Robotic Surgical Cavity Control via Normalized Bone Density
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Solution Overview
Problem
Current computer-assisted surgical systems for joint replacement surgeries face challenges in accurately planning and executing the creation of a cavity for prosthetics due to fixed cutting strategies, variability in CT scanner values, and limitations in accommodating clinical needs and bone density variations, leading to potential errors in cut volume accuracy and increased operating times.
Innovation Solution
A system and process that utilize pre-operative imaging data to segment bone structures, apply normalized density values, and provide customizable cutting strategies based on clinical needs, allowing for precise planning and execution of cavity creation, using a universal phantom to normalize CT values and adjust cutter speed and engagement for optimal cutting paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If fixed cutting strategies are used for a given prosthesis module, then reproducibility of cut volume is ensured, but surgeon's ability to adjust for clinical factors is limited
Solution Approach 1:
The system transforms fixed cutting parameters into dynamic, adjustable parameters. The surgeon can modify cutting speed, feed rate, and tool paths in real-time based on intraoperative bone density observations and clinical conditions, while the system maintains the overall cut volume accuracy through continuous monitoring and adjustment.
Solution Approach 2:
The invention allows changing of cutting parameters (speed, feed rate, engagement depth) based on measured bone density values. The system adjusts these parameters dynamically during the cutting process to optimize both precision and adaptability to different clinical scenarios.
2Measurement precision
If conventional registration techniques are used to align coordinate frames, then alignment within 1 mm is achieved, but registration errors are propagated affecting overall system accuracy
Solution Approach 1:
The system implements continuous feedback during the cutting process by monitoring forces on the end mill and comparing actual cutting conditions against the planned trajectory. This feedback loop allows real-time correction of registration errors and maintains overall system accuracy despite initial alignment limitations.
Solution Approach 2:
The system performs preliminary validation of the cutting plan against the registered coordinate frames before actual cutting begins. This preliminary check allows identification and correction of potential registration errors before they propagate through the cutting process.
3Productivity
If cutter speed and feed rate are increased to reduce operating time, then productivity improves, but cutting accuracy may be compromised in dense bone
Solution Approach 1:
The system automatically adjusts cutting speed and feed rate parameters based on real-time bone density measurements. In denser bone regions, the system reduces speed and feed rate to maintain cutting accuracy, while in softer bone regions, it increases parameters to optimize productivity.
Solution Approach 2:
Different cutting parameters are applied to different regions of the bone based on local density variations. The system creates a spatially varying cutting strategy where high-speed cutting is used in softer regions and low-speed precision cutting is used in denser regions.
4Device complexity
If CT scanner values are used directly for bone density estimation, then pre-operative planning is simplified, but variability between scanners affects cutting strategy accuracy
Solution Approach 1:
The system introduces an intermediary calibration process that maps CT scanner values to actual bone density measurements. This calibration layer acts as a mediator between the scanner output and the cutting strategy, normalizing values across different scanner models and eliminating interscanner variability.
Solution Approach 2:
The system applies scanner-specific correction factors and calibration parameters to transform raw CT values into accurate bone density estimates. These parameter adjustments compensate for differences between scanner models while maintaining a unified planning interface.
Data Source
AI summary
A process and system for computer assisted orthopedic procedure is provided with a plurality of options to plan, execute, and monitor the creation of a cavity to receive a prosthetic based on clinical needs and pre-operative imaging data. A phantom made of materials of known densities is used to normalize CT image intensity values to estimate bone density. The process and system controls the speed, cutter engagement, orientation, and shape of the cavity so produced based on the normalized bone density values.