Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, Falmer, UK Scientific Department, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy.
Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, Falmer, UK.
J Alzheimers Dis. 2014;40(1):213-20. doi: 10.3233/JAD-131766.
We investigated changes in functional network architecture in amnestic mild cognitive impairment using graph-based analysis of task-free functional magnetic resonance imaging and fine cortical parcellation. Widespread disconnection was observed primarily in cortical hubs known to manifest early Alzheimer's disease pathology, namely precuneus, parietal lobules, supramarginal and angular gyri, and cuneus, with additional involvement of subcortical regions, sensorimotor cortex and insula. The connectivity changes determined using graph-based analysis significantly exceed those detected using independent component analysis both in amplitude and topographical extent, and are largely decoupled from the presence of overt atrophy. This superior ability of graph-based analysis to detect disease-related disconnection highlights its potential use in the determination of biomarkers of early dementia. Graph-based analysis source code is provided as supplementary material.
我们使用基于图的分析方法和精细的皮质分割对任务态功能磁共振成像数据进行分析,以研究遗忘型轻度认知障碍患者的功能网络结构变化。研究发现,广泛的连接中断主要发生在已知早期表现出阿尔茨海默病病理的皮质中枢,即楔前叶、顶叶叶、缘上回和角回,以及扣带回,此外还涉及皮质下区域、感觉运动皮层和岛叶。基于图的分析方法确定的连接变化在幅度和拓扑范围上均显著超过独立成分分析检测到的变化,并且与明显的萎缩无关。基于图的分析方法在检测与疾病相关的连接中断方面具有优越的能力,这突出了其在确定早期痴呆症生物标志物方面的潜在用途。基于图的分析源代码作为补充材料提供。