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Updated: Jan 23, 2026

Diffusion Tensor Magnetic Resonance Imaging in Chronic Spinal Cord Compression
Published on: May 7, 2019
Comparison of Acute Diffusion Tensor Imaging and Conventional Magnetic Resonance Parameters in Predicting Long-Term
Kathirkamanathan Shanmuganathan1, Jiachen Zhuo1, Uttam K Bodanapally1
1Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland.
Abstract:
This prospective longitudinal study compares the ability of conventional and diffusion tensor imaging (DTI) parameters made at the cervical spinal cord injury (CSCI) site to predict long-term neurological and functional outcomes. Twenty patients with CSCI, with follow-up at 6 or 12 months, and 15 control volunteers were included. Conventional magnetic resonance imaging (MRI) and DTI parameters were measured on admission and follow-up studies. Stepwise regression analysis was performed to find relevant parameters (normalized DTI values, conventional MRI measurements, hemorrhagic contusion [HC] or non-HC [NHC]) that correlated with three primary outcome measures: patient International Standards for Neurological Classification of Spinal Cord Injury total motor score (ISNCSCI-TMS), ability to walk, and expected recovery of upper limb motor scores (ER-ULMS) at 6 or 12 months. Univariate analysis showed HC (p < 0.0001 to 0.0098), lesion length on follow-up MRI (p < 0.0001 to 0.019), mean diffusivity (p = 0.01 to 0.045), and axial diffusivity (p = 0.004 to 0.023) predicted all three primary outcomes. Conspicuity of HC was significantly better on axial susceptibility-weighted imaging (SWI) compared with T2* images (p = 0.0009). A negative correlation existed between HC volumes on sagittal SWI images and follow-up ISNCSCI-TMS ( p = 0.02). The regression model identified NHC as the best predictor of the ability to walk (sensitivity = 88.9%; specificity = 100%; positive predictive value = 100%; negative predictive value = 91%; p < 0.0001) and lesion length on follow-up MRI as the best predictor of ER-ULMS (β coefficient = 0.12, standard error [SE] = 0.07; R2 = 0.64; p = 0.0002). Finally, NHC (β coefficient = 24.2, SE = 3.7; p < 0.0001) and lesion length on initial MRI (β coefficient = 0.78, SE = 0.2; p = 0.002) were the best predictors of ISNCSCI-TMS (R2 = 0.83; p < 0.0001). Our study demonstrates HC and follow-up lesion length are potential neuroimaging biomarkers in predicting long-term neurological and functional outcome following blunt CSCI.
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