Validation of oxygen extraction fraction measurement by qBOLD technique

Abstract

Key words: OEF; BOLD; qBOLD; brain metabolism; brain hemodynamics; fMRIWhile the dynamic properties of blood oxygenation level dependent (BOLD) contrast in MRI during functional activation have received much consideration, very little attention has been paid to the nature of the BOLD contrast during the resting or baseline level of neuronal activity in the brain. Because "resting brain" is responsible for approximately 20% of total human body oxygen consumption (1,2), understanding brain functioning in the baseline state is important for understanding brain performance in health and disease. One of the important parameters defining oxygen consumption is oxygen extraction fraction (OEF) -the percent of the oxygen removed from the blood by tissue during its passage through the capillary network. Previously, Raichle et al. (2,3) used this parameter to characterize the baseline state of the normal human brain. Such a characterization is germane because OEF maps of normal human subjects, resting quietly with their eyes closed, demonstrate remarkable uniformity (2,4) despite substantial regional variations of cerebral blood flow and the cerebral metabolic rate of oxygen consumption (2,3). This uniformity of the OEF in the absence of specific goal-directed activities supports the hypothesis that an established equilibrium exists between the local metabolic requirements necessary to sustain a long term modal level of neural activity and the level of blood flow in a particular region.Thus far most quantitative imaging studies mapping tissue OEF were conducted using oxygen-15 based positron emission tomography (PET) imaging techniques (5). The advent of BOLD MR imaging initiated by Ogawa et al. (6) opened new opportunities to noninvasively study brain hemodynamics. BOLD approach capitalizes on the fact that deoxygenated blood has different magnetic susceptibility as compared to oxygenated blood (7), which in turn has magnetic susceptibility similar to the tissue (6). Due to this effect, the deoxyhemoglobin containing part of the blood vessel network in the brain creates mesoscopic field inhomogeneities in the surrounding tissue leading to more rapid MRI signal decay than from standard T2 decay alone. Because these field inhomogeneities are tissue specific, measuring the MRI signal decay rate may provide information on the tissue structure and functioning. Previously this lab has developed a theoretical model of BOLD contrast that analytically connects the BOLD signal to hemodynamic parameters such as the deoxyhemoglobincontaining blood volume (DBV), deoxyhemoglobin concentration, and OEF (8). A subsequent publication (9) quantitatively validated important features of the model in phantom studies and developed a theoretical background and experimental method (based on the Gradient Echo Sampling of Spin Echo (GESSE) sequence) that allows the separation of mesoscopic field inhomogeneity effects from both macroscopic and microscopic inhomogeneities. Such separation allows one to take full advantage of the mesoscopic, tissue...

Tissue Oxygen Saturation Mapping with Magnetic Resonance Imaging

“…Based on the qBOLD approach, 3,5 the mqBOLD technique presented here includes two major modifications. First, mqBOLD combines several MR estimates obtained from sequences widely available on preclinical and clinical scanners.…”

“…8 As such, mqBOLD aims to yield values equal to the weighted sum of arterial and venous oxygenation levels and above the venous oxygenation level. 5 We evaluated the validity of this assumption using healthy rats submitted to various brain oxygenation challenges and found a strong correlation between MR_StO 2 (from mqBOLD) and StO 2 estimates from blood gas in the range of 20-90%. This technique could be further refined by taking into account the variations of magnetic susceptibilities across tissue types, as recently proposed in Yablonskiy et al 28 However, this would firstly require a procedure to assign a tissue type to each voxel and to handle partial volume effects.…”

“…3,4 By analyzing the magnetic resonance (MR) signal evolution through a biophysical model, cerebral venous blood volume and venous blood oxygen saturation maps have been obtained in both humans and animals. [5][6][7] This qBOLD approach, however, requires a specific MRI sequence, which limits its dissemination. To ease its use and improve its spatial resolution, our group has recently proposed combining several estimates obtained with routinely used clinical sequences, the multiparametric qBOLD (mqBOLD).…”

Measuring Biexponential Transverse Relaxation of the ASL Signal at 9.4 T to Estimate Arterial Oxygen Saturation and the Time of Exchange of Labeled Blood Water into Cortical Brain Tissue

“…A hyperbolic secant adiabatic inversion pulse was used with a bandwidth of 22 kHz for both the slice-selective and global inversion. 30 Images were acquired at 15 TE in a randomized order (19,21,36,25,48,33,65,27,30,56,23,40, 60, 52, and 44 ms). Tagged and control images were acquired at each TE and the protocol was repeated for a total of 50 averages at each TE.…”

“…Currently, most quantitative fMRI studies assume that blood on the arterial side of the vasculature is B100% saturated with oxygen. [26][27][28] These data challenge the validity of this assumption, and highlight the value of combined ASL and T2 measurement techniques for accurate, non-invasive estimation of arterial oxygen saturation in quantitative fMRI studies.…”