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Diffusion MRI in Cervical Spondylotic Myelopathy (CSM)

Active, not recruiting
Conditions
Cervical Spondylotic Myelopathy
Interventions
Diagnostic Test: MRI with DBSI technology
Registration Number
NCT03296592
Lead Sponsor
Washington University School of Medicine
Brief Summary

Patients who have been diagnosed with Cervical Spondylotic Myelopathy will be asked to undergo an MRI using diffusion basis spectrum imaging (DBSI) technology. The patients will have this MRI preoperatively and at 24 months postop. The investigators believe that with this imaging, biomarkers will be able to be seen to assist in prediction of long term outcomes in patients with spinal cord compression. These patients will be compared to healthy cohorts who will also undergo an MRI using the DBSI technology.

Detailed Description

CSM is the most common form of spinal cord injury and is the leading cause of progressive disability in patients over the age of 65. A major shortcoming limiting the clinical management of CSM is the lack of quantifiable metrics to 1) base clinical decisions and 2) predict potential for functional recovery following surgical intervention. DBSI MRI will provide imaging biomarkers to more reliably predict a patient's clinical course, response to therapy, and long-term prognosis.

Patients who are diagnosed with CSM will have an MRI using the DBSI technology preoperatively and at 24 months. Surgical patients will be assessed with the Neck Disability Index (NDI), Disability of the Arm, Shoulder and Hand (DASH), hand grip dynamometer and Manual Muscle Testing (MMT), the modified Japanese Orthopaedic Association scale (mJOA), and the Major Depression Inventory (MDI), the Short Form-36 (SF-36) and Nurick scoring.

A control group of healthy volunteers will have an MRI using the DBSI technology when enrolled and then again between 12-24 months later.

Recruitment & Eligibility

Status
ACTIVE_NOT_RECRUITING
Sex
All
Target Recruitment
71
Inclusion Criteria
  • History of ongoing spinal cord compression,
  • clinical evidence of CSM as determined by signs and symptoms including, but not limited to loss of manual dexterity, extremity weakness, sensory abnormalities, quadriparesis, loss of proprioception, and positive Babinski's or Hoffman's sign.
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Exclusion Criteria
  • pregnant
  • having an MRI incompatible device
  • having a known diagnosis of amyotrophic lateral sclerosis, multiple sclerosis, rheumatoid arthritis, concomitant thoracic and/or lumbar stenosis, spine tumor or HIV-related myelopathy and having systemic instability or being deemed unable to tolerate standard MRI sequencing.
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Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Arm && Interventions
GroupInterventionDescription
Control groupMRI with DBSI technologyHealthy volunteers aged 45-65 Visit 1: DBSI MRI Visit 2: 24 months after first MRI, patient will undergo the second MRI
Investigational subjectsMRI with DBSI technologyPatients who have been diagnosed with cervical spondylotic myelopathy and who will be undergoing surgical correction for this diagnosis. Visit 1 Investigational subjects will undergo a clinical assessment. Patients will undergo a DBSI MRI Visit 2. 6 months after surgery, investigational subjects will undergo a clinical assessment. Visit 3 12 months after surgery, investigational subjects will undergo a clinical assessment Visit 4 18 months after surgery, investigational subjects will undergo a clinical assessment. Visit 5 24 months after surgery, investigational subjects will undergo a clinical assessment and a DBSI MRI.
Primary Outcome Measures
NameTimeMethod
Accurate prediction of neurologic outcomes after surgery24 months

Outcome measure will assess spinal cord DBSI pathological metrics at baseline and at 24 months.

Secondary Outcome Measures
NameTimeMethod
Assessment of effects of blood flow deficits on spinal cord pathology24 months

Outcome measure will assess effects of blood flow deficits on spinal cord pathology and determine the accuracy of axonal loss quantification in CSM

Trial Locations

Locations (1)

Washington University

🇺🇸

St. Louis, Missouri, United States

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