Collision Detection for Surgical End-Effector Using Registered Imaging
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Solution Overview
Problem
Current computer-assisted surgery systems face challenges in accurately positioning bones relative to each other, leading to limited feedback and increased operating time due to potential collisions and the need for manual repositioning, which complicates the execution of surgical plans during joint replacement procedures.
Innovation Solution
A method and system that provide visual and computational feedback to assist in positioning bones by projecting potential collision paths of the end-effector with bystander anatomy, allowing for real-time adjustments to avoid collisions and optimize bone placement, using registered imaging data and cut-files to determine safe orientations and movements of the end-effector.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the end-effector is manually repositioned to avoid collisions with bystander anatomy, then collision risk is reduced, but operating time increases due to repeated manual adjustments and re-fixation
Solution Approach 1:
The system performs preliminary collision detection by projecting the end-effector's planned trajectory against registered imaging data of bystander anatomy before execution. This advance detection allows the surgical plan to be adjusted pre-operatively or intra-operatively to avoid collisions, eliminating the need for time-consuming manual repositioning during surgery.
Solution Approach 2:
The system provides real-time feedback by calculating and displaying potential collision paths based on registered imaging data and the surgical plan. This feedback mechanism allows the surgeon to visualize and adjust bone positioning or surgical approach before collisions occur, preventing time loss from manual interventions.
2Measurement precision
If imaging data is registered to bystander anatomy to detect collision paths, then collision detection accuracy is improved, but system complexity increases
Solution Approach 1:
The system creates a virtual copy of the bystander anatomy from registered imaging data (CT or MRI scans) and superimposes it onto the surgical field. This digital twin allows for accurate collision detection without adding physical complexity to the surgical environment. The virtual model can be manipulated and analyzed computationally to predict end-effector trajectories.
Solution Approach 2:
The system replaces complex mechanical collision detection mechanisms with computational methods. Instead of using physical sensors or mechanical guides to detect collisions, the system uses software algorithms to calculate potential collision paths by projecting the end-effector's intended movement against the registered imaging data of bystander anatomy.
3Adaptability or versatility
If the bone position is adjusted to provide clearance for the end-effector, then surgical plan executability is improved, but positioning accuracy requirements increase
Solution Approach 1:
The system determines optimal bone positioning requirements in advance by analyzing the surgical plan and calculating the clearance needed for end-effector execution. This preliminary analysis provides specific positioning guidelines to the surgeon before the procedure begins, ensuring that bones are positioned correctly from the start to maintain both clearance and accuracy.
Solution Approach 2:
The system provides feedback on bone positioning by comparing the actual position against the optimal position calculated from the surgical plan. This feedback allows for real-time adjustments while maintaining precision, ensuring that clearance requirements are met without compromising positioning accuracy.
Data Source
AI summary
A method of detecting a potential collision between an end-effector and bystander anatomy is provided. A cut-file or a representation of an implant is registered to a position of a first bone, the registered cut-file defining at least one orientation for an end-effector axis to assume while physically modifying the first bone. Imaging data of bystander anatomy is registered to a position of the bystander anatomy. The at least one orientation of the end-effector axis as defined in the registered cut-file is calculated in a computer if it has a spatial overlap with the registered imaging data to detect the potential collision. A portion of the registered representation can also projected along an axis with the projection used to determine possible collisions and if so provide the user with options.