Cerebrovascular reactivity (CVR) MRI with CO2 challenge: A technical review

Abstract

Cerebrovascular reactivity (CVR) is an indicator of cerebrovascular reserve and provides important information about vascular health in a range of brain conditions and diseases. Unlike steady-state vascular parameters, such as cerebral blood flow (CBF) and cerebral blood volume (CBV), CVR measures the ability of cerebral vessels to dilate or constrict in response to challenges or maneuvers. Therefore, CVR mapping requires a physiological challenge while monitoring the corresponding hemodynamic changes in the brain. The present review primarily focuses on methods that use CO2 inhalation as a physiological challenge while monitoring changes in hemodynamic MRI signals. CO2 inhalation has been increasingly used in CVR mapping in recent literature due to its potency in causing vasodilation, rapid onset and cessation of the effect, as well as advances in MRI-compatible gas delivery apparatus. In this review, we first discuss the physiological basis of CVR mapping using CO2 inhalation. We then review the methodological aspects of CVR mapping, including gas delivery apparatus, the timing paradigm of the breathing challenge, the MRI imaging sequence, and data analysis. In addition, we review alternative approaches for CVR mapping that do not require CO2 inhalation.

Keywords: Arterial spin labeling; BOLD; Carbon dioxide; Cerebrovascular reactivity; Cerebrovascular reserve; End-tidal CO2; Hypercapnia; Phase-contrast MRI.

Figure 1

Mechanisms of vessel dilation as a result of CO2 inhalation. CO2 and the associated increase in H⁺ can cause hyperpolarization of smooth muscle cells directly or indirectly via endothelial cells.

Figure 2

Three systems of gas delivery apparatus with a fixed CO2 concentration in inspired air. (a) Breathing apparatus by Lu et al. (b) Breathing apparatus by Tancredi et al. (c) Breathing apparatus by Bulte et al.

Figure 3

Example of CO2 time course during the experiment. (a) CO2 time course with 5% CO2 inhalation. Segments of the breath-by-breath CO2 content trace, as recorded by the CO2 monitor, are shown for a room-air breathing period (left inset) and a 5% CO2 inhalation period (right inset). (b) CO2 time course with 7.5% CO2 inhalation. Blue arrows indicate the periods where the inhaled CO2 concentration exceeded the exhaled CO2 concentration. Extracted Et-CO2 time courses are shown by the orange curve.

Figure 4

Illustration of typical CO2 breathing paradigms.

Figure 5

CVR maps acquired with different BOLD imaging resolutions in one healthy subject. 5%CO2 inhalation was used. All images were smoothed by a 4mm Gaussian kernel.

Figure 6

Illustration of the CVR data analysis pipelines.

Figure 7

CVR, CBVv, BAT and functional connectivity networks (FCNs) obtained in a healthy subject (28-year-old female) using concomitant CO2 and O2 inhalation. DMN: Default mode network. FPN: frontal-parietal network.

Figure 8

CVR maps derived from resting-state BOLD data and hypercapnia BOLD data. The healthy subject was a 25-year-old male. The Moyamoya patient was a 24-year-old female with left ICA stenosis.