Spinal cord injury (SCI) is a debilitating condition with significant limitations for acute evaluation of severity, complicating prompt and effective treatment strategies. Diffusion Tensor Imaging (DTI) is a promising magnetic resonance imaging (MRI) research technique for detecting microscopic tissue injury in SCI, but requires long scan durations and lacks specificity for the important prognostic marker of cellular damage, reducing its clinical usefulness. The goal of this project is to apply a novel diffusion MRI technique to overcome these limitations and improve diagnosis and prognosis of SCI. This technique, termed double diffusion encoding (DDE), was specifically tailored to evaluate axonal integrity in the spinal cord, which has been shown to be the best predictor of functional outcome following injury, by reducing its sensitivity to edema and other processes that confound diffusion measurements. Preliminary data demonstrate that DDE measurements enable greater sensitivity to injury than DTI with a substantially reduced acquisition time. Furthermore, the automated DDE analysis requires minimal data post-processing and provides an important objective benefit over the time-consuming manual region of interest drawing commonly used with DTI. Thus, the DDE technique provides multiple benefits over DTI that increase its feasibility for potential clinical evaluation of SCI.
The aims of the project are to demonstrate the cellular basis for diffusion changes measured with DDE and its use as a prognostic indicator for long-term functional recovery. This method will be evaluated using a rat contusion model of SCI with graded severities induced by weight drop injuries. Comparison of MRI measurements to gold-standard histological quantification will demonstrate the strong association between DDE parameters and axonal injury (Aim 1). The prognostic capabilities of this new method will also be tested in the ability of acute DDE measurements to predict chronic nervous system function following injury (Aim 2). The results of these studies will impact both preclinical and clinical applications of SCI evaluation where improved sensitivity to axonal damage will better inform intervention, treatment, and rehabilitation strategies. The translational nature of the project, coupled with training in fundamental principles of scientific investigation, will promote continued success in my long-term goal to become an independent physician scientist.
This project will study a new MRI-based technique for rapidly evaluating spinal cord injury severity. Using a rat model of spinal cord injury, we will assess the ability of this method to detect injury and predict recovery. This will improve planning of short-term and long-term treatment strategies to provide the best care possible to patients with this debilitating condition.
|Budde, Matthew D; Skinner, Nathan P (2018) Diffusion MRI in acute nervous system injury. J Magn Reson 292:137-148|
|Skinner, Nathan P; Lee, Seung-Yi; Kurpad, Shekar N et al. (2018) Filter-probe diffusion imaging improves spinal cord injury outcome prediction. Ann Neurol 84:37-50|
|Budde, Matthew D; Skinner, Nathan P; Muftuler, L Tugan et al. (2017) Optimizing Filter-Probe Diffusion Weighting in the Rat Spinal Cord for Human Translation. Front Neurosci 11:706|