Surgical Implant Planning Using Corrected Joint Motion Data
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Solution Overview
Problem
Current surgical methods for joint replacement surgery face challenges in accurately determining the position and orientation of implant components due to anatomical variations and disease states, such as osteoarthritis, which affect joint alignment and ligament tension, making it difficult to achieve optimal joint kinematics postoperatively.
Innovation Solution
A surgical planning method and system that captures corrected limb pose data using a corrective force to align bones in a desired alignment, allowing for precise implant placement based on preoperative CT-derived models, enabling accurate intraoperative implant planning and bone cutting to achieve appropriate ligament tension throughout the joint's range of motion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If preoperative images are used for implant planning, then the planning process is straightforward, but the accuracy of assessing joint motion and alignment is insufficient due to disease state distortions
Solution Approach 1:
The system performs preliminary actions by capturing bone pose data and applying corrective forces to achieve desired alignment before the actual implant placement. This allows the surgeon to plan implant positioning based on corrected alignment data rather than distorted preoperative images, improving measurement precision while maintaining a systematic workflow
Solution Approach 2:
The system creates digital copies of bone structures through CT-derived models and virtual representations of bones and implant components. These digital models allow for accurate assessment and planning without being constrained by the limitations of physical preoperative imaging, enabling precise measurement while keeping the interface user-friendly
2Manufacturing precision
If corrective force is applied to achieve desired alignment, then accurate implant placement can be planned, but the surgical procedure becomes more complex
Solution Approach 1:
The system replaces complex mechanical alignment procedures with a computational approach. A computer automatically applies corrective forces to virtual bone models and calculates optimal implant placement based on captured bone pose data, achieving high precision while reducing the need for complex manual surgical techniques
Solution Approach 2:
The system introduces an intermediary computational layer between bone pose capture and implant placement planning. The computer processes bone pose data, applies corrective forces virtually, and generates implant placement recommendations, simplifying the overall surgical workflow while maintaining precision
3Reliability
If customized implant placement is implemented to address anatomical variations, then joint performance is improved, but the planning process requires more time and resources
Solution Approach 1:
The system enables customization of implant placement by allowing modification of key parameters such as implant position, orientation, and size based on captured bone pose data and desired alignment goals. This ensures optimal joint performance for each patient's unique anatomy while the computer automates the parameter optimization process to maintain efficiency
Data Source
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AI summary
The description relates to surgical computer systems, including computer program products, and methods for implant planning using corrected captured joint motion information. Data representative of a corrected limb pose at a plurality of poses within a range of motion of a joint (120) associated with a particular individual is captured, the joint comprising a first bone (T) and a second bone (F), while the first bone, the second bone, or both are subject to a corrective force aligning the first and second bones in a desired alignment. The first bone of the joint is represented. The second bone of the joint is represented. A first implant model is associated with the representation of the first bone. A second implant model is associated with the representation of the second bone. Based on the captured data, a relationship is determined between the first implant model and the second implant model at one or more poses of the plurality of poses within the range of motion of the joint. Information representative of the determined relationship is displayed.