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Abstract #3782

Characterizing Periventricular and Deep WMH in Aging Using Advanced Diffusion MRI for Tract-Based Insights

Kelly Chang1, Luke Burke2, Nina LaPiana3, Bradley Howlett3, David Hunt3, Margaret Dezelar2, Jalal B Andre4, Patti Curl4, James D Ralston2, Ariel Rokem1, and Christine L Mac Donald3
1Psychology, University of Washington, Seattle, WA, United States, 2Kaiser Permanente Washington Health Research Institute, Seattle, WA, United States, 3Neurological Surgery, University of Washington, Seattle, WA, United States, 4Radiology, University of Washington, Seattle, WA, United States

Synopsis

Keywords: Diffusion Modeling, White Matter

Motivation: This study aims to characterize the biophysical properties of white matter hyperintensities (WMH) using advanced diffusion MRI, as current clinical assessments are limited by labor-intensive visual inspection.

Goal(s): Our goal is to differentiate the biophysical tissue properties of periventricular and deep WMH to better understand their distinct characteristics.

Approach: We applied advanced diffusion MRI modeling, machine learning, and free-water eliminated tractography to FLAIR and diffusion MRI from 360 participants, using segmentation and tract-based analysis.

Results: We identified distinct diffusion metric patterns for periventricular and deep WMH, with tractography showing diffuse periventricular WMH and localized deep WMH in association tracts.

Impact: This study differentiates periventricular and deep WMH using advanced diffusion MRI, allowing more precise characterization and localization of WMH subtypes beyond visual inspection. This work could inform future research on tract-specific WMH-related cognitive impairments in aging.

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