The correlation between changes in gray matter microstructure and cerebral blood flow in Alzheimer’s disease - Niu, Xiaoxi; Guo, Ying; Chang, Zhongyu; Li, Tongtong; Chen, Yuanyuan; Zhang, Xianchang; Ni, Hongyan (Frontiers in Aging Neuroscience, 2023)
Objective: To investigate the relationship between changes in cerebral blood flow and gray matter (GM) microstructure in Alzheimer’s disease (AD) and mild cognitive impairment (MCI). Methods: A recruited cohort of 23 AD patients, 40 MCI patients, and 37 normal controls (NC) underwent diffusional kurtosis imaging (DKI) for microstructure evaluation and pseudo-continuous arterial spin labeling (pCASL) for cerebral blood flow assessment. We investigated the differences in diffusion- and perfusion-related parameters across the three groups, including cerebral blood flow (CBF), mean diffusivity (MD), mean kurtosis (MK) and fractional anisotropy (FA). These quantitative parameters were compared using volume-based analyses for the deep GM and surface-based analyses for the cortical GM. The correlation between CBF, diffusion parameters, and cognitive scores was assessed using Spearman coefficients, respectively. The diagnostic performance of different parameters was investigated with k-nearest neighbor (KNN) analysis, using 5-fold cross-validation to generate the mean accuracy (mAcc), mean precision (mPre), and mean area under the curve (mAuc). Results: In the cortical GM, CBF reduction primarily occurred in the parietal and temporal lobes. Microstructural abnormalities were predominantly noted in the parietal, temporal, and frontal lobes. In the deep GM, more regions showed DKI and CBF parametric changes at the MCI stage. MD showed most of the significant abnormalities among all the DKI metrics. The MD, FA, MK, and CBF values of many GM regions were significantly correlated with cognitive scores. In the whole sample, the MD, FA, and MK were associated with CBF in most evaluated regions, with lower CBF values associated with higher MD, lower FA, or lower MK values in the left occipital lobe, right temporal lobe, and right parietal lobe. CBF values performed best (mAuc = 0.876) for distinguishing the MCI from the NC group. Last, MD values performed best (mAuc = 0.939) for distinguishing the AD from the NC group. Conclusion: GM microstructure and CBF are closely related in AD. Increased MD, decreased FA, and MK are accompanied by decreased blood perfusion throughout the AD course. Furthermore, CBF values are valuable for the predictive diagnosis of MCI and AD. GM microstructural changes are promising as novel neuroimaging biomarkers of AD.