Bone Cut Positioning by Bone Hardness for Implant Fit
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Solution Overview
Problem
Existing surgical procedures face challenges in accurately adjusting bone cut positioning due to variations in bone quality, density, or hardness, leading to issues such as implant misfit, bone fracture, or insufficient osseointegration, especially when using cementless implants.
Innovation Solution
The use of computer-assisted surgical systems with robotic assistance to detect bone hardness parameters, determine a bone hardness index, and adjust bone cut positions based on this index to optimize implant fit, utilizing algorithms and empirical models to correlate detected parameters with hardness values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a fixed A-P distance cutting block is used, then the cutting process is simple and quick, but the implant fit is poor when bone hardness varies
Solution Approach 1:
The cutting block transitions from a fixed A-P distance design to an adjustable design where the A-P distance can be dynamically modified based on detected bone hardness. The system includes adjustment mechanisms that allow the anterior-posterior cut positions to be shifted relative to each other, enabling the cutting block to adapt to different bone conditions while maintaining surgical efficiency.
Solution Approach 2:
The system changes the physical parameter of A-P distance based on bone hardness detection. When bone hardness is detected, the system automatically or semi-automatically adjusts the A-P distance parameter to optimize the interference fit for cementless implants, transforming a static parameter into a variable one that responds to bone quality.
2Loss of time
If bone hardness is not accounted for, then the surgical procedure is faster, but the risk of bone fracture or insufficient osseointegration increases
Solution Approach 1:
The system performs bone hardness detection and A-P distance adjustment before the actual implant placement. This preliminary action allows the optimal cutting parameters to be established in advance based on the patient's specific bone characteristics, ensuring both speed and reliability without requiring time-consuming intraoperative adjustments during implant insertion.
Solution Approach 2:
The system incorporates feedback from bone hardness detection to automatically adjust the A-P distance. The detection system provides real-time information about bone quality, and this feedback is used to modify the cutting parameters, creating a closed-loop control system that ensures reliable osseointegration while maintaining surgical efficiency.
3Adaptability or versatility
If the A-P distance is adjusted manually based on surgeon experience, then some bone hardness variations can be addressed, but the adjustment precision is limited by subjective estimation
Solution Approach 1:
The system replaces manual subjective estimation with an automated detection and adjustment system. Objective measurement tools (such as percussion sensors, ultrasonic devices, or imaging-based analysis) substitute for the surgeon's tactile and visual assessment, providing precise quantification of bone hardness and enabling accurate calculation of the optimal A-P distance adjustment.
Solution Approach 2:
The system introduces an intermediary computational layer between bone hardness detection and A-P distance adjustment. Software algorithms process the detected bone hardness data and calculate the precise adjustment needed, serving as a mediator that translates subjective or raw measurement data into precise, actionable cutting parameter modifications.
Data Source
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AI summary
Systems and methods for adjusting bone cut positioning are disclosed that can aid in optimizing implant size selection and positioning relative to bone during, e.g., orthopedic surgical procedures such as knee arthroplasty, hip arthroplasty, etc. In one embodiment, such a surgical method can include performing a first bone cut of a first bone using an at least partially robot-assisted surgical instrument, detecting one or more parameters related to bone hardness, selecting a bone hardness index based on the one or more detected parameters, and adjusting a position of a second bone cut of the first bone based on the selected bone hardness index to optimize implant fit relative to bone. Detecting the one or more parameters related to bone hardness can be performed in a number of manners, including by monitoring energy required to perform the first bone cut.