Automatic positioning of cutting planes for bone tumor resection surgery

Area of Science:

• Orthopedic Surgery
• Biomedical Engineering
• Computational Optimization

Background:

• Patient-specific cutting guides are crucial for precise bone tumor resection.
• Current surgical guide modeling lacks automated cutting plane placement, a manual and critical step.
• Minimizing healthy bone resection is vital for improving post-operative results.

Purpose of the Study:

• To develop and evaluate an algorithm for automatic cutting plane positioning in bone tumor resection.
• To reduce the volume of healthy bone resected during surgery.
• To improve overall post-operative outcomes through enhanced surgical precision.

Main Methods:

• An algorithm employing particle swarm optimization (PSO) was developed for automatic cutting plane positioning.
• The cutting surface is defined by planes parallel to a specified surgical approach direction.
• An objective function evaluated cutting surface quality based on resected healthy bone and removed tumor volumes.

Main Results:

• The algorithm was tested on three long bone tumor cases (tibial and humeral epiphyses).
• Optimal PSO parameters were identified, with iterative parameter adjustments improving objective function stability.
• Initializing PSO with a plausible configuration enhanced stability and minimized healthy bone resection.

Conclusions:

• The developed algorithm shows promise for automating cutting plane positioning in bone tumor surgery.
• This automation can lead to reduced healthy bone resection and potentially better patient outcomes.
• Future research should focus on 3D optimization for further improvements in surgical planning.