Quantifying cerebral blood arrival times using hypoxia-mediated arterial BOLD contrast

Abstract

Cerebral blood arrival and tissue transit times are sensitive measures of the efficiency of tissue perfusion and can provide clinically meaningful information on collateral blood flow status. We exploit the arterial blood oxygen level dependent (BOLD) signal contrast established by precisely modulating arterial hemoglobin saturation using hypoxic respiratory challenges (dOHb-BOLD) to quantify arterial blood arrival times throughout the brain. A combination of hemodynamic lag with a modified carpet plot analysis yielded lag, onset (blood arrival), mean transit time (MTT) and hypoxic response information, which is indicative of relative total blood volume. Onset times averaged across 12 healthy subjects were 1.1 ± 0.4 and 1.9 ± 0.6 for cortical gray and deep white matter, respectively. The average whole brain MTT was 4.5 ± 0.9 seconds. The dOHb-BOLD response was 1.7 fold higher in grey versus white; in line with known differences in regional blood volume fraction. Our method was also applied in unilateral carotid artery occlusion patient, which revealed prolonged signal onset with normal perfusion in the affected hemisphere. In cases with exhausted reserve capacity or confounding flow effects such as vascular steal, dOHb-BOLD can potentially inform on collateral flow pathways to provide a valuable compliment to clinical vascular reactivity measures.

Sinusoidal CO2 respiratory challenge for concurrent perfusion and cerebrovascular reactivity MRI

“…All subsequent dDSC processing was performed in MATLAB (MathWorks, Natick, MA). Signal contribution from pial veins was suppressed by eliminating voxels with higher signal amplitude than the 98th percentile (Bhogal et al, 2022). Whole brain (WB), GM, and WM perfusion values was computed by averaging voxels within brain and tissue-specific masks in each subject's functional native space.…”

“…The great cerebral veins not only have the largest signal intensity changes, but they have the longest delay relative to the global BOLD signal. Individual VOFs were obtained automatically by choosing 20 voxels with the highest integrated, rectified signal intensity (Carroll et al, 2003) and delay greater than the 98th percentile (Bhogal et al, 2022). To convert ΔR 2 * to concentrationtime curve C(t) in both blood and tissue voxels, this manuscript assumed a linear relationship ΔR 2 * (t) r Y × C(t), with coefficients r Y tissue r Y blood 1.…”

“…where f c is the fundamental frequency of the sinusoidal stimulus and ϕ is the phase of the sine wave (Blockley et al, 2011) calculated from the Fourier transform of the BOLD signal with respect to time. The venous phase ϕ venous was estimated by forming a histogram of phase delays across all voxels within the brain for each subject and selecting the 98th percentile, thus removing observer bias to obtain more consistent phase estimates (Bhogal et al, 2022).…”