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

Authors

Meral A. Tubi, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, 90292, USA.
Franklin W. Feingold, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, 90292, USA; Stanford University, Stanford, CA, 94305, USA.
Deydeep Kothapalli, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, 90292, USA.
Evan T. Hare, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, 90292, USA.
Kevin S. King, Huntington Medical Research Institute, Imaging Division, Pasadena, CA, 91105, USA.
Paul M. Thompson, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, 90292, USA.
Meredith N. Braskie, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, 90292, USA. Electronic address: braskie@usc.edu.

Document Type

Article

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.

Medical Subject Headings

Aged; Aged, 80 and over; Alzheimer Disease (cerebrospinal fluid, diagnostic imaging, physiopathology); Amyloid beta-Peptides (cerebrospinal fluid); Bone Substitutes; Brain (diagnostic imaging); Cognition; Cognitive Dysfunction (cerebrospinal fluid, diagnostic imaging, physiopathology); Female; Humans; Image Processing, Computer-Assisted (methods); Magnetic Resonance Imaging; Male; Middle Aged; White Matter (diagnostic imaging)

Publication Date

2-1-2020

Publication Title

NeuroImage

E-ISSN

1095-9572

Volume

206

First Page

116327

PubMed ID

31682983

Digital Object Identifier (DOI)

10.1016/j.neuroimage.2019.116327

Recommended Citation

Tubi, Meral A.; Feingold, Franklin W.; Kothapalli, Deydeep; Hare, Evan T.; King, Kevin S.; Thompson, Paul M.; and Braskie, Meredith N., "White matter hyperintensities and their relationship to cognition: Effects of segmentation algorithm" (2020). Neuroradiology. 63.
https://scholar.barrowneuro.org/neuroradiology/63