视神经脊髓炎和多发性硬化深部灰质损伤的多模态MRI研究

Neuromyelitis optica (NMO) and multiple sclerosis (MS) are the most common demyelinating diseases of central nervous system, which burdens patients and society. Previous studies found that gray matter damage was more relevant with clinical disability and cognitive impair than white matter lesions. Thalamus is a key part in studies of gray matter. In this study, we plan to collect 50 patients with NMO, 50 patients with MS, and 50 healthy volunteers. Clinical information are fulfilled and MRI data are acquired, including conventional MRI, three- dimentional structural images, diffusion tensor image (DTI), and resting-state functional MRI(f MRI). We will use noval probabilistic tractography algorithm with DTI data to identify specific connections between human thalamus and cortex. Then thalamus will be segmented to seven subregions. Diffusion indices will be measured and fiber connectivity between subregions of thalamus and cortex will be tracted. On registration templates of segmented subregions in fMRI, we will analyze the functional connectivity between subregions of thalamus and cortex in three groups. Comparing the structural and functional connectivity indices among the three groups, we will presume the possible pathophysiology mechanisms in thalamus in NMO and MS. Correlations between structural and functional indices and clinical scores, disease duration and brain lesions will be further proformed, which provides important information of early evaluation and best treatment options.

视神经脊髓炎(NMO)和多发性硬化(MS)是中枢神经系统最常见的脱髓鞘疾病，给患者家庭和社会带来沉重的负担。研究发现MS灰质损伤比白质病灶更能准确反映患者残疾程度，而丘脑是灰质损伤研究中的关键部位。本项目拟收集NMO、MS患者和健康志愿者各50例，获取患者的临床资料和磁共振扫描数据，包括常规序列、三维结构像、弥散张量成像(DTI)及静息态功能磁共振成像(fMRI)。应用DTI纤维束追踪技术的自动概率算法将丘脑分割为7个亚区，测量NMO、MS组和正常对照组丘脑亚区的弥散指标，分析丘脑亚区的纤维束连接情况；并将分割的亚区模板配准到fMRI上，分析丘脑亚区的功能连接情况，最后得出三组病例丘脑亚区的结构和功能连接参数，并比较其异同，推测NMO和MS丘脑损伤可能的病理生理机制。将丘脑结构和功能连接的指标与临床评分、病程、脑内病灶体积等做相关分析，为临床早期评估、制定最优治疗方案提供重要依据。

视神经脊髓炎(NMO)和多发性硬化(MS)是中枢神经系统最常见的脱髓鞘疾病，给患者家庭和社会带来沉重的负担。研究发现MS灰质损伤比白质病灶更能准确反映患者残疾程度，而丘脑是灰质损伤研究中的关键部位。研究收集了52例NMO、54例MS患者和51例健康志愿者(HC)的临床资料和MRI常规序列、三维结构像、弥散张量成像及静息态功能磁共振成像。应用纤维束追踪技术的自动概率算法将丘脑分割为7个亚区，测量NMO、MS组和HC全脑和丘脑亚区的结构和功能指标差异。并将丘脑结构和功能连接的指标与临床评分、病程、脑内病灶体积等做相关分析。结果发现MS结构改变以脑萎缩为主，而NMO以脊髓萎缩为主。MS全脑和局部功能网络效率即使在疾病早期也存在异常。MS和NMO丘脑整体和各亚区均发生萎缩(MS丘脑体积0.244；NMO 0.297; HC 0.329; P < 0.001)，和弥散异常(MS分数各向异性 0.293; NMO 0.323;HC 0.355; P < 0.001)，但MS的异常改变程度更重。丘脑是MS功能连接的重要节点，但不是NMO功能连接的重要节点。MS脑萎缩、NMO脊髓萎缩与临床残疾进展相关，而NMO丘脑萎缩及丘脑弥散指标异常与临床认知损伤相关。结论：MS和NMO丘脑结构损伤模式相似，但与NMO功能连接模式不同的是，丘脑是MS功能连接的重要节点。MS丘脑萎缩可以预测临床残疾进展，而NMO丘脑萎缩是预测认知损伤的重要指标。