Diffusion MRI in Cervical Spondylotic Myelopathy

NCT ID: NCT04952831

Last Updated: 2021-07-07

Basic Information

• Recruitment Status: UNKNOWN
• Total Enrollment: 200 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2020-09-01
• Study Completion Date: 2024-09-01

Brief Summary

diffusion MRI in evaluates and predicts prognosis in CSM

Detailed Description

Cervical spondylotic myelopathy (CSM) is a spinal dysfunction disease common in the elderly population caused by cervical spine degeneration, spinal canal stenosis, and spinal cord compression. It may result in reduced quality of life or even disability. With the increased life expectancy of today's population, the incidence of CSM is increasing. Surgery is recommended to reduce compression of the spinal cord. However, due to individual differences and variations in spinal cord injury severity, the prognosis after surgery is often unpredictable. Therefore, proper evaluation of spinal cord function and prognosis prediction are important considerations for the clinical decision of whether to operate and selection of appropriate operation time. To achieve this goal, medical images are used to correctly evaluate the damage and recovery potential of neurons. Magnetic resonance imaging (MRI) provides spinal cord macrostructure details and can detect spinal cord damage. Clinically, conventional MRI is often used to confirm a CSM diagnosis and predict prognosis. However, MRI assessments, including increased signal intensity (ISI) and T1 hypo-intensity, might not be consistent with clinical manifestations or prognostic expectations.

Diffusion MRI (dMRI) enables early diagnoses and prognostic predictions due to its microstructure assessment advantages. The diffusion of water molecules is restricted due to structural barriers, such as axon membranes and myelin sheaths. Using the microscopic movement of water molecules, dMRI can detect microstructures indirectly using a model with specific underlying probability distribution function of diffusion. Three models are widely applied clinically: diffusion tensor imaging (DTI), diffusional kurtosis imaging (DKI), and neurite orientation dispersion and density imaging (NODDI). DTI assumes the diffusion distribution function to be Gaussian, DKI assumes it to be non-Gaussian, and NODDI assumes it to be multi-compartmental (intracellular pool, extracellular pool, and free water). Previous studies suggested the potential application value of DTI and DKI in patients with CSM; however, these models had limited specificity and were not sufficient to diagnose CSM in a clinical setting. Compared with DTI and DKI, NODDI has been shown to characterize spinal cord microstructure better.

Conditions

Cervical Spondylotic Myelopathy

Study Design

• Observational Model Type: CASE_CONTROL
• Study Time Perspective: PROSPECTIVE

Study Groups

Patients with mild CSM

mJOA score ≥15

diffusion MRI (dMRI)

Intervention Type: OTHER

All participants underwent dMRI scan at baseline

Patients with moderate CSM

mJOA score 13\~14

diffusion MRI (dMRI)

Intervention Type: OTHER

All participants underwent dMRI scan at baseline

Patients with severe CSM

mJOA score ≤ 12

diffusion MRI (dMRI)

Intervention Type: OTHER

All participants underwent dMRI scan at baseline

Controls

health volunteers

diffusion MRI (dMRI)

Intervention Type: OTHER

All participants underwent dMRI scan at baseline

Interventions

diffusion MRI (dMRI)

All participants underwent dMRI scan at baseline

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• ages ranged 30-75
• compliance to MRI scan
• no MRI contraindication
• (Patients) clinical diagnosis of CSM and surgery in our hospital
• (Healthy controls) no spinal cord dysfunction

Exclusion Criteria

• prior head or neck surgery or accompanying diseases with neurologic deficits and/or symptoms including multiple sclerosis, spinal cord injury, motor neuron disease, or spinal cord tumour
• images with motion artifact

• Minimum Eligible Age: 30 Years
• Maximum Eligible Age: 75 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Peking University Third Hospital

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Huishu Yuan, Dr

Role: PRINCIPAL_INVESTIGATOR

Peking University Third Hospital

Locations

Peking University Third Hospital

Beijing, Beijing Municipality, China

Countries

China

Other Identifiers

M2020408

Identifier Type: -

Identifier Source: org_study_id