Pedicle Screw Trajectory Planning With Weighted Anatomical Factors
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Solution Overview
Problem
The planning process for pedicle screw placement in spinal fusion surgeries is time-consuming and complex, especially when using assistive technologies, and existing automated methods are biased by training data and require manual annotation, leading to inconsistent results.
Innovation Solution
A method and system that utilize a screw trajectory planning algorithm to determine initial and revised pedicle screw plans based on patient scans, incorporating weighted factors and techniques like Magerl, Roy-Camile, and Anderson, allowing for automated optimization and adjustment by surgeons, with options for manual or robotic surgery assistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual planning process is used for pedicle screw placement, then surgeon can account for individual anatomical variations and surgical preferences, but the process becomes time-consuming and complex
Solution Approach 1:
The system enables automated self-planning of pedicle screw trajectories by processing patient-specific anatomical data through algorithms that generate optimized screw paths without requiring manual annotation or surgeon intervention for each trajectory calculation
Solution Approach 2:
The system transforms the planning process from manual coordinate specification to automated parameter optimization by adjusting trajectory parameters (entry point, angle, depth) based on anatomical constraints and surgical goals
2Loss of time
If automated planning using atlas technique or machine learning is used, then surgical time is reduced, but the results are biased by training data and require manual annotation
Solution Approach 1:
The system creates a digital copy of the patient's unique spinal anatomy from imaging data and operates entirely on this virtual model, eliminating the need to copy or adapt trajectories from atlas data or training sets
Solution Approach 2:
The system extracts and removes the bias and annotation requirements from the planning process by using pure patient-specific anatomical data without incorporating external reference data or training sets
3Measurement precision
If assistive technologies like surgical navigation or robots are used, then surgical precision is improved, but the workflow is hindered by manual plan input
Solution Approach 1:
The automated planning system serves as an intermediary that translates patient anatomical data directly into machine-executable trajectory parameters, eliminating the manual translation step between surgeon planning and robotic/navigational system input
4Adaptability or versatility
If multiple screw trajectories are planned for different surgeons, then individual surgical preferences are accommodated, but the complexity of the planning process increases
Solution Approach 1:
The system dynamically adjusts trajectory parameters based on selected surgical techniques by allowing modification of weighting factors for different anatomical constraints and surgical goals, enabling adaptation to various techniques without restructuring the entire planning process
Data Source
AI summary
Systems and methods for automatically determining pedicle screw trajectories for surgery may be provided. A scan of a spine may be received, and positions of one or more vertebra and one or more components of the one or more vertebra in the scan may be identified. Next, a screw trajectory planning algorithm may determine an initial screw trajectory plan using the positions of the one or more vertebra and the one or more components. The screw trajectory planning algorithm may then determine a revised screw trajectory plan by revising the initial screw trajectory plan according to weighted factors.