4940. White Matter Hyperintensity and Cerebral Blood Flow: A Novel ASL Perfusion Parameter That May Predict the Severity of White Matter Disease
Authors* Denotes Presenting Author
Ates Fettahoglu;
Stanford University
Moss Zhao;
Stanford University
Greg Zaharchuk;
Stanford University
Abdelkader Mahammedi *;
Stanford University
Objective:
Small vessel disease (SVD) is a common cause of stroke and cognitive decline, characterized by white matter hyperintensities (WMH) on neuroimaging. While WMH can be associated with reduced cerebral blood flow (CBF), current clinical and radiological assessments of these associations remain controversial and mostly qualitative without quantitative measures. Our study aimed to develop a standardized quantitative perfusion-MRI parameter that assesses WMH severity.
Materials and Methods:
From our institution’s Alzheimer’s Disease Research Center (ADRC) and 15-O-water PET study database (<em>N</em> = 135), healthy adults with normal cognition were retrospectively selected in this preliminary study. Our inclusion criteria included patients aged > 50 years with no structural brain abnormalities besides SVD or cognitive impairment, and at least one clinical brain MR study with ASL-perfusion images. WMH grading was performed based on the Fazekas scale, and total WMH volume was calculated along with white and gray matter cerebral blood flow quantification. Associations between multiple perfusion parameters including perfusion-mismatch metric (PMM), WMH grade, and WMH volume, were evaluated. PMM, a relative perfusion mismatch percentage capturing the normalized perfusion difference between whole brain (WB) and white matter (WM) CBF, PMM (%) = ([(CBF_WB - CBF_WM) / CBF_WB] x 100). The PMM classifier performance was summarized by the area under the ROCAUC.
Results:
A total of 26 age-matched participants met the inclusion criteria and were divided into minimal (mean age, 71.2 ± 7.7, 12 women) versus moderate to severe WMH (mean age, 71.6 ± 9.7, 6 women). PMM was found to have the highest correlation with Fazekas score and total WMH volume (<em>r</em> = 0.64 and 0.49, respectively; <em>P</em> < 0.001). PMM had the highest ROCAUC of 0.91 as a predictor of WMH severity (95% CI: 0.81, 1.00).
Conclusion:
The PMM approach yielded a strong correlation with WMH severity. Further longitudinal studies are required to determine the potential role of PMM as a predictive marker of WMH progression.
