Experimental research based on robot-assisted surgery: Lower limb fracture reduction surgery planning navigation...

Area of Science:

• Orthopedic Surgery
• Medical Imaging
• Computational Geometry

Background:

• Achieving high precision in lower extremity fracture reduction surgery while minimizing secondary trauma remains a significant surgical challenge.
• Current methods for fracture reduction often face limitations in accuracy and potential for iatrogenic injury.

Purpose of the Study:

• To develop and evaluate a novel surgical planning and navigation system for lower extremity fracture reduction.
• To improve the accuracy of fracture reduction and reduce the forces involved during the procedure.

Main Methods:

• Segmentation and 3D reconstruction of fractures using computed tomography (CT) images.
• Development of a cross-sectional point cloud extraction algorithm and iterative closest point (ICP) algorithm for optimal bone repositioning.
• Integration of a collision detection algorithm to create a surgical planning algorithm for precise, collision-free fracture reduction.

Main Results:

• The developed system achieved an average reduction error of less than 1.0 mm in model bones.
• Surgical reduction using the planning and navigation system significantly reduced the applied reduction force.
• The system demonstrated a smoother change in reduction force during the procedure.

Conclusions:

• The proposed planning and navigation system for lower extremity fracture reduction surgery is both feasible and effective.
• This technology offers a promising approach to enhance precision and safety in orthopedic fracture treatment.