Baseline oxygenation in the brain: Correlation between respiratory-calibration and susceptibility methods
Introduction
Adequate oxygen supply is critical to the health of cerebral tissues, and cerebral oxygen extraction fraction (OEF) is thought to be highly conserved across the brain (Hatazawa et al., 1995, Ishii et al., 1996b). While OEF is preserved across a wide range of physiological states in normal brain function, it is also known to be altered by cerebrovascular (Derdeyn et al., 1998, Yamauchi et al., 1999) and neurodegenerative disorders (Ishii et al., 1996a). The ability to noninvasively image OEF would thus provide important clinical information in patients where the brain oxygen supply may be disrupted. This information may also improve our understanding of the baseline physiology that underlies vascular and metabolic blood-oxygen-level-dependent (BOLD) signal changes. Although [15O] positron emission tomography (PET) is the accepted reference method to quantify OEF maps in the brain (Ito et al., 2005), it is rarely used in the clinic due to the need for a cyclotron on site to produce short half-life [15O]-tracers, experimental complexity, and use of ionizing radiation. Recognition of the importance of sophisticated OEF mapping and the current limitations in its measurement has prompted recent efforts to develop magnetic resonance imaging (MRI) alternatives. A variety of MRI methods have been proposed to measure global and local OEF from T2 relaxation (Bolar et al., 2011, Guo and Wong, 2012, Lu and Ge, 2008), respiratory calibration (Bulte et al., 2012, Gauthier and Hoge, 2012, Wise et al., 2013), and magnetic susceptibility contrasts (Fan et al., 2012, Haacke et al., 1997, Jain et al., 2010).
One new class of MRI methods utilizes respiratory calibration with multiple gas challenges to quantify tissue OEF in the brain. Traditional calibrated BOLD techniques have relied on a single isometabolic gas challenge, such as hypercapnia or hyperoxia, to measure relative changes in oxygen metabolism during a functional task (Chiarelli et al., 2007, Davis et al., 1998). These approaches typically assume a baseline OEF value and estimate the M parameter, the maximum achievable BOLD signal at rest due to deoxyhemoglobin (dHb), as an intermediate step in the processing. On the other hand, the recently proposed generalized calibration model (GCM) enables biophysical modeling of BOLD MRI, perfusion MRI, and end-tidal O2 (ETO2) responses to arbitrary combinations of hyperoxia and hypercapnia (Gauthier and Hoge, 2013). Through use of multiple gas manipulations and the GCM, local baseline values of M and OEF are available per tissue voxel. Several variants of this respiratory calibration approach have been implemented with pure hyperoxia and hypercapnia (Bulte et al., 2012, Germuska and Bulte, 2014), or multiple combinations of gases with different combinations of O2 and CO2 concentrations (Wise et al., 2013). In this work, we focus on a specific variant known as QUantitative O2 (QUO2) MRI (Gauthier et al., 2012), which provides a graphical interpretation of the GCM and was originally proposed with use of three gases.
On the other hand, magnetic susceptibility represents a distinct MRI contrast mechanism that reflects the magnetizability of a tissue and is thus sensitive to brain oxygenation. The OEF level in cerebral veins directly relates to the concentration of paramagnetic dHb molecules in the vessels (Weisskoff and Kiihne, 1992). The presence of dHb molecules changes the magnetic susceptibility in venous blood relative to reference tissue, such as the cerebrospinal fluid, which can be measured using gradient echo phase images. These magnetic field perturbations are non-local and depend on the geometry of the object and its orientation with respect to the main magnetic field, B0. Based on the observed MRI field maps, quantitative susceptibility mapping (QSM) methods (Bilgic et al., 2014, de Rochefort et al., 2008, Liu et al., 2009, Liu et al., 2012) have been proposed to invert the dipole imaging kernel and reconstruct the underlying susceptibility distribution. These QSM reconstructions typically rely on prior information about the spatial “smoothness” of the desired susceptibility, and allow measurement of susceptibility, and thus OEF, along brain vessels of arbitrary orientation and geometry. Given sufficient resolution to measure susceptibility within the veins, quantitative oxygenation venograms that measure baseline OEF along the venous vasculature of the brain are then available (Fan et al., 2014, Haacke et al., 2010, Xu et al., 2014).
While these new MRI approaches to assess absolute OEF are promising, they have not been carefully compared to each other or to known physiological signals, such as BOLD contrast and cerebral blood flow (CBF). Only a few studies have investigated the reproducibility of MRI-based oxygenation mapping across different sites (Liu et al., 2015), begun to compare global measurements of baseline OEF in healthy volunteers (Barhoum et al., 2015, Rodgers et al., 2015), or estimated relative changes of OEF compared to corresponding changes in BOLD and CBF (Donahue et al., 2009, Lu and van Zijl, 2005). Our aims were thus to compare two variants of QUO2 (with two and three gases, respectively) against independent OEF values by QSM analysis; as well as to see if baseline OEF measurements by these methods relate to BOLD and perfusion signals elicited during a visual functional task. These experiments were performed at 7 Tesla (7 T) to achieve high spatial resolution and localize OEF values to the visual cortex for comparison.
Section snippets
MRI acquisitions
Eleven healthy volunteers (9 female, ages 22–32 years, free of vascular abnormalities) were scanned on a MAGNETOM 7 T scanner (Siemens Healthcare, Erlangen, Germany) with a 24-channel head coil (6 volunteers) or a 32-channel head coil (all remaining participants). All procedures were approved by the Ethics Committee of the University of Leipzig and informed written consent was given by all volunteers. Manual shimming was performed to optimize field homogeneity over the imaging and labeling
Results
Table 1 lists the baseline OEF (%) measured in each volunteer from the visual ROI. OEF values are shown for QUO2 with data from hypercapnia and hyperoxia (2-gas), QUO2 with data from all three gas challenges (3-gas), and QSM in vessels. Individual plots of M (%) versus OEF (%) for each gas are shown as an intermediate step of the QUO2 technique in Fig. 2 for each subject and for group analysis. Group mean OEF values were (43.5 ± 14)% for 2-gas QUO2, (42.3 ± 17)% for 3-gas QUO2, and (29.4 ± 3)% for
Discussion
The present study compared two advanced MRI techniques to measure absolute, resting brain oxygenation in the visual cortex of healthy volunteers. We compared 2-gas and 3-gas versions of QUO2 against QSM for OEF assessment, and found that the 3-gas QUO2 values more strongly related to QSM values. Although susceptibility and respiratory calibration methods provided OEF estimates that were correlated, a non-constant overestimation bias in OEF was found with QUO2 relative to QSM. Further analysis
Acknowledgments
We thank Dr. Robert Trampel, Domenica Wilfling, and Elisabeth Wladimirow for their indispensible technical support during MRI experiments. This work was supported by the Alexander von Humboldt Foundation (C.J.G.), the Fonds de Recherche Santé Québec (C.J.G.), the Natural Sciences and Engineering Research Council of Canada (RGPIN-2015-04665) and the MIT-Germany Program (A.P.F.).
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Present address: Lucas Center for Imaging, 1201 Welch Road, Stanford CA, 94043, USA.