Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
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.
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| MS |
| ||
| NMOSD |
| ||
| Control |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| MRI | Diagnostic Test | MRI examination |
|
| Measure | Description | Time Frame |
|---|---|---|
| Results of MRI data analysis | The baseline data of MS, nmosd and normal group were complete, and the number of cases completed follow-up according to the requirements reached the expected requirements (100 cases each), and met the statistical standards. | 2021-03-01-2022-06-30 |
Not provided
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
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.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Xaoyu Han | Contact | 18560081083 | 710804284@qq.com | |
| Anning Li | Contact | 18560080268 | anningli00@163.com |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D009103 | Multiple Sclerosis |
| D009471 | Neuromyelitis Optica |
| ID | Term |
|---|---|
| D020278 | Demyelinating Autoimmune Diseases, CNS |
| D020274 | Autoimmune Diseases of the Nervous System |
| D009422 | Nervous System Diseases |
| D003711 | Demyelinating Diseases |
Not provided
Not provided
Not provided
Not provided
Not provided
| D001327 | Autoimmune Diseases |
| D007154 | Immune System Diseases |
| D009188 | Myelitis, Transverse |
| D009902 | Optic Neuritis |
| D009901 | Optic Nerve Diseases |
| D003389 | Cranial Nerve Diseases |
| D005128 | Eye Diseases |