Application of Multiparametric Structural and Functional MRI in Unraveling the Substrates of Cognitive Impairment and Disability in Multiple Sclerosis

NCT ID: NCT06653283

Last Updated: 2024-10-22

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Total Enrollment: 104 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2024-10-20
• Study Completion Date: 2025-12-30

Brief Summary

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.

Detailed Description

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.

Conditions

Multiple Sclerosis

Study Design

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

Study Groups

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.

No interventions assigned to this group

Eligibility Criteria

Inclusion Criteria

• o be included, they had to be (1) right-handed, (2) ≥ 18 years old

Exclusion Criteria

• without neurological and psychological symptoms or a history of neuropsychological disorders were also included in the study.

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Zhuo Wang

OTHER

Sponsor Role: lead

Responsible Party

Zhuo Wang

Department of Magnetic Resonance

Responsibility Role: SPONSOR_INVESTIGATOR

Locations

MRI

Lanzhou, Gansu, China

Countries

China

Central Contacts

zhuo wang

Role: CONTACT

2892904774@qq.com

18142618122

Facility Contacts

Zhuo Wang, Doctor

Role: primary

2892904774@qq.com

18142618122

Other Identifiers

21JR7RA438

Identifier Type: OTHER

Identifier Source: secondary_id

2024A-1077

Identifier Type: -

Identifier Source: org_study_id