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Updated: Feb 7, 2026

DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions
Published on: August 26, 2014
White matter lesions: Spatial heterogeneity, links to risk factors, cognition, genetics, and atrophy
Mohamad Habes1, Aristeidis Sotiras2, Guray Erus2
1From the Center for Biomedical Image Computing and Analytics (M.H., A.S., G.E., N.R.B., J.D., C.D.), Department of Neurology and Penn Memory Center (M.H., D.A.W.), and Department of Biostatistics and Epidemiology (H.S.), University of Pennsylvania, Philadelphia; Department of Psychiatry (M.H., D.J., H.J.G.), Institute for Community Medicine (M.H., H.V., W.H.), and Department of Neurology (U.S.), University of Greifswald, Germany; Department of Neurology (J.B.T.), Houston Methodist Hospital, TX; German Center for Neurodegenerative Diseases (W.H., H.J.G.), Rostock/Greifswald, Germany; and Laboratory of Behavioral Neuroscience (S.M.R.), National Institute on Aging, Baltimore, MD. habesm@uphs.upenn.edu.
Objectives:
To investigate spatial heterogeneity of white matter lesions or hyperintensities (WMH).
Methods:
MRI scans of 1,836 participants (median age 52.2 ± 13.16 years) encompassing a wide age range (22-84 years) from the cross-sectional Study of Health in Pomerania (Germany) were included as discovery set identifying spatially distinct components of WMH using a structural covariance approach. Scans of 307 participants (median age 73.8 ± 10.2 years, with 747 observations) from the Baltimore Longitudinal Study of Aging (United States) were included to examine differences in longitudinal progression of these components. The associations of these components with vascular risk factors, cortical atrophy, Alzheimer disease (AD) genetics, and cognition were then investigated using linear regression.
Results:
WMH were found to occur nonuniformly, with higher frequency within spatially heterogeneous patterns encoded by 4 components, which were consistent with common categorizations of deep and periventricular WMH, while further dividing the latter into posterior, frontal, and dorsal components. Temporal trends of the components differed both cross-sectionally and longitudinally. Frontal periventricular WMH were most distinctive as they appeared in the fifth decade of life, whereas the other components appeared later in life during the sixth decade. Furthermore, frontal WMH were associated with systolic blood pressure and with pronounced atrophy including AD-related regions. AD polygenic risk score was associated with the dorsal periventricular component in the elderly. Cognitive decline was associated with the dorsal component.
Conclusions:
These results support the hypothesis that the appearance of WMH follows age and disease-dependent regional distribution patterns, potentially influenced by differential underlying pathophysiologic mechanisms, and possibly with a differential link to vascular and neurodegenerative changes.
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