Degenerative cervical spondylotic myelopathy (CSM) is the most common cause of spinal cord injury (SCI) representing a significant public health problem. A major shortcoming limiting efforts to improve the treatment of patients with CSM is the lack of quantifiable metrics on which to base clinical decisions. Advanced MRI techniques, such as diffusion tensor imaging (DTI) have shown promise in this area. DTI measures the magnitude, anisotropy, and directionality of water displacement in tissue and provides quantifiable measures of directional diffusivity along white matter tracts. While DTI provides a valuable tool to assess white matter integrity, unfortunately, we have found current DTI techniques are flawed because diffusion properties derived using DTI lose specificity and sensitivity with increasing pathological and anatomical complexity. Thus the prediction of long-term outcome using DTI remains uncertain. To overcome factors confounding DTI analysis, we developed diffusion basis spectrum imaging (DBSI), to more accurately delineate white matter injury, allowing differentiation and quantification of axonal injury/loss, demyelination, and inflammation in the setting of spinal cord compression. DBSI quantifies edema/tissue loss in addition to axon/myelin injury, providing improved imaging biomarkers that more accurately predict a patient's clinical course, response to therapy, and long-term prognosis. The long-term objective of this proposal is to establish and validate non-invasive imaging biomarkers that are predictors of clinical course and therapeutic response to surgical decompression in patients with CSM.
The first aim will assess whether spinal cord DBSI pathological metrics reflect neurological impairments and predict long-term neurologic outcomes following decompressive spinal surgery in patients with CSM.
This aim will test the hypothesis that clinical manifestations of spinal cord compression in mild CSM are predominantly a reflection of edema and inflammation, with a lower incidence of true axonal loss; In contrast the high variability of functional recovery observed in moderate CSM patients is attributable to a greater risk for permanent axonal loss caused by spinal cord compression.
The second aim of this proposal, will refine DBSI modeling for assessing effects of blood flow deficits on spinal cord pathology and improving the accuracy of axonal loss quantification in CSM.
This aim will test the hypothesis that the effect of spinal cord blood flow on CSM pathology may be assessed by including Intra-Voxel-Incoherent-Motion (IVIM) in DBSI modeling; the accuracy of DBSI-derived axon volume may be improved by including intra-axonal diffusion component in DBSI modeling. The identification and validation of such non-invasive DBSI biomarkers will provide guidance on clinical management, long-term prognosis, and family counseling. The validation of a non-invasive biomarker for predicting functional recovery in the surgical management of cervical myelopathy would represent a new and substantial advance in the treatment of cervical myelopathy.

Public Health Relevance

Cervical spondylotic myelopathy is the most common form of spinal cord injury and is a significant public health problem. The identification of non-invasive methods to assess preserved spinal cord integrity and predict functional recovery would represent a new and exciting advance in the treatment of these patients. This project seeks to identify and validate imaging markers that reliably assess preserved tissue and are predictive of functional recovery in patients with cervical spondylotic myelopathy.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS047592-11
Application #
9520435
Study Section
Neuroscience and Ophthalmic Imaging Technologies Study Section (NOIT)
Program Officer
Jakeman, Lyn B
Project Start
2005-04-01
Project End
2022-06-30
Budget Start
2018-07-01
Budget End
2019-06-30
Support Year
11
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Washington University
Department
Neurosurgery
Type
Schools of Medicine
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
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