Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China.
School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, Guangdong, China.
Curr Alzheimer Res. 2018;15(12):1151-1160. doi: 10.2174/1567205015666180813145935.
In this study, we investigated the influence that the pathology of Alzheimer's disease (AD) exerts upon the corpus callosum (CC) using a total of 325 mild cognitive impairment (MCI) subjects, 155 AD subjects, and 185 healthy control (HC) subjects.
Regionally-specific morphological CC abnormalities, as induced by AD, were quantified using a large deformation diffeomorphic metric curve mapping based statistical shape analysis pipeline. We also quantified the association between the CC shape phenotype and two cognitive measures; the Mini Mental State Examination (MMSE) and the Alzheimer's Disease Assessment Scale-Cognitive Behavior Section (ADAS-cog). To identify AD-relevant areas, CC was sub-divided into three subregions; the genu, body, and splenium (gCC, bCC, and sCC).
We observed significant shape compressions in AD relative to that in HC, mainly concentrated on the superior part of CC, across all three sub-regions. The HC-vs-MCI shape abnormalities were also concentrated on the superior part, but mainly occurred on bCC and sCC. The significant MCI-vs-AD shape differences, however, were only detected in part of sCC. In the shape-cognition association, significant negative correlations to ADAS-cog were detected for shape deformations at regions belonging to gCC and sCC and significant positive correlations to MMSE at regions mainly belonging to sCC.
Our results suggest that the callosal shape deformation patterns, especially those of sCC, linked tightly to the cognitive decline in AD, and are potentially a powerful biomarker for monitoring the progression of AD.
在这项研究中，我们共纳入 325 例轻度认知障碍（MCI）患者、155 例阿尔茨海默病（AD）患者和 185 例健康对照（HC），采用基于全脑形态学的大变形弥散张量成像配准方法，探讨 AD 病理对胼胝体（CC）的影响。
采用基于大变形弥散张量成像配准方法的统计形状分析管道，量化 AD 引起的 CC 区域特异性形态异常。我们还量化了 CC 形态表型与两种认知测量之间的关系，即简易精神状态检查（MMSE）和阿尔茨海默病评估量表认知行为部分（ADAS-cog）。为了识别与 AD 相关的区域，我们将 CC 分为三个亚区：膝部、体部和压部（gCC、bCC 和 sCC）。
与 HC 相比，AD 患者的 CC 形状明显压缩，主要集中在 CC 的上半部分，在三个亚区均如此。与 HC 相比，MCI 患者的 CC 形态异常也主要集中在上半部分，但主要发生在 bCC 和 sCC。然而，与 MCI 相比，AD 患者的 CC 形态差异仅在部分 sCC 区显著。在认知关联分析中，与 ADAS-cog 呈显著负相关的是 gCC 和 sCC 区域的形态变形，与 MMSE 呈显著正相关的主要是 sCC 区域的形态变形。
我们的研究结果表明，CC 的形态变形模式，特别是 sCC 的形态变形模式，与 AD 认知下降密切相关，可能是监测 AD 进展的有力生物标志物。
