Spatial Distribution of White-Matter Hyperintensities in Alzheimer Disease, Cerebral Amyloid Angiopathy, and Healthy Aging

Abstract

Background and Purpose-White-matter hyperintensities (WMHs) detected by magnetic resonance imaging are thought to represent the effects of cerebral small-vessel disease and neurodegenerative changes. We sought to determine whether the spatial distribution of WMHs discriminates between different disease groups and healthy aging individuals and whether these distributions are related to local cerebral perfusion patterns. Methods-We examined the pattern of WMHs by T2/fluid-attenuated inversion recovery-weighted magnetic resonance imaging in 3 groups of subjects: cerebral amyloid angiopathy (nϭ32), Alzheimer disease or mild cognitive impairment (nϭ41), and healthy aging (nϭ29). WMH frequency maps were calculated for each group, and spatial distributions were compared by voxel-wise logistic regression. WMHs were also analyzed as a function of normal cerebral perfusion patterns by overlaying a single photon emission computed tomography atlas. Results-Although WMH volume was greater in cerebral amyloid angiopathy and Alzheimer disease/mild cognitive impairment than in healthy aging, there was no consistent difference in the spatial distributions when controlling for total WMH volume. Hyperintensities were most frequent in the deep periventricular WM in all 3 groups. A strong inverse correlation between hyperintensity frequency and normal perfusion was demonstrated in all groups, demonstrating that WMHs were most common in regions of relatively lower normal cerebral perfusion. Conclusions-WMHs show a common distribution pattern and predilection for cerebral WM regions with lower atlas-derived perfusion, regardless of the underlying diagnosis. These data suggest that across diverse disease processes, WM injury may occur in a pattern that reflects underlying tissue properties, such as relative perfusion.

White Matter Hyperintensity Volume and Cerebral Perfusion in Older Individuals with Hypertension Using Arterial Spin-Labeling

“…However, WMHs primarily develop in regions with low perfusion, suggesting that low perfusion is involved in WMH conception. 21,22 Conceivably, tiny infarctions interact with low-grade hypoperfusion, for example, originating when perfusion in a small area drops below a certain threshold. Such low-grade hypoperfusion could be too small to measure with current techniques and only becomes apparent after WMHs develop due to tissue damage.…”

“…20 WMHs primarily originate in physiologically poorly perfused areas (ie, the periventricular and deep WM), explaining how even a slight cerebral perfusion deficit could provoke low-grade ischemia in those regions associated with WMHs. 21,22 Low perfusion in NAWM has also been associated with subsequent WMH development. 23 While these findings seem to suggest that WMHs are related to a perfusion deficit extending beyond the WMHs, current evidence remains circumstantial.…”

Effects of short-term dietary nitrate supplementation on blood pressure, O2uptake kinetics, and muscle and cognitive function in older adults

“…Therefore, dietary NO 3 Ϫ supplementation may have the potential to modify cerebrovascular physiology and enhance cognitive function. Indeed, Presley et al (63) recently reported that dietary nitrate improves regional white matter perfusion in older adults in areas of the brain that are involved in executive functioning and speculated that this may offset the influence of aging on cognitive decline and dementia (32).…”

The Gothenburg MCI study: Design and distribution of Alzheimer’s disease and subcortical vascular disease diagnoses from baseline to 6-year follow-up

“…43,44 FreeSurfer is an automatic tool that estimates a number of regional brain volumes (e.g., hippocampus, amygdala, and thalamus) from T1-weighted MRI. Manual WMC volumetry on FLAIR images is also performed in the Gothenburg MCI study using the software MRIcron, employing a modified method used by Holland et al 45 To consistently analyze each participant series, a grayscale mapping of the brain tissue is performed in the image containing the quadrigeminal plate. After the manual segmentation, an image intensity thresholding is applied and the overlap between the manually segmented regions and the intensity thresholding is used as estimates of WMC volume.…”