Dynamic analysis of nerves around the elbow using MRI-derived 3-D modeling

Area of Science:

• Orthopedic Surgery
• Medical Imaging
• Biomechanical Engineering

Background:

• Elbow arthroscopy requires precise portal placement for safety and efficacy.
• Augmented reality (AR) systems offer potential for real-time surgical guidance.
• Accurate 3-D anatomical models are crucial for AR system development.

Purpose of the Study:

• To extract 3-D bone and nerve data from elbow MRI scans.
• To generate an averaged 3-D model of peri-elbow nerves.
• To analyze nerve kinematics during elbow flexion and extension for surgical planning.

Main Methods:

• Fifteen volunteers underwent elbow MRI at multiple flexion angles (0°, 45°, 90°).
• DICOM data were processed into 3-D bone and nerve models using VoTracer and Rhinoceros software.
• Nerve models were averaged, and nerve kinematics were analyzed throughout the flexion-extension arc.

Main Results:

• Averaged 3-D nerve models were successfully generated with excellent reliability.
• The distance between the lateral epicondyle and the posterior interosseous nerve significantly increased with flexion (p=0.001).
• The distance between the medial epicondyle and the median-ulnar nerve showed no significant change with flexion (p=0.201).

Conclusions:

• 3-D bone and nerve data can be extracted from a single MRI sequence.
• Generalized peri-elbow nerve trajectories can be mapped in vivo across the flexion-extension arc.
• These findings provide quantitative guidance for optimal elbow positioning during arthroscopic portal creation.