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Automated elaborate resection planning for bone tumor surgery
Dave Hill1, Tom Williamson2, Chow Yin Lai3
1Centre for Additive Manufacturing, School of Engineering, RMIT University, 58 Cardigan St, Carlton, 3001, Australia.
International Journal of Computer Assisted Radiology and Surgery
|November 2, 2022
Summary
This study presents an automated method for bone tumor resection planning, significantly reducing healthy bone removal. This approach optimizes surgical cuts, improving patient outcomes and preserving critical anatomy.
Area of Science:
- Orthopedic Surgery
- Computational Geometry
- Medical Robotics
Background:
- Bone tumor resection planning is complex and manual.
- Current methods involve manual positioning of planar cuts.
- Advanced techniques require new planning strategies.
Purpose of the Study:
- To develop an automated approach for conformal bone tumor resection planning.
- To optimize resection geometry by minimizing healthy bone collateral resection.
- To compare automated planning with manual methods.
Main Methods:
- An automated approach using convex hull and focal point for resection geometry.
- Particle swarm optimization to minimize collateral resection of healthy bone.
- Comparison with manual planar resection plans in 20 tumor cases.
Main Results:
- Algorithm-generated hull-type resections significantly reduced healthy bone collateral resection.
- Statistically significant improvements observed compared to manual planning (p < 0.001).
Conclusions:
- The automated approach can improve patient outcomes in bone tumor surgery.
- Reduces collateral resection of healthy bone.
- Aids in preserving critical nearby anatomy.
