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Updated: Jan 3, 2026

MRI Mapping of Cerebrovascular Reactivity via Gas Inhalation Challenges
Published on: December 17, 2014
The association between BOLD-based cerebrovascular reactivity (CVR) and end-tidal CO2 in healthy subjects
Xirui Hou1, Peiying Liu2, Yang Li3
1Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA; The Russell H. Morgan Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Abstract:
Cerebrovascular reactivity (CVR) mapping using CO2-inhalation can provide important insight into vascular health. At present, blood-oxygenation-level-dependent (BOLD) MRI acquisition is the most commonly used CVR method due to its high sensitivity, high spatial resolution, and relatively straightforward processing. However, large variations in CVR across subjects and across different sessions of the same subject are often observed, which can cloud the ability of this promising measure in detecting diseases or monitoring treatment responses. The present work aims to identify the physiological components underlying the observed variability in CVR data. When studying the association between CVR value and the subject's CO2 levels in a total of N = 253 healthy participants, we found that CVR was lower in individuals with a higher basal end-tidal CO2, EtCO2 (slope = -0.0036 ± 0.0008%/mmHg2, p < 0.001), or with a greater EtCO2 change (ΔEtCO2) with hypercapnic condition (slope = -0.0072 ± 0.0018%/mmHg2, p < 0.001). In a within-subject setting, when studying the CVR difference between two repeated scans (with repositioning) in relation to the corresponding differences in basal EtCO2 and ΔEtCO2 (n = 11), it was found that CVR values were lower if the basal EtCO2 or ΔEtCO2 during that particular scan session was greater. The present work suggests that basal physiological state and the level of hypercapnic stimulus intensity should be considered in application studies of CVR in order to reduce inter-subject and intra-subject variations in the data. Potential approaches to use these findings to reduce noise and augment sensitivity are proposed.
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