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Abstract #4039

Numerical Validation of Multi-Compartment Diffusion Biomarkers of Peripheral Nerve Trauma

Thammathida Ketsiri1, Kelvin Chen1,2, Junzhong Xu3, and Richard Dortch1
1Department of Translational Neuroscience, Barrow Neurological Institute, Phoenix, AZ, United States, 2University of Virginia, Charlottesville, VA, United States, 3Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States

Synopsis

Keywords: Simulation/Validation, Diffusion Modeling, biomarkers,volume fraction, spherical mean technique

Motivation: The spherical mean technique (SMT) is a multi-compartmental diffusion model that has been used to evaluate axonal loss in the brain. This method holds promise as a biomarker of peripheral nerve regeneration following injury and surgical repair but has yet to be validated.

Goal(s): This study aims to validate the use of the multi-compartmental diffusion MRI in peripheral nerve imaging.

Approach: The SMT technique was validated via computational modeling studies based on light microscopy data of rats' sciatic nerves.

Results: We found that the SMT specifically assays axonal regeneration after trauma, even in the presence of other potentially confounding features.

Impact: The spherical mean technique (SMT), a multi-compartmental diffusion MRI model, demonstrated potential as a biomarker of peripheral nerve regeneration following injury and surgical repair.

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Keywords