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