Li Kaidi, Xie Dingling, Zhang Zhengyong, Fu Chunyu, Li Chunyang
Department of Neurology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China.
Inner Mongolia Regional Center for Neurological Disorders, Hohhot, China.
Front Aging Neurosci. 2025 Jun 25;17:1546977. doi: 10.3389/fnagi.2025.1546977. eCollection 2025.
This study aimed to investigate alterations in whole-brain cortical thickness (CT) and cortical and subcortical gray matter volume (GMV) in patients with Alzheimer's disease (AD) compared with healthy controls (HC) using voxel-based morphometry (VBM) and surface-based morphometry (SBM). Furthermore, we sought to develop a combined predictive model based on these neuroimaging markers and assess their potential clinical utility for the early detection and diagnosis of AD.
A total of 42 patients diagnosed with mild-to-moderate AD and 49 demographically matched HC were recruited for this study. VBM and SBM analyses were performed on three-dimensional T1-weighted magnetization-prepared rapid gradient echo (3D T1-MPRAGE) imaging sequences to identify brain regions that exhibited statistically significant differences between the AD and HC groups. Brain regions showing significant group differences were selected as the regions of interest (ROIs). Pearson's correlation analysis was used to assess the relationship between extracted neuroimaging metrics (CT, cortical GMV, and subcortical GMV) and cognitive performance. Predictive models were constructed using CT (from SBM), cortical GMV, and subcortical GMV (from VBM) metrics derived from ROIs, both individually and in combination. Model performance in discriminating between patients with AD and HCs was evaluated using a receiver operating characteristic (ROC) curve analysis.
Compared to HCs, patients with AD exhibited significant CT reductions primarily in the transverse temporal gyrus, superior temporal gyrus, supramarginal gyrus, insula, temporal pole, entorhinal cortex, and fusiform gyrus. Significant GMV reductions in patients with AD were observed predominantly in the hippocampus, parahippocampal gyrus, posterior temporal lobe, inferior temporal gyrus, middle temporal gyrus, limbic lobe structures, fusiform gyrus, amygdala, and thalamus, as detected by VBM analysis. Extracted CT, cortical GMV, and subcortical GMV measurements from the ROIs demonstrated significant positive correlations with both MMSE and MoCA scores.
In patients with AD, VBM and SBM showed overlapping cortical GMV and CT reductions. Volume/thickness reduction was correlated with lower MMSE/MoCA scores, confirming functional relevance. ROC analysis revealed that combining CT and GMV improved cognitive impairment prediction compared to single measures. This integrated approach may enhance clinical diagnosis and early risk identification of AD.
本研究旨在使用基于体素的形态学测量（VBM）和基于表面的形态学测量（SBM），调查与健康对照（HC）相比，阿尔茨海默病（AD）患者全脑皮质厚度（CT）以及皮质和皮质下灰质体积（GMV）的变化。此外，我们试图基于这些神经影像学标志物开发一个联合预测模型，并评估其在AD早期检测和诊断中的潜在临床效用。
本研究共招募了42例诊断为轻度至中度AD的患者和49例人口统计学匹配的HC。对三维T1加权磁化准备快速梯度回波（3D T1-MPRAGE）成像序列进行VBM和SBM分析，以识别AD组和HC组之间表现出统计学显著差异的脑区。显示出显著组间差异的脑区被选为感兴趣区域（ROI）。使用Pearson相关分析评估提取的神经影像学指标（CT、皮质GMV和皮质下GMV）与认知表现之间的关系。使用从ROI得出的CT（来自SBM）、皮质GMV和皮质下GMV（来自VBM）指标单独或联合构建预测模型。使用受试者工作特征（ROC）曲线分析评估模型区分AD患者和HC的性能。
与HC相比，AD患者主要在颞横回、颞上回、缘上回、岛叶、颞极、内嗅皮质和梭状回出现显著的CT降低。通过VBM分析检测到，AD患者主要在海马体、海马旁回、颞叶后部、颞下回、颞中回、边缘叶结构、梭状回、杏仁核和丘脑出现显著的GMV降低。从ROI提取的CT、皮质GMV和皮质下GMV测量值与MMSE和MoCA评分均呈显著正相关。
在AD患者中，VBM和SBM显示出皮质GMV和CT降低存在重叠。体积/厚度降低与较低的MMSE/MoCA评分相关，证实了功能相关性。ROC分析显示，与单一测量相比，联合CT和GMV可改善对认知障碍的预测。这种综合方法可能会增强AD的临床诊断和早期风险识别。
