White Matter Hyperintensity Longitudinal Morphometric Analysis In Association With Alzheimer Disease
Abstract
INTRODUCTION: Vascular damage in Alzheimer's disease (AD) has shown conflicting findings particularly when analyzing longitudinal data. We introduce white matter hyperintensity (WMH) longitudinal morphometric analysis (WLMA) that quantifies WMH expansion as the distance from lesion voxels to a region of interest boundary. METHODS: WMH segmentation maps were derived from 270 longitudinal fluid-attenuated inversion recovery (FLAIR) ADNI images. WLMA was performed on five data driven WMH patterns with distinct spatial distributions. Amyloid accumulation was evaluated with WMH expansion across the five WMH patterns. RESULTS: The preclinical group had significantly greater expansion in the posterior ventricular WM compared to controls. Amyloid significantly associated with frontal WMH expansion primarily within AD individuals. WLMA outperformed WMH volume changes for classifying AD from controls primarily in periventricular and posterior WMH. DISCUSSION: These data support the concept that localized WMH expansion continues to proliferate with amyloid accumulation throughout the entirety of the disease in distinct spatial locations.
Recommended Citation
J. F. Strain and C. L. Phuah and B. Adeyemo and K. Cheng and K. B. Womack and J. McCarthy and M. Goyal and Y. Chen and A. Sotiras and H. An and C. Xiong and A. Scharf and C. Newsom-Stewart and J. C. Morris, "White Matter Hyperintensity Longitudinal Morphometric Analysis In Association With Alzheimer Disease," Alzheimer's and Dementia, Wiley, Jan 2023.
The definitive version is available at https://doi.org/10.1002/alz.13377
Department(s)
Biological Sciences
Publication Status
Full Access
Keywords and Phrases
AD; longitudinal; preclinical; WLMA; WMH
International Standard Serial Number (ISSN)
1552-5279; 1552-5260
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2023 Wiley, All rights reserved.
Publication Date
01 Jan 2023
PubMed ID
37563879
Comments
National Institutes of Health, Grant K23 NS110927