Clinical trial NCT04822623: Imaging Evaluation of Central Nervous Autoimmune Diseases
Official title: Computer Aided Imaging Evaluation of Central Nervous System Autoimmune Diseases
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: MS (Multiple Sclerosis)
NMO Spectrum Disorder
Lead sponsor: Qilu Hospital of Shandong University
Sponsor class: OTHER
First posted: 2021-03-30
Enrollment: 300
Sex: ALL
Minimum age (years): 18
Maximum age (years): 65
Standard ages: ADULT
OLDER_ADULT
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: The patients in MS group and nmosd group were recruited from the Department of Neurology (outpatient and inpatient); the volunteers in control group were recruited through subject recruitment advertisement.

Brief summary: Multiple sclerosis (MS) is the most common demyelinating disease of the central nervous system and the most common cause of non traumatic disability in young and middle-aged people. Neuromyelitis optica spectrum disease (nmosd) is an independent disease different from Ms. the pathogenesis and the mode of brain and spinal cord injury are different from MS, and the prognosis and optimal treatment are different. It is difficult to distinguish the two diseases in the early stage. Early diagnosis and treatment of the two diseases can greatly improve the quality of life of patients. Therefore, it is an urgent problem to clarify the difference between MS and nmosd injury patterns and to find sensitive imaging markers for early clinical intervention. With the continuous progress of computer aided diagnosis (CAD), it is more and more widely used in medicine, which is expected to help solve the above problems.

The purpose of this study is to create a neuroimmune disease evaluation database based on image data. By combining brain and spinal cord imaging, and based on Zhang quantum space learning computer-aided technology, we can achieve accurate segmentation of MS and nmosd brain and spinal cord lesions, analyze the evolution characteristics of the disease at different time points, and screen the imaging indexes related to clinical scores combined with clinical and laboratory indexes Objective: to determine the different prognosis and its influencing factors at the clinical, imaging and molecular levels, and establish the model for predicting disease progression and prognosis, so as to provide the basis for early identification and assistance in guiding treatment and judging prognosis.

Clinical information was collected: age, gender, course of disease, MMSE, EDSS disability score, nine hole test, 25 foot walking test. Assess the patient's information processing ability. Blood samples were collected. Imaging examination was performed. The patients were followed up regularly.


Eligibility criteria: Inclusion Criteria:

1. 18-65 years old;
2. Nmosd was diagnosed according to wingerchuk standard revised in 2015, MS was diagnosed according to McDonald standard revised in 2017, and 100 normal people were diagnosed;
3. In the acute stage, within 1 month of the onset or stable stage, there was no GD enhanced lesion on MRI, and EDSS score had no significant change within 6 months, which was more than 1 month from the last attack;
4. MRI examination was complete: baseline, 6 months, 1 year, 2 years;
5. Sign informed consent.

Exclusion Criteria:

1. The course of disease was more than 30 years;
2. History of brain injury or spinal cord injury;
3. History of central nervous system infection or immunodeficiency syndrome;
4. HBV, HCV patients, syphilis, HIV-1, HIV-2 patients;
5. Suffering from mental illness;
6. Pregnant and lactating women or patients planning to conceive within one year;
7. Unable to cooperate to complete the follow-up due to geographical or other reasons;
8. Patients also participated in other randomized controlled trials.

Primary outcomes:
measure: Results of MRI data analysis
timeFrame: 2021-03-01-2022-06-30
Secondary outcomes:
Other outcomes:
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