复发缓解型多发性硬化患者默认网络亚区成本整合初探
发布时间：2018-11-19 16:22
【摘要】：目的采用图论衍生的成本整合(CI)分析对复发缓解型多发性硬化(RRMS)患者默认网络(DMN)亚区间(内)相互关系进行研究。方法采集24例处于缓解期的RRMS患者及相同数量健康对照组静息态功能磁共振(R-f MRI)和高分辨率T1WI数据。R-f MRI数据处理助手(DPARSFA)基于Matlab2012a平台进行数据预处理,提取DMN核心和双侧亚系统区20个感兴趣区信号,Pearson相关计算功能连接系数为边,计算并比较两组维持网络不碎裂条件下,DMN亚区间(内)的CI值的改变,及与临床参数如临床扩展残疾量表(EDSS)、同步听觉连续加法测验评分(PASAT)、脑实质分数(BPF)、T2WI可见病灶体积和病程的相关性。结果最小网络密度(Dmin)条件下,RRMS患者DMN功能网络左侧颞中叶(MTL)亚系统区成本整合(0.80 vs.0.30)较对照组显著增高(P=0.006),且和BPF之间呈负相关(r=-0.414,P=0.045)。结论处于缓解期的RRMS患者,存在和脑萎缩相关的DMN亚区成本整合增高改变。该方法为理解疾病状态下的功能整合机制提供了新的视角。
[Abstract]:Objective to study the relationship between default network (DMN) subinterval (internal) of recurrent multiple sclerosis (RRMS) patients with relapsed multiple sclerosis (RMS) by means of graph derived cost integration (CI) analysis. Methods resting functional magnetic resonance imaging (R-f MRI) and high-resolution T1WI data were collected from 24 patients with RRMS in remission and the same number of healthy controls. R-f MRI data processing assistant (DPARSFA) was used for data preprocessing based on Matlab2012a platform. DMN core and bilateral sub-system signals of 20 regions of interest were extracted, and the functional connection coefficient of Pearson correlation was calculated as edge. The changes of CI value of DMN subinterval (inner) were calculated and compared under the condition of maintaining the network without fragmentation. And its correlation with clinical parameters, such as clinical extended disability scale (EDSS), simultaneous auditory continuous addition test (PASAT), brain parenchyma score (BPF), T2WI), lesion volume and course of disease. Results under the condition of minimal network density (Dmin), the cost integration of (MTL) subsystem in the left temporal middle temporal lobe of DMN patients with RRMS was significantly higher than that in the control group (P0. 006). There was a negative correlation with BPF (r = 0.414, P < 0. 045). Conclusion in patients with RRMS in remission period, the cost integration of DMN subregion associated with brain atrophy is increased. This method provides a new perspective for understanding the mechanism of functional integration in disease state.
【作者单位】： 南昌大学第一附属医院影像科 江西省医学影像研究所;南昌市第二医院肿瘤科;
【基金】：国家自然科学基金(编号:81060116,81101041,81260217) 江西省科技支撑计划项目(编号:20111BBG70028-1) 江西省青年自然科学基金(编号:2013BAB215008)
【分类号】：R744.51;R445.2
[Abstract]:Objective to study the relationship between default network (DMN) subinterval (internal) of recurrent multiple sclerosis (RRMS) patients with relapsed multiple sclerosis (RMS) by means of graph derived cost integration (CI) analysis. Methods resting functional magnetic resonance imaging (R-f MRI) and high-resolution T1WI data were collected from 24 patients with RRMS in remission and the same number of healthy controls. R-f MRI data processing assistant (DPARSFA) was used for data preprocessing based on Matlab2012a platform. DMN core and bilateral sub-system signals of 20 regions of interest were extracted, and the functional connection coefficient of Pearson correlation was calculated as edge. The changes of CI value of DMN subinterval (inner) were calculated and compared under the condition of maintaining the network without fragmentation. And its correlation with clinical parameters, such as clinical extended disability scale (EDSS), simultaneous auditory continuous addition test (PASAT), brain parenchyma score (BPF), T2WI), lesion volume and course of disease. Results under the condition of minimal network density (Dmin), the cost integration of (MTL) subsystem in the left temporal middle temporal lobe of DMN patients with RRMS was significantly higher than that in the control group (P0. 006). There was a negative correlation with BPF (r = 0.414, P < 0. 045). Conclusion in patients with RRMS in remission period, the cost integration of DMN subregion associated with brain atrophy is increased. This method provides a new perspective for understanding the mechanism of functional integration in disease state.
【作者单位】： 南昌大学第一附属医院影像科 江西省医学影像研究所;南昌市第二医院肿瘤科;
【基金】：国家自然科学基金(编号:81060116,81101041,81260217) 江西省科技支撑计划项目(编号:20111BBG70028-1) 江西省青年自然科学基金(编号:2013BAB215008)
【分类号】：R744.51;R445.2
【共引文献】
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