Joint Prosthesis Simulation Using Segmented Soft Tissue Models
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Solution Overview
Problem
Existing methods for planning joint prosthesis implant surgery do not adequately account for the influence of soft tissues such as ligaments, tendons, muscles, and cartilage, leading to variability in surgical outcomes despite the use of identical prosthesis models.
Innovation Solution
A method for simulating a patient's joint by obtaining images that include point clouds of both bone and peri-bone tissue geometry, using shape recognition and deep learning to create a segmented digital model, and integrating a digital prosthesis simulation to anticipate the effects of the prosthesis on the patient's joint movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If only bone geometry is considered in joint prosthesis simulation, then the simulation process is simple and quick, but the surgical outcomes vary significantly between patients
Solution Approach 1:
The simulation model is segmented into multiple tissue types (bone, cartilage, ligaments, tendons, muscles) rather than treating the joint as a single homogeneous structure. Each tissue type is assigned specific mechanical properties and behavioral characteristics, allowing the simulation to capture the complex interactions between different peri-bone tissues and their influence on prosthesis performance
Solution Approach 2:
The simulation incorporates variable parameters for peri-bone tissue properties (elasticity, strength, attachment points) that differ between patients. By adjusting these parameters based on individual patient anatomy and tissue quality, the simulation achieves more reliable and uniform predictive outcomes across different patients while maintaining computational feasibility
2Measurement precision
If detailed peri-bone tissue analysis is incorporated into the simulation, then personalized surgical planning is achieved, but the processing time and computational resources increase
Solution Approach 1:
Peri-bone tissue characteristics (attachment points, fiber orientations, mechanical properties) are pre-characterized and stored in a database before surgery. During pre-operative planning, the simulation rapidly retrieves and applies these pre-analyzed tissue parameters to the patient's specific anatomy, achieving high measurement precision without requiring extensive real-time computation or delaying the surgical schedule
Solution Approach 2:
The method creates a detailed digital copy (virtual model) of the patient's joint including all peri-bone tissues. This virtual model can be repeatedly analyzed, tested with different prosthesis options, and optimized without additional time cost to the patient, as all computational work occurs in the digital domain rather than requiring physical prototypes or extended imaging sessions
Data Source
AI summary
Method for simulating a joint of a patient in order to plan joint prosthesis 20 implantation surgery including: analyzing an image 1 of the patient's joint to extract geometric information concerning the geometry of the bones 3, and of some at least of the soft tissues 2 forming it; fusing this information, assigning geometrical properties to the bones; using this information, assigning to the soft tissues of the points of connection on the bones, as well as connection forces estimated using the dimensions of these tissues; digitally modeling the joint taking into account the geometrical properties of the bones and the points of connection of the soft tissues, as well as the maximum connection forces of the soft tissues; integrating a digital simulation of the joint prosthesis 20 to the digital model; animating the digital model obtained after integrating the prosthesis, to anticipate its effect of the patient receiving surgery.