Neurodegener Dis. 2018;18(1):5-18. doi: 10.1159/000484248. Epub 2018 Jan 13.
Making use of multimodal data simultaneously to understand the neural mechanism of mild cognitive impairment (MCI) has been in the focus nowadays. The simultaneous use of multimodal data can take advantage of each modality which may only provide the view of one specific aspect of the brain.
To this end, the present study used structural magnetic resonance imaging (sMRI), fluorodeoxyglucose positron emission tomography (FDG-PET) and florbetapir PET to reveal the integrated brain network between MCI and normal controls (NCs).
In this study, 116 MCI, 116 NC and 116 Alzheimer disease (AD) subjects from the Alzheimer's Disease Neuroimaging Initiative were included for the evaluation of the brain covariance graphic model. Sparse inverse covariance estimation was utilized to get the graphic model.
The connections among different brain regions were quite different between NC and MCI or between MCI and AD subjects (p < 0.01). The number of connections, which were represented by the covariance among different brain regions in the graphic model, decreased from NC to MCI and then AD, especially in the temporal lobe, occipital-parietal lobe and parietal-temporal lobe.
These findings are good evidence to reveal the difference between MCI or AD and NC, and enhance the understanding of MCI.
利用多模态数据来同时理解轻度认知障碍（MCI）的神经机制已成为当前的研究热点。多模态数据的同时使用可以利用每种模态，而每种模态可能仅提供大脑特定方面的视图。
为此，本研究使用结构磁共振成像（sMRI）、氟脱氧葡萄糖正电子发射断层扫描（FDG-PET）和 florbetapir PET 来揭示 MCI 和正常对照组（NC）之间的综合脑网络。
本研究纳入了来自阿尔茨海默病神经影像学倡议的 116 名 MCI、116 名 NC 和 116 名 AD 患者，以评估脑协方差图形模型。使用稀疏逆协方差估计来获取图形模型。
NC 和 MCI 之间或 MCI 和 AD 患者之间的不同脑区之间的连接存在明显差异（p < 0.01）。图形模型中不同脑区之间的协方差表示的连接数量从 NC 到 MCI 再到 AD 逐渐减少，尤其是在颞叶、枕叶-顶叶和顶叶-颞叶。
这些发现为揭示 MCI 或 AD 与 NC 之间的差异提供了有力证据，并增强了对 MCI 的理解。
