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

• Published in: NeuroImage (Orlando, Fla.) Fla.), 2020-02, Vol.206, p.116327-116327, Article 116327
• Main Authors: Tubi, Meral A., Feingold, Franklin W., Kothapalli, Deydeep, Hare, Evan T., King, Kevin S., Thompson, Paul M., Braskie, Meredith N.
• Format: Article
• Language: English
• Subjects: Aged; Aged, 80 and over; Aging; Algorithms; Alzheimer Disease - cerebrospinal fluid; Alzheimer Disease - diagnostic imaging; Alzheimer Disease - physiopathology; Alzheimer's disease; Amyloid; Amyloid beta-Peptides - cerebrospinal fluid; Automation; Bias; Bone Substitutes; Boundaries; Brain - diagnostic imaging; Cerebrospinal fluid; Cognition; Cognition & reasoning; Cognitive ability; Cognitive Dysfunction - cerebrospinal fluid; Cognitive Dysfunction - diagnostic imaging; Cognitive Dysfunction - physiopathology; Cognitively normal; Dementia; Diagnosis; Executive function; Female; Humans; Image Processing, Computer-Assisted - methods; Magnetic Resonance Imaging; Male; Memory; Middle Aged; Mild cognitive impairment; MRI; Neurodegenerative diseases; Neuroimaging; Older people; Quality control; Scanners; Segmentation; Substantia alba; White Matter - diagnostic imaging
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2019.116327

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. •WMH boundary selection modifies the relationship between WMH volume and cognition.•When less hyperintense voxels were excluded, WMH volume related best to cognition.•In Aβ- participants, greater WMH volume was associated with worse clinical measures.•Alzheimer’s disease-related processes may mask the effect of WMHs on cognition.•Larger total, frontal, parietal and periventricular WMH volumes were related to worse cognition.