# Advanced MRI of Spinal Cord Injury

> **NIH VA I01** · CLEMENT J. ZABLOCKI VA MEDICAL CENTER · 2020 · —

## Abstract

Rationale and Preliminary Data: We will conduct a study of human spinal cord injury (SCI) to validate MRI
biomarkers of injury severity and prognostication of outcome using a novel diffusion MRI technique developed
specifically to detect axonal injury in the spinal cord. Predicting outcome from SCI has been a longstanding goal
for better clinical management and aiding in the development and testing of therapies. Traditional neurological
examination is not an accurate predictor of outcome, and conventional MRI, including T2-weighted imaging,
while useful for diagnosis, does not accurately predict the degree of recovery. Diffusion tensor imaging (DTI)
has shown promise as a prognostic imaging biomarker in SCI, but its clinical adoption has been hindered by
technical challenges and non-specificity to the underlying pathology. Our preclinical studies in a rat SCI model
have demonstrated that double diffusion encoding (DDE) MRI is sensitive to acute axonal injury and predicts
outcome with accuracy better than either DTI or traditional functional scoring. Likewise, recent developments
by our collaborative group have demonstrated the ability to employ diffusion contrast adjacent to metal surgical
hardware, which is prone to artifacts. While promising, validation of these technologies to simultaneously
improve contrast and quality is critical to advance the technology and ensure its utility in human subjects and
clinical settings. This project will translate these techniques to advance the understanding of the DTI changes
in the cord as markers of injury. Our hypotheses are 1) in the acute setting, DDE estimates of acute axonal
injury will predict long-term functional outcomes, and 2) in the chronic setting, DDE estimates of permanent
axonal loss will correlate with existing functional outcomes. It is predicted that DDE will outperform DTI,
conventional MRI, or functional neurological exams in SCI. To test this hypothesis, we will perform in vivo MRI
and functional assessments in the acute phase after traumatic spinal cord injury. In Aim 1, we will examine the
prognostic ability of DDE to predict later neurological recovery using follow-up functional assessments. In Aim
2, we will detail the link between axonal loss (sparing) as measured by DDE and permanent neurological function
after SCI. These studies seek to establish and validate DDE as a surrogate maker of injury severity and outcome
and compare it with existing clinical standards and established MRI indicators of SCI. We hypothesize based
on strong preclinical results that detection of microstructural injury using DDE will more accurately reflect the
degree of neurological impairment than MRI techniques non-specific to underlying pathology. The potential for
clinical translation is highlighted by DDE being a rapid acquisition of only a few minutes and requires minimal
post-processing or post-hoc analysis for quantification. Moreover, DDE enables visualization of the degree of
injury in individual ...

## Key facts

- **NIH application ID:** 9900574
- **Project number:** 5I01RX002751-02
- **Recipient organization:** CLEMENT J. ZABLOCKI VA MEDICAL CENTER
- **Principal Investigator:** Shekar N. Kurpad
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2020
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2019-04-01 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9900574

## Citation

> US National Institutes of Health, RePORTER application 9900574, Advanced MRI of Spinal Cord Injury (5I01RX002751-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9900574. Licensed CC0.

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