Assisted Trajectory Planning for Surgical Precision
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current surgical procedures lack an efficient system for planning and rating trajectories during minimally invasive procedures, which can lead to variability in outcomes due to subjective decision-making by surgeons, and there is a need for a system that can assist in determining safe and efficacious trajectories based on prior data and user-specific preferences.
Innovation Solution
An assisted trajectory planning (ATP) system that utilizes both offline and online learning algorithms to analyze and rate trajectories, incorporating data from expert ratings and user-specific inputs to provide personalized and objective trajectory planning for surgical procedures, such as tumor removal or deep brain stimulation, by using image data and geometric features to determine coefficients for trajectory evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If surgical procedures rely on subjective decision-making by surgeons for trajectory planning, then surgeon experience and intuition can guide the procedure, but variability in outcomes increases and objectivity decreases
Solution Approach 1:
The patent introduces an assisted trajectory planning system that acts as an intermediary between the surgeon's subjective decision-making and the actual trajectory execution. The system processes multiple trajectories through learned coefficients and algorithms to generate objective ratings, mediating the transition from subjective surgeon preference to objective, consistent outcome evaluation without replacing surgeon control
Solution Approach 2:
The system transforms trajectory evaluation from subjective surgeon assessment to objective parameter-based rating by changing the evaluation parameters. It uses geometric features, image data, and learned coefficients to quantify trajectory characteristics, converting qualitative surgeon judgment into measurable, consistent parameters that reduce outcome variability
2Measurement precision
If a standardized trajectory rating system is implemented, then objectivity and consistency improve, but adaptability to individual surgeon preferences and specific cases decreases
Solution Approach 1:
The system implements dynamic adaptability where the standardized rating framework can adjust to individual surgeon preferences and specific case characteristics. The learned coefficients are trained on diverse datasets including multiple surgeons' preferences, allowing the system to adapt its evaluation criteria while maintaining the core standardized structure for objective measurement
Solution Approach 2:
The trajectory evaluation is segmented into multiple independent components including geometric features, image data analysis, and learned coefficient ratings. This segmentation allows the system to maintain standardized precision in each component while enabling flexible weighting and combination to adapt to different surgeon preferences and case requirements
3Reliability
If multiple trajectories are evaluated and rated, then the best trajectory can be identified, but the time and computational resources required increase
Solution Approach 1:
The system performs preliminary action by pre-training learned coefficients on extensive datasets of trajectories and surgical outcomes before actual use. This preliminary training establishes the evaluation framework and coefficient weights in advance, allowing rapid application during actual trajectory planning without requiring time-consuming analysis during the procedure itself
Solution Approach 2:
The patent replaces manual, time-consuming trajectory evaluation with automated computational algorithms. The system uses computer-based processing to calculate geometric features, analyze image data, and apply learned coefficients to rate multiple trajectories simultaneously, substituting mechanical surgeon assessment with efficient computational evaluation that handles multiple trajectories rapidly
Data Source
AI summary
A procedure can be assisted by a processor system, such as a computer system. A trajectory can be used to identify a selected trajectory or path of an instrument to reach a tumor within a brain of a subject, reach a selected portion of the anatomy (e.g. sub-thalamic nucleus (STN) or spinal cord), or other appropriate target. The planning algorithm can include both inputted data and learned rankings or ratings related to selected trajectories. The planning algorithm can used the learned ratings to rate and later determined trajectories.