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. 2024 Apr 23;16(1):88.
doi: 10.1186/s13195-024-01448-1.

Exploring morphological similarity and randomness in Alzheimer's disease using adjacent grey matter voxel-based structural analysis

Ting-Yu Chen  1   2 , Jun-Ding Zhu  2 , Shih-Jen Tsai  1   3   4 , Albert C Yang  5   6   7   8
Affiliations

Exploring morphological similarity and randomness in Alzheimer's disease using adjacent grey matter voxel-based structural analysis

Ting-Yu Chen et al. Alzheimers Res Ther. .

Abstract

Background: Alzheimer's disease is characterized by large-scale structural changes in a specific pattern. Recent studies developed morphological similarity networks constructed by brain regions similar in structural features to represent brain structural organization. However, few studies have used local morphological properties to explore inter-regional structural similarity in Alzheimer's disease.

Methods: Here, we sourced T1-weighted MRI images of 342 cognitively normal participants and 276 individuals with Alzheimer's disease from the Alzheimer's Disease Neuroimaging Initiative database. The relationships of grey matter intensity between adjacent voxels were defined and converted to the structural pattern indices. We conducted the information-based similarity method to evaluate the structural similarity of structural pattern organization between brain regions. Besides, we examined the structural randomness on brain regions. Finally, the relationship between the structural randomness and cognitive performance of individuals with Alzheimer's disease was assessed by stepwise regression.

Results: Compared to cognitively normal participants, individuals with Alzheimer's disease showed significant structural pattern changes in the bilateral posterior cingulate gyrus, hippocampus, and olfactory cortex. Additionally, individuals with Alzheimer's disease showed that the bilateral insula had decreased inter-regional structural similarity with frontal regions, while the bilateral hippocampus had increased inter-regional structural similarity with temporal and subcortical regions. For the structural randomness, we found significant decreases in the temporal and subcortical areas and significant increases in the occipital and frontal regions. The regression analysis showed that the structural randomness of five brain regions was correlated with the Mini-Mental State Examination scores of individuals with Alzheimer's disease.

Conclusions: Our study suggested that individuals with Alzheimer's disease alter micro-structural patterns and morphological similarity with the insula and hippocampus. Structural randomness of individuals with Alzheimer's disease changed in temporal, frontal, and occipital brain regions. Morphological similarity and randomness provide valuable insight into brain structural organization in Alzheimer's disease.

Keywords: Alzheimer’s disease; Information-based similarity method; Morphological similarity network; Structural magnetic resonance imaging.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Flowchart. A Grey matter relationships with neighboring six voxels identified structural pattern indices. The binary symbol sequence, which represented the combination of intensity relationships, was then converted to a decimal pattern index. B Preprocessed grey matter maps were mapped using a zero-padded grey matter mask. This step ensured the retention of voxels and their neighbors for morphological similarity analysis. Subsequently, these were mapped with the grey matter mask. C We measured the IBS distances as dissimilarity between two AAL brain regions based on the probabilities and rank orders of structural patterns. D The IBS distance between the original and spatial shuffled grey matter intensities assessed the structural randomness. The stepwise regression was used to examine the relationship of the MMSE score with structural randomness. E We applied the one-sample t-test to investigate the regional structural similarity and the independent t-tests to explore group differences in inter-regional structural similarity and structural randomness. AAL: automated anatomical labeling; IBS: information-based similarity; MMSE: Mini-Mental State Examination
Fig. 2
Fig. 2
Brain regions with significant difference in regional structural similarity. We first generated the group average probability of structural pattern indices. Next, we calculated the distances (dissimilarities) for the same region between the CN and AD groups. The nodes represent the brain regions with significant dissimilarity, and the colors illustrate the IBS distances. AD: Alzheimer’s disease; CN: cognitively normal older adults; IBS: information-based similarity; ACG: anterior cingulate and paracingulate gyri; HIP: hippocampus; OLF: olfactory cortex; PCG: posterior cingulate gyrus
Fig. 3
Fig. 3
Altered inter-regional structural similarities in AD. We calculated the inter-regional distances to evaluate the individual morphological similarities in all participants. A The nodes represent brain regions where individuals with AD showed significantly decreased inter-regional structural similarity. B The nodes represent the brain regions where inter-regional structural similarity significantly increased in individuals with AD. The edges illustrate pairs of altered similarities, with colors representing the t values from comparisons between AD and CN groups. AD: Alzheimer’s disease; CN: cognitively normal older adults; HIP: hippocampus; INS: insula; OLF: olfactory cortex
Fig. 4
Fig. 4
Group differences in structural randomness of brain regions. We calculated the nonrandomness index for each brain region and investigated the group differences. The colors represent the t values from group comparisons between AD and CN groups. AD: Alzheimer’s disease; CN: cognitively normal older adults
Fig. 5
Fig. 5
Brain regions with structural randomness associated with cognitive performance in AD. The nodes represent the brain regions where the nonrandomness indices correlated with the cognitive performance in individuals with AD. The colors illustrate the beta coefficients derived from the stepwise regression analysis. AD: Alzheimer’s disease; ACG: anterior cingulate and paracingulate gyri; ANG: angular gyrus; HIP: hippocampus; MTG: middle temporal gyrus; SMG: supramarginal gyrus.
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