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| ID | Type | Description | Link |
|---|---|---|---|
| 21JR7RA438 | Other Identifier | Gansu Province Clinical Research Center for Functional and Molecular Imaging |
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Multiple sclerosis (MS) is a disabling inflammatory demyelinating disease of the nervous system that predominantly affects white matter, because of its complicated pathogenesis, and overlapping clinical manifestations with other inflammatory demyelinating diseases diseases, which compromises clinical diagnosis and assessment for some patients at an early stage, leading to delayed treatment. Therefore, the development and validation of simple, non-invasive, accurate biomarkers becomes an urgent need. Neurite orientation dispersion and density imaging (NODDI) is an advanced diffusion model applied to quantify the extent of neurite destruction, allowing early assessment of the integrity of brain white matter microstructure. Many previous studies have shown that diffusion tensor imaging (DTI) can reflect the damage caused by MS, but it cannot accurately describe the true course of fiber bundles, such as curved and crossed fiber bundles. In addition, most of the studies are cross-sectional and lack of longitudinal follow-up. In this study, NODDI technique was used to investigate the damage pattern of white matter microstructural integrity in the early stage of multiple sclerosis for early diagnosis and differential diagnosis. In addition, to evaluate the relationship between NODDI parameters and clinical disability and cognitive impairment in MS, reveal the relationship between the pattern of white matter microstructural integrity damage and the severity of the disease to improve the understanding of the pathophysiological mechanisms of clinical disability and cognitive impairment, and provide potential therapeutic targets. To search for imaging biomarkers that can assess/predict disability progression and cognitive deterioration in patients with MS. Based on the above results, we can then propose a comprehensive and individualized model for the initial diagnosis, progression and clinical prognosis in patients with MS.
Multiple sclerosis (MS) is a disabling inflammatory demyelinating disease of the nervous system that predominantly affects white matter, because of its complicated pathogenesis, and overlapping clinical manifestations with other inflammatory demyelinating diseases diseases, which compromises clinical diagnosis and assessment for some patients at an early stage, leading to delayed treatment. Therefore, the development and validation of simple, non-invasive, accurate biomarkers becomes an urgent need. Neurite orientation dispersion and density imaging (NODDI) is an advanced diffusion model applied to quantify the extent of neurite destruction, allowing early assessment of the integrity of brain white matter microstructure. Many previous studies have shown that diffusion tensor imaging (DTI) can reflect the damage caused by MS, but it cannot accurately describe the true course of fiber bundles, such as curved and crossed fiber bundles. In addition, most of the studies are cross-sectional and lack of longitudinal follow-up. In this study, NODDI technique was used to investigate the damage pattern of white matter microstructural integrity in the early stage of multiple sclerosis for early diagnosis and differential diagnosis. In addition, to evaluate the relationship between NODDI parameters and clinical disability and cognitive impairment in MS, reveal the relationship between the pattern of white matter microstructural integrity damage and the severity of the disease to improve the understanding of the pathophysiological mechanisms of clinical disability and cognitive impairment, and provide potential therapeutic targets. To search for imaging biomarkers that can assess/predict disability progression and cognitive deterioration in patients with MS. Based on the above results, we can then propose a comprehensive and individualized model for the initial diagnosis, progression and clinical prognosis in patients with MS.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| 60 patients with RRMS and 44 age- and sex-matched healthy controls | A total of 104 participants, including 44 healthy controls (HCs) and 60 patients diagnosed with relapsing-remitting multiple sclerosis (RRMS) based on the 2017 revised McDonald criteria (Thompson AJ), were enrolled for this study. To be included, they had to be (1) right-handed, (2) ≥ 18 years old, (3) relapse- and steroid-free for at least 1 month before MRI acquisition, (4) conducting a stable disease-modifying treatment for at least 3 months. The exclusion criteria were as follows: (1) sleep disorder or taking medication for sleep, (2) a history of stroke, epilepsy, head trauma, and cerebral small vessel diseases, (3) neuropsychological or psychiatric disorders, (4) neuromyelitis optica spectrum disorders and myelin oligodendrocyte glycoprotein antibody-associated disease. 44 age- and sex-matched HCs without neurological and psychological symptoms or a history of neuropsychological disorders were also included in the study. |
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| Measure | Description | Time Frame |
|---|---|---|
| DTI-ALPS CPV | diffusion tensor image analysis along the perivascular space (DTI-ALPS) choroid plexus volume | one year |
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Inclusion Criteria:
Exclusion Criteria:
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44 age- and sex-matched HCs without neurological and psychological symptoms or a history of neuropsychological disorders were also included in the study.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| zhuo wang | Contact | 18142618122 | 2892904774@qq.com |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| MRI | Lanzhou | Gansu | 730030 | China |
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| ID | Term |
|---|---|
| D009103 | Multiple Sclerosis |
| D060825 | Cognitive Dysfunction |
| ID | Term |
|---|---|
| D020278 | Demyelinating Autoimmune Diseases, CNS |
| D020274 | Autoimmune Diseases of the Nervous System |
| D009422 | Nervous System Diseases |
| D003711 | Demyelinating Diseases |
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| D001327 | Autoimmune Diseases |
| D007154 | Immune System Diseases |
| D003072 | Cognition Disorders |
| D019965 | Neurocognitive Disorders |
| D001523 | Mental Disorders |