Cortical and subcortical gray matter abnormalities in mild cognitive impairment

被引:0
|
作者
Wang, Junxia [1 ]
Liang, Xue [1 ]
Lu, Jiaming [1 ]
Zhang, Wen [1 ]
Chen, Qian [1 ]
Li, Xin [1 ]
Chen, Jiu [1 ]
Zhang, Xin [1 ]
Zhang, Bing [1 ,2 ]
机构
[1] Nanjing Univ, Affiliated Drum Tower Hosp, Med Sch, Dept Radiol, Nanjing 210008, Peoples R China
[2] Nanjing Univ, Inst Med Imaging & Artificial Intelligence, Nanjing 210008, Peoples R China
基金
中国国家自然科学基金;
关键词
Mild cognitive impairment; Structural magnetic resonance imaging; Morphometric alterations; Cognitive assessment; Support vector machine; ALZHEIMERS-DISEASE; VENTRICULAR STRUCTURES; SHAPE ABNORMALITIES; DEMENTIA; MRI; HIPPOCAMPAL; THICKNESS; MANAGEMENT; PATTERN; CORTEX;
D O I
10.1016/j.neuroscience.2024.07.036
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Gray matter changes are thought to be closely related to cognitive decline in mild cognitive impairment (MCI) patients. The study aimed to explore cortical and subcortical structural alterations in MCI and their association with cognitive assessment. 24 MCI patients and 22 normal controls (NCs) were included. Voxel-based morphometry (VBM), vertex-based shape analysis and surface-based morphometry (SBM) analysis were applied to explore subcortical nuclei volume, shape and cortical morphology. Correlations between structural changes and cognition were explored using spearman correlation analysis. Support vector machine (SVM) classification evaluated MCI identification accuracy. MCI patients showed significant atrophy in the left thalamus, left hippocampus, left amygdala, right pallidum, right hippocampus, along with inward deformation in the left amygdala. SBM analysis revealed that MCI group exhibited shallower sulci depth in the left hemisphere and increased cortical gyrification index (GI) in the right frontal gyrus. Correlation analysis showed the positive correlation between right hippocampus volume and episodic memory, while negative correlation between the altered GI and memory performance in MCI group. SVM analysis demonstrated superior performance of sulci depth and GI derived from SBM in MCI identification. When combined with cortical and subcortical metrics, SVM achieved a peak accuracy of 89 % in distinguishing MCI from NC. The study reveals significant gray matter structural changes in MCI, suggesting their potential role in underlying functional differences and neural mechanisms behind memory impairment in MCI.
引用
收藏
页码:81 / 88
页数:8
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