Modeling Postoperative Nerve Regeneration Using Diffusion MRI: A Preclinical Study of a Novel Mathematical Approach.

Area of Science:

• Neuroscience
• Biomedical Engineering
• Radiology

Background:

• Timely nerve regeneration is crucial for functional recovery after injury.
• Current assessment methods offer limited insights, leading to delayed treatment and poor outcomes.
• Diffusion magnetic resonance imaging (MRI) and mathematical modeling present a potential solution for monitoring nerve repair.

Purpose of the Study:

• To evaluate diffusion magnetic resonance imaging (MRI) and a Gompertz function-based mathematical model for monitoring nerve regeneration.
• To assess the correlation between diffusion tensor imaging (DTI)-derived fractional anisotropy (FA) and functional recovery after nerve injury and repair.

Main Methods:

• Sprague Dawley rats underwent sham surgery or sciatic nerve cut and immediate repair.
• In vivo diffusion tensor imaging (DTI) was performed bi-weekly for 12 weeks.
• Functional recovery was assessed weekly using the sciatic functional index (SFI).

Main Results:

• Sciatic functional index (SFI) and DTI-derived fractional anisotropy (FA) values demonstrated similar longitudinal trends in sham and repair groups.
• FA values in the distal nerve section showed the highest correlation with behavioral indices (r=0.84, p<0.001).
• FA values in central (r=0.82, p<0.001) and farthest sections (r=0.70, p<0.001) also correlated significantly with functional recovery.

Conclusions:

• Automated analysis of FA profiles along the nerve can distinguish successful from unsuccessful nerve regeneration.
• This DTI-based tool could enable early diagnosis of nerve recovery in clinical settings.
• The method may help identify patients requiring secondary surgical repair, improving patient outcomes.