White Matter Structure-Function Coupling in Different Stages of Alzheimer's Disease
Poster No:
187
Submission Type:
Abstract Submission
Authors:
Shih-Ze Huang1, Huei-Min Liu2, Ching-Po Lin2, Chun-Yi Lo1
Institutions:
1Department of Biomedical Engineering, Chung Yuan Christian University, Taoyuan, Taiwan, 2National Yang Ming Chiao Tung University, Taipei, Taiwan
First Author:
Co-Author(s):
Introduction:
Alzheimer's disease (AD) is a neurodegenerative disorder marked by abnormal protein accumulation and neuronal damage, with mild cognitive impairment (MCI) representing an intermediate stage that is crucial for early intervention. The recent functional correlation tensor (FCT) describes functional information along white matter fibers by analyzing spatio-temporal correlations of resting-state fMRI signals (Ding et al., 2013). Integrating FCT with diffusion tensor (DT) provides a comprehensive understanding of the structural-functional coupling between brain regions. As neuronal activation in white matter is essential for efficient information transmission and functional connectivity, its dysfunction is a key factor in the cognitive decline observed in AD and MCI (Sun et al., 2024). Investigating the structural and functional co-variations in white matter regions can help uncover the underlying mechanisms and progression of neurodegeneration in AD patients.
Methods:
The study recruited 23 AD patients (F/M: 14/9, age: 78 ± 8), 23 MCI patients (F/M: 11/12, age: 75 ± 14), and 48 healthy volunteers (HV) (F/M: 35/13, age: 69 ± 9). Data were acquired using a 3.0T GE Discovery MR750 scanner, including T1-weighted images, diffusion-weighted images (DWI), and resting-state fMRI (rs-fMRI). DWI preprocessing involved denoising, Gibbs Ring correction, head-motion, susceptibility, eddy current, and bias field corrections. fMRI preprocessing included orientation correction, removal of the first 10 volumes, head-motion correction, brain extraction, slice-timing correction, spatial smoothing, band-pass filtering (0.01–0.1 Hz), and CSF/motion parameter regression, with volumes registered to DWI space. DT were calculated from DWI, and FCT were derived from signal correlations between each voxel and its 26 neighbors in fMRI data. Both tensors were normalized, and their similarity was evaluated using Euclidean distance. The Mann-Whitney U test analyzed FCT-DT consistency to explore structure-function coupling across AD, MCI, and HV.
Results:
DT indicates neural fiber orientation, while FCT reflects neural activation in white matter tracts. In a splenium slice of the corpus callosum, voxel similarity analysis revealed higher values for tensors with greater alignment in both structural integrity and functional activation (Figure 1).
Significant FCT-DT consistency differences were identified between AD and HV in regions such as the splenium of the corpus callosum, cingulum, fornix/stria terminalis, and left superior fronto-occipital fasciculus (Figure 2). Pairwise comparisons highlighted differences between AD and MCI in the right cingulum, right fornix/stria terminalis, and left superior fronto-occipital fasciculus, as well as between MCI and HV in the splenium, right cingulum, and left fornix/stria terminalis.
Significant FCT-DT consistency differences were identified between AD and HV in regions such as the splenium of the corpus callosum, cingulum, fornix/stria terminalis, and left superior fronto-occipital fasciculus (Figure 2). Pairwise comparisons highlighted differences between AD and MCI in the right cingulum, right fornix/stria terminalis, and left superior fronto-occipital fasciculus, as well as between MCI and HV in the splenium, right cingulum, and left fornix/stria terminalis.
Conclusions:
In AD patients, similarity metrics in critical white matter regions, including the corpus callosum, cingulum, fornix/stria terminalis, and the left superior fronto-occipital fasciculus, were significantly lower compared to HV, indicating reduced structural and functional consistency. These findings underscore the importance of similarity as a quantitative measure reflecting the alignment between neural fiber integrity and neural activation, with reduced similarity in AD implying disrupted neural transmission efficiency.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI)
Connectivity (eg. functional, effective, structural) 2
Task-Independent and Resting-State Analysis
Keywords:
Other - Functional Correlation Tensor, Diffusion tensor, Mild cognitive impairment, neurodegeneration disease, brain connectivity
1|2Indicates the priority used for review
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Was this research conducted in the United States?
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
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Provide references using APA citation style.
Sun, H., et al. (2024) "Structure-function coupling reveals the brain hierarchical structure dysfunction in Alzheimer’s disease: A multicenter study. " Alzheimer’s & Dementia, 20(6), 6305-6315.