目的利用基于体素的形态学研究方法比较复发缓解型多发性硬化(relapsing—remitting multiple sclerosis,RRMS)患者和健康志愿者局部脑灰质的体积差异,推断灰质体积变化可能的病理生理机制。方法对32例RRMS患者和32名性别、年龄匹配的健康志愿者进行常规MRI和三维T1WI扫描,采用参数统计软件包SPM5进行图像后处理,对RRMS组及对照组数据进行基于体素的统计学比较。利用相关分析检测患者灰质体积的变化与疾病病程、临床残疾程度及脑内可见病灶体积的相关性。结果与对照组相比,RRMS患者的灰质萎缩区域分布广泛,在两侧丘脑(左侧2031,右侧1711)、尾状核(左侧815,右侧1031)、海马旁回(左侧313,右侧467)及额、颞、顶、枕叶多个皮质区域,灰质体积差异具有统计学意义(t=8.853—11.163,校正后均P〈0.01)。RRMS患者两侧丘脑(左侧r=-0.596,右侧r=-0.694)和右侧尾状核(r=-0.409)的体积与脑内可见病灶的体积呈显著负相关(均P〈0.05)。结论RRMS患者灰质萎缩具有分布广泛的特征,尤其在深部灰质更显著。灰质萎缩的关键机制可能是继发于脑内可见病灶的神经元或轴索变性。
Objective To investigate the feature of regional grey matter volume changes in relapsing-remitting multiple sclerosis (RRMS) patients by voxel-based morphometry (VBM) and presume the possible pathophysiological basis. Methods Conventional magnetic resonance imaging (MRI) and TL - weighted three-dimensional MRI were obtained from 32 RRMS and 32 sex- and age-matched normal controls. The comparison of grey matter volume between the two groups was analyzed by statistical analysis software SPM5 and VBM. A Pearson correlational analysis was used to assess correlation between grey matter loss and disease duration, expanded disability status scale (EDSS) and visible brain lesion volume. Results Compared with normal controls, RRMS patients had extensive bilateral grey matter atrophy in thalami (left 2031 and fight 1711 ), caudate (left 815 and right 1031 ) and parahippocampal gyrus (left 313 and right 467), as well as several cortical regions in frontal, temporal, parietal, and occipital lobes (t value were between 8. 853 and 11. 163, all P 〈 0. 01 ). Regional grey matter loss in bilateral thalami ( r value were - 0. 596 on left and were - 0. 694 on fight ) and fight caudate ( r = - 0. 409 ) were strongly negatively correlated with visible brain lesion volume in RRMS ( all P 〈 0. 05 ). Conclusions By means of VBM, extensive grey matter atrophy are found in RRMS patients, especially in deep grey matter. Axonal degeneration secondary to visible brain lesions may be a key pathogenesis of grey matter atrophy in RRMS.