Clinical trial NCT04952831: Diffusion MRI in Cervical Spondylotic Myelopathy
Official title: Utilization of Diffusion Magnetic Resonance Imaging (dMRI) in Evaluation of Spinal Cord Dysfunction and Prognosis in Patients With Cervical Spondylotic Myelopathy (CSM)
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Cervical Spondylotic Myelopathy
Lead sponsor: Peking University Third Hospital
Sponsor class: OTHER
First posted: 2021-07-07
Enrollment: 200
Sex: ALL
Minimum age (years): 30
Maximum age (years): 75
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_CONTROL
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The patients come from the Peking University Third Hospital. Healthy volunteers come from online recruitment.

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.

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

Primary outcomes:
measure: Postoperative neurologic improvement
timeFrame: 3-month, 6-month, 12-month, and 24-month
measure: diagnosis of CSM
timeFrame: at baseline
Secondary outcomes:
Other outcomes:
Locations:
city: Beijing
country: China
facility: Peking University Third Hospital
state: Beijing
Study officials:
affiliation: Peking University Third Hospital
name: Huishu Yuan, Dr
role: PRINCIPAL_INVESTIGATOR
References: