White matter hyperintensities and their relationship to cognition: Effects of segmentation algorithm

白质高信号及其与认知的关系:分割算法的影响

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Abstract

White matter hyperintensities (WMHs) are brain white matter lesions that are hyperintense on fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) scans. Larger WMH volumes have been associated with Alzheimer's disease (AD) and with cognitive decline. However, the relationship between WMH volumes and cross-sectional cognitive measures has been inconsistent. We hypothesize that this inconsistency may arise from 1) the presence of AD-specific neuropathology that may obscure any WMH effects on cognition, and 2) varying criteria for creating a WMH segmentation. Manual and automated programs are typically used to determine segmentation boundaries, but criteria for those boundaries can differ. It remains unclear whether WMH volumes are associated with cognitive deficits, and which segmentation criteria influence the relationships between WMH volumes and clinical outcomes. In a sample of 260 non-demented participants (ages 55-90, 141 males, 119 females) from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we compared the performance of five WMH segmentation methods, by relating the WMH volumes derived using each method to both clinical diagnosis and composite measures of executive function and memory. To separate WMH effects on cognition from effects related to AD-specific processes, we performed analyses separately in people with and without abnormal cerebrospinal fluid amyloid levels. WMH volume estimates that excluded more diffuse, lower-intensity lesions were more strongly correlated with clinical diagnosis and cognitive performance, and only in those without abnormal amyloid levels. These findings may inform best practices for WMH segmentation, and suggest that AD neuropathology may mask WMH effects on clinical diagnosis and cognition.

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