Longitudinal changes in surface based brain morphometry measures in amnestic mild cognitive impairment and Alzheimer's Disease

Abstract

Background: Alzheimer's disease (AD) is associated with marked brain atrophy. While commonly used structural MRI imaging methods do not account for the complexity of human brain morphology, little is known about the longitudinal changes of cortical geometry and their relationship with cognitive decline in subjects with AD. Methods: Data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were used to perform two-sample t-tests to investigate longitudinal changes of cortical thickness (CTh) and three surface-based morphometry measures: fractal dimension (i.e. cortical complexity; FD), gyrification index (GI), and sulcal depth (SD) in subjects with AD, amnestic mild cognitive impairment (aMCI) in comparison to cognitively unimpaired controls (CU) in baseline and 2-year follow-up sMRI scans. In addition, correlations of the morphological measures with two-year cognitive decline as assessed by the modified AD Assessment Scale-Cognitive Subscale (ADAS-Cog 11) were calculated via regression analyses. Results: Compared to CU, both AD and aMCI showed marked decreases in CTh. In contrast, analyses of FD and GI yielded a more nuanced decline of the respective measures with some areas showing increases in FD and GI. Overall changes in FD and GI were more pronounced in AD as compared to aMCI. Analyses of SD yielded widespread decreases. Interestingly, cognitive decline corresponded well with CTh declines in aMCI but not AD, whereas changes in FD corresponded with AD only but not aMCI, whereas GI and SD were associated with cognitive decline in aMCI and AD. Conclusion: Patterns of longitudinal changes in FD, GI and SD were only partially overlapping with CTh reductions. In AD, surface-based morphometry measures for brain-surface complexity showed better correspondence than CTh with cognitive decline over a two-year period of time. Being drawn from measures reflecting changes in more intricate aspects of human brain morphology, these data provide new insight into the complexity of AD-related brain atrophy and its relationship with cognitive decline. © 2023 The Author(s)