AUTHOR=Sayin Ece Su , Sobczyk Olivia , Poublanc Julien , Mikulis David J. , Fisher Joseph A. , Duffin James 

TITLE=Transfer function analysis assesses resting cerebral perfusion metrics using hypoxia-induced deoxyhemoglobin as a contrast agent

JOURNAL=Frontiers in Physiology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2023.1167857

DOI=10.3389/fphys.2023.1167857

ISSN=1664-042X

ABSTRACT=Recent experiments have used hypoxia-induced changes in deoxyhemoglobin as a susceptibility contrast agent for magnetic resonance imaging to provide information about cerebral blood flow and its distribution within the brain.  Conventional methods of analysis require the selection of an arterial input function (AIF) which measures the temporal changes in the blood oxygen dependent (BOLD) signal over an artery in the brain, which is then used in a tracer kinetic model to calculate perfusion metrics in each voxel.  Transfer function analysis (TFA) offers an alternative approach that simplifies acquisition of perfusion metrics as it eliminates the issues concerning identification of an optimal AIF from BOLD data thus simplifying the data analysis. This analysis estimates the strength and temporal relationship of the response to the contrast agent in terms of Gain, and phase or time Lag.  We hypothesized that TFA metrics Gain, Lag, and their ratio, Gain/Lag, correspond to conventional AIF resting perfusion metrics relative cerebral blood volume (rCBV), mean transit time (MTT) and relative cerebral blood flow (rCBF), respectively. 24 healthy participants (17 M) and 1 patient with steno-occlusive disease were recruited to undergo a 4.2-minute transient pulmonary hypoxia protocol.  TFA and conventional AIF analyses were used to calculate averages of whole brain and smaller regions of interest perfusion metrics. Maps of these average metrics with colour scales adjusted to enhance spatial discrimination show high congruence. Regional gray matter/white matter (GM/WM) ratios for MTT and Lag, rCBF and Gain/Lag, and rCBV and Gain were compared. The GM/WM ratios were greater for TFA metrics compared to those from AIF analysis indicating an improved spatial discrimination.