3D Shoulder Arthroplasty Planning for Mobility and Stability Prediction
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Solution Overview
Problem
Current TSA planning tools fail to provide personalized predictions of post-operative mobility, stability, and muscle function, leading to issues like scapular notching, implant loosening, and instability, which are not adequately addressed by existing generic knowledge extrapolation to patient-specific cases.
Innovation Solution
A 3D modeling system integrated with CT-based patient anatomy for simulating post-operative shoulder range-of-motion, muscle function, and activities of daily living, providing personalized insights for implant selection and placement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If generic knowledge from scientific literature is used to predict post-operative muscle function, then the planning process is simple, but the prediction accuracy for patient-specific cases is poor
Solution Approach 1:
The patent creates a personalized 3D computational model that copies and replicates the patient's specific anatomy from CT scan data, including bone geometry, muscle attachments, and joint structures. This patient-specific digital copy enables accurate simulation of post-operative muscle function and joint mechanics that cannot be obtained from generic literature data.
Solution Approach 2:
The system changes key parameters by transitioning from generic population-based data to patient-specific anatomical parameters derived from individual CT scans. This includes measuring actual muscle moment arms, bone geometry, and joint center positions for each patient, which fundamentally alters the accuracy of predictions.
2Ease of operation
If current TSA planning tools are used, then the planning process is straightforward, but post-operative mobility and stability cannot be accurately predicted
Solution Approach 1:
The patent performs preliminary computational simulations before surgery to predict post-operative mobility, stability, and muscle function. By conducting virtual trials of different implant configurations and orientations in the patient-specific 3D model, the system enables surgeons to optimize implant placement beforehand, avoiding the need for complex post-operative adjustments.
Solution Approach 2:
The system introduces a computational simulation engine as an intermediary between implant selection and surgical execution. This software intermediary calculates and visualizes predicted post-operative outcomes, serving as a bridge that translates implant geometry and placement parameters into meaningful predictions of mobility and stability.
3Length of moving object
If implant placement is optimized for range of motion, then mobility is improved, but stability may be compromised due to scapular notching and impingement
Solution Approach 1:
The patent employs dynamic simulation that analyzes joint mechanics across the full range of motion, not just static positions. The system evaluates how the joint behaves during movement, identifying dynamic impingement events and stability issues that occur during activities of daily living, enabling optimization that balances both mobility and stability.
Solution Approach 2:
The system adds the dimension of temporal analysis by simulating motion through multiple positions and angles. Instead of evaluating a single static configuration, the software analyzes the joint's behavior across a spectrum of movements, identifying conflicts between mobility and stability that only manifest during dynamic activity.
Data Source
AI summary
Disclosed herein is a system and method for performing pre-operative planning of total joint arthroplasty. The planning tool builds a model and analyzes and visualizes movement of the joint for various selections of implant models and placement of the components on the implants on the patient's anatomy. The tool also analyzes and visualizes motions of the joint during common activities of daily living and analyzes and visualizes changes in muscles.