White Matter Hyperintensity Burden is Related to White Matter Cerebrovascular Reactivity in Aging
Poster No:
259
Submission Type:
Abstract Submission
Authors:
Claire Hsu1, Quimby Lee2, Gregory Wheeler1, Audrey Fan1,2
Institutions:
1Department of Biomedical Engineering, University of California, Davis, Davis, CA, 2Department of Neurology, University of California, Davis, Davis, CA
First Author:
Co-Author(s):
Audrey Fan, PhD
Department of Biomedical Engineering, University of California, Davis|Department of Neurology, University of California, Davis
Davis, CA|Davis, CA
Department of Biomedical Engineering, University of California, Davis|Department of Neurology, University of California, Davis
Davis, CA|Davis, CA
Introduction:
White matter hyperintensities (WMH) are regions located in the white matter (WM) of the brain that appear unexpectedly bright in fluid-attenuated inversion recovery (FLAIR) scans of magnetic resonance imaging (MRI). The pathogenesis of WMH remains unclear; however, WMH burden has been associated with both stroke risk and stroke damage, suggesting vascular contributions [1]. Cerebrovascular reactivity (CVR), or the ability for blood vessels to dilate in response to vasoactive stimuli, is an indicator of cerebrovascular health. Functional MRI (fMRI) studies have utilized the blood oxygen level dependent (BOLD) signal to measure CVR response to a vasodilation challenge, such as increased CO2 inhalation, and how it relates to cognitive decline in aging and stroke-related disorders. However, the vasodilation challenge required in traditional CVR adds to patient burden during scan acquisition. To circumvent this challenge, recent studies have proposed using relative CVR (rCVR) mapping derived solely from resting-state BOLD (rs-BOLD) signals. In this method, a frequency filtered global BOLD signal is used as a surrogate measure of the arterial CO2 timeseries to estimate cerebrovascular responses to natural CO2 fluctuations during normal breathing. With this innovation, CVR analysis can be performed on resting-state fMRI (rs-fMRI) scans without gas challenges that are more accessible to patient populations with high vascular risk. In this study, we utilize this novel rCVR mapping method to investigate the relationship between global WMH burden and tract-specific white matter CVR changes in an elderly cohort with vascular risk.
Methods:
A T1-weighted structural scan, 8-minute rs-fMRI scan, and T2 FLAIR scan were acquired for 135 participants (64-97 years, 95 female) from the Alzheimer's Disease Research Center at UC Davis. Of the participants, 87 were cognitively normal, 38 were mildly impaired, and 10 were diagnosed with dementia. The T2 FLAIR scans were segmented into gray matter, white matter, cerebrospinal fluid, and WMH regions through a semi-automated procedure described in previous studies [2,3]. To calculate %WMH, the number of WMH voxels was divided by the total number of brain voxels and multiplied by 100%. %WMH was log-transformed to ensure a normal distribution. Resting-state fMRI scans were motion corrected and spatially smoothed (Gaussian kernel full-width-half-max=8mm) and CVR maps were generated using voxel-wise regression of the gray matter BOLD signal, which acted as a surrogate for the CO2 timeseries during natural breathing [4]. Maps were then normalized to global CVR to produce rCVR maps. CVR calculation was performed in native fMRI space, then transformed into T1-anatomical and MNI standard space. Finally, we calculated the average rCVR values for specific WM tracts identified by the Johns Hopkins University atlas. Relative CVR was regressed on log(%WMH), age, sex, and cognitive status for each of the 20 WM tracts.
Results:
We observed a negative correlation (p<0.05) between %WMH and rCVR in the left and right cingulate gyrus (m=-0.05, p=0.01; m=-0.04, p=0.04), and left and right cingulum hippocampus (m=-0.09, p=0.003; m=-0.006, p=0.006). This finding aligns with our hypothesis that a greater %WMH corresponds to a lower rCVR value.
Conclusions:
The identified WM tracts support the default mode network, a functional network that changes in aging and cognitive impairment, which our results associate with vascular injury (reduced rCVR) [5]. As WMH are associated with both stroke risk and damage, our research provides insight into early vascular changes that may lead to WMH and vulnerable brain structural connections which can inform stroke prevention, treatment, and rehabilitation.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Lifespan Development:
Aging 2
Modeling and Analysis Methods:
Task-Independent and Resting-State Analysis
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
White Matter Anatomy, Fiber Pathways and Connectivity
Novel Imaging Acquisition Methods:
BOLD fMRI
Keywords:
Aging
Cerebrovascular Disease
Degenerative Disease
FUNCTIONAL MRI
White Matter
Other - Cerebrovascular Reactivity, White Matter Hyperintensities
1|2Indicates the priority used for review
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2. DeCarli C, et al. (1992), ‘Method for quantification of brain, ventricular, and subarachnoid CSF volumes from MR Images’, Journal of Computer Assisted Tomography, vol.16,2, pp. 274-84
3. DeCarli C, et al. (1995), ‘The effect of white matter hyperintensity volume on brain structure, cognitive performance, and cerebral metabolism of glucose in 51 healthy adults’, Neurology, vol. 45,11, pp. 2077-84
4. Bhogal AA. (2021), ‘Medullary vein architecture modulates the white matter bold cerebrovascular reactivity signal response to CO2: Observations from high-resolution T2* weighted imaging at 7t’, NeuroImage, vol. 245
5. Seiler S, et al. (2018), ‘Cerebral tract integrity relates to white matter hyperintensities, Cortex Volume, and cognition’, Neurobiology of Aging. vol. 72, pp. 14-22