ORIGINAL RESEARCH article
Front. Aging Neurosci.
Sec. Alzheimer's Disease and Related Dementias
Volume 17 - 2025 | doi: 10.3389/fnagi.2025.1546977
This article is part of the Research TopicAdvancing Early Alzheimer's Detection Through Multimodal Neuroimaging TechniquesView all 8 articles
Voxel-based and surface-based morphometry in the cortical thickness, and cortical and subcortical grey matter volume in patients with mild to moderate Alzheimer's disease
Provisionally accepted- 1Department of Neurology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia Autonomous Region, China
- 2The Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia Autonomous Region, China
- 3Xianning Central Hospital, Xianning, Hubei, China
- 4Xinxiang Medical University, Xinxiang, Henan Province, China
- 5Mental Health Center of Inner Mongolia, Hohhot, Inner Mongolia Autonomous Region, China
- 6Inner Mongolia Brain Hospital, Huhhot, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Aim: This study aimed to investigate alterations in whole-brain cortical thickness (CT) and both cortical and subcortical grey matter volume (GMV) in patients with Alzheimer's disease (AD) compared to healthy controls (HC) using voxel-based morphometry (VBM) and surfacebased morphometry (SBM). Furthermore, we sought to develop a combined predictive model based on these neuroimaging markers and assess its potential clinical utility for the early detection and diagnosis of AD.Methods: A total of 42 patients diagnosed with mild-to-moderate AD and 49 demographicallymatched HC were recruited for this study. VBM and SBM analyses were performed on threedimensional T1-weighted magnetization-prepared rapid gradient echo (3D T1-MPRAGE) imaging sequences to identify brain regions exhibiting statistically significant differences between the AD and HC groups. Brain regions showing significant group differences were selected as regions of interest (ROIs). Pearson correlation analysis was employed to assess the relationship between the extracted neuroimaging metrics (CT, cortical GMV, subcortical GMV) and cognitive performance. Predictive models were constructed using CT (from SBM), cortical GMV, and subcortical GMV (from VBM) metrics derived from the ROIs, both individually and in combination. Model performance in discriminating between AD patients and HCs was evaluated using receiver operating characteristic (ROC) curve analysis.Results: Compared to HCs, AD patients 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 AD patients 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 measures from the ROIs demonstrated significant positive correlations with both MMSE and MoCA scores.SBM and VBM in brain atrophy with AD 3 Conclusion:In AD patients, VBM and SBM showed overlapping cortical GMV and CT reductions. Volume/thickness reductions correlated with lower MMSE/MoCA scores, confirming functional relevance. ROC analysis revealed that combining CT and GMV improved cognitive impairment prediction over single measures. This integrated approach may enhance clinical AD diagnostics and early risk identification.
Keywords: SBM, VBM, grey matter volume (gmv), cortical thickness (CT), Alzheimer's disease
Received: 17 Dec 2024; Accepted: 03 Jun 2025.
Copyright: © 2025 Li, Xie, Zhang, Fu and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Chunyang Li, Mental Health Center of Inner Mongolia, Hohhot, 010010, Inner Mongolia Autonomous Region, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.