Abstract
Neurotrauma is a leading cause of death and disability worldwide. Trauma is inherently chaotic and difficult to study, necessitating the use of translational models that provide standardizable and quantifiable models of injury. Rats are the most commonly used models of spinal cord (SCI) and peripheral nerve (PNI) injuries because their anatomy and physiology approximates that of humans, while their size and management make them economical and practical for large scale studies. Although the CNS does not regenerate, the peripheral nervous system does. One recent strategy under investigation for SCI patients is to use nerve grafts to restore function to spinal levels below the site of lesion. Questions remain about the suitability of rodent models for studies focused on higher order, complex, spinal tracts. Furthermore, questions remain on the best methods to track recovery following nerve graft or injury, as current diagnostic and prognostic clinical tools are limited. Diffusion MRI (dMRI) has the potential to classify nerve injury severity and evaluate nerve recovery more accurately and earlier in time than current electrodiagnostics but requires validation.
In this study, we evaluated the rat’s suitability as a translation model of sensory injury and recovery within the corticospinal tract (CST), the tract which controls fine hand function in primates. We chose this tract because restoration of hand function is the most cited goal among quadriplegics. Additionally, we developed and tested a method to help validate and evaluate advanced dMRI biomarkers of PNI. Our long long-term goal is to use dMRI to quantify nerve injury and recovery to aid clinical decision making and aid prognostication following PNI.
We found that rats display a similar response to primates and are suitable translational models for basic questions regarding the CST’s response to a sensory dorsal root-dorsal column SCI. Additionally, using a novel nerve-specific tissue clearing and innumolableing method we developed, we were able to track axons and derive a quantitative measure of the 3D histological structure of injured nerves, called a structure tensor. We show this measure correlates to the fractional anisotropy we acquired from dMRI within our clinically relevant cut-repair PNI model. Together, this lays the foundation for future clinical validation and translation of these novel imaging biomarkers of nerve injury and recovery.