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Updated: Jun 14, 2025
Author Spotlight: Noninvasive Cerebral Blood Flow Determination in Human Functional Brain Region for Diagnosis of Neurological Disorders
Published on: May 31, 2024
Arterial Spin-Labeling MRI Identifies Abnormal Perfusion Metric at the Gray Matter/CSF Interface in Cerebral Small
Abdelkader Mahammedi1, Ates Fettahoglu2, Jeremy J Heit2
1From the Department of Radiology (A.M., A.F., J.J.H., G.Z.), Stanford University, Stanford, California abdelkader.mahammedi@stanford.edu.
Background And Purpose:
Cerebral small vessel disease (SVD) is a common cause of stroke and cognitive decline. SVD is characterized by white matter hyperintensities (WMH) and dilated perivascular spaces (PVS). While WMH can be associated with reduced CBF and glymphatic clearance, current clinical and radiologic assessments of these associations remain controversial and mostly qualitative. We aim to identify if arterial spin-labeling (ASL)-based CBF differences, particularly in the cortical surface at the GM/CSF interface, correlate with SVD severity.
Materials And Methods:
We performed a retrospective cohort study of healthy controls with normal cognition who underwent a brain MRI as part of our university's Alzheimer Disease Research Center (ADRC) and an 15O-water PET study database. Our inclusion criteria included patients aged >50 years with no structural brain abnormalities besides SVD with ASL perfusion images. WMH grading was performed by using the Fazekas scale, WMH score, PVS grade, and manually segmented WMH volume. We identified patients with moderate-to-severe SVD and then selected age-matched samples of patients with minimal or no SVD. CBF of the whole brain (WB), GM, WM, and along the GM/CSF interface were calculated. Several perfusion metrics (WB, GM, and WM) as well as a novel perfusion metric, normalized GM/CSF interface (nGCI) perfusion metric, which indirectly reflects the relative ASL signal near the GM-CSF boundary, were evaluated by using receiver operating characteristic and correlation analyses.
Results:
Thirty-two patients met the inclusion criteria (n=11 moderate-to-severe SVD, mean age 72 ± 10 years, 6 women; n = 21 none-to-minimal SVD, mean age 70 ± 10 years, 12 women). Of the measured perfusion markers, nGCI had the strongest negative correlation with Fazekas score, total WMH volume, PVS grade, and average total SVD score (r = -0.68, -0.67, -0.54, -0.54, respectively; P < .001) as well as the highest area under the receiver operating characteristics curve (0.95, 95% CI: 0.87-1.0) as a predictor of WMH severity.
Conclusions:
nGCI, a novel perfusion metric that may capture features of perfusion at the GM-CSF boundary, was strongly correlated with WMH and PVS severity. Further, longitudinal studies are required to determine the potential role of nGCI as a predictive marker of SVD progression.
Insights
A new metric, normalized gray matter/cerebrospinal fluid (GM/CSF) interface (nGCI) perfusion, strongly correlates with cerebral small vessel disease (SVD) severity, including white matter hyperintensities (WMH) and perivascular spaces (PVS). This finding may aid in assessing SVD progression.
Area of Science:
- Neuroimaging
- Cerebrovascular Diseases
- Radiology
Background:
- Cerebral small vessel disease (SVD) is a major cause of stroke and cognitive decline.
- SVD is characterized by white matter hyperintensities (WMH) and dilated perivascular spaces (PVS).
- Current assessments of SVD-related perfusion changes are often qualitative and controversial.
Purpose of the Study:
- To investigate the correlation between arterial spin-labeling (ASL)-based cerebral blood flow (CBF) at the gray matter/cerebrospinal fluid (GM/CSF) interface and SVD severity.
- To evaluate a novel ASL-derived metric, normalized GM/CSF interface (nGCI) perfusion, for its association with SVD markers.
Main Methods:
- Retrospective analysis of brain MRI and 15O-water PET data from 32 participants (>50 years old) with varying SVD severity.
- WMH grading using Fazekas scale, WMH score, PVS grade, and segmented WMH volume.
- Calculation of whole brain, GM, WM CBF, and a novel nGCI perfusion metric.
Main Results:
- The nGCI metric showed the strongest negative correlation with Fazekas score (r = -0.68), WMH volume (r = -0.67), and PVS grade (r = -0.54).
- nGCI demonstrated high accuracy (AUC = 0.95) in predicting WMH severity.
- A significant negative correlation was observed between nGCI and the average total SVD score (r = -0.54).
Conclusions:
- The novel nGCI perfusion metric is strongly associated with the severity of WMH and PVS in SVD.
- nGCI may serve as a sensitive marker for evaluating perfusion changes at the GM/CSF boundary in SVD.
- Further longitudinal studies are needed to establish nGCI as a predictive marker for SVD progression.
