopedic structure of the patient using the radiographic images of the orthopedic structure,
b. Generating an implant model in consideration of the 3D model,
c. Generating a treatment plan in consideration of the implant model, d. Evaluating the treatment plan using a biomechanical analysis, and
e. Modifying the treatment plan using the data from the biomedical analysis.
28. The method of claim 27, wherein the step of generating a treatment further includes generating a pre-surgical plan in consideration of the 3D model, the implant model, and other related information of the patient, the step of evaluating the treatment plan further comprising evaluating the pre-surgical plan using a biomechanical analysis, and the step of modifying the treatment plan further comprising modifying the pre- surgical plan using the data from the biomedical analysis,
a. Generating an implant model,
b. Evaluating the implant model using a biomechanical analysis, and
c. Modifying the implant model using the output of the biomedical analysis.
29. The method of claim 27, further comprising:
a. Constaicting an implant using the implant model, and
b. Reporting the results of the treatment planning.
30. The method of claim 29, further comprising;
a. Acquiring a second set of radiographic images of the body section after the surgery,
b. Constructing a second 3D model of the relevant orthopedic structures using the second set of radiographic images,
c. Evaluating the conditions of the orthopedic structures by examining the second set of radiographic images and the second 3D model.
31. A system for computer-aided diagnosis of an orthopedic disease of a patient,
comprising
a. An acquisition module for acquiring a radiographic image of the patient
relevant to the disease,
b. A detection module for detecting a conspicuous region of a relevant bone structure of the patient using an artificial intelligence algorithm, and c. An analysis module for exacting from the conspicuous region a bone
characteristic associated with an orthopedic disease.
32. A system for planning an orthopedic treatment of a patient, comprising:
a. A personalization module that allows the generation of a personalized 3D
model or a personalized implant model,
b. An evaluation module for evaluating the 3D model or implant model using a biomechanics analysis, wherein the results of the evaluation module may be used by the personalization module to modify the 3D model or the implant model, and
c. An output module for displaying the results of the personalization module and evaluation module.
33. The system of claim 32, wherein the output module utilizes a wearable display.
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