A B S T R A C TAs energy metabolism in the brain is largely oxidative, the measurement of cerebral metabolic rate of oxygen consumption (CMRO 2 ) is a desirable biomarker for quantifying brain activity and tissue viability. Currently, PET techniques based on oxygen isotopes are the gold standard for obtaining whole brain CMRO 2 maps. Among MRI techniques that have been developed as an alternative are dual calibrated fMRI (dcFMRI) methods, which exploit simultaneous measurements of BOLD and ASL signals during a hypercapnic-hyperoxic experiment to modulate brain blood flow and oxygenation.In this study we quantified the repeatability of a dcFMRI approach developed in our lab, evaluating its limits and informing its application in studies aimed at characterising the metabolic state of human brain tissue over time. Our analysis focussed on the estimates of oxygen extraction fraction (OEF), cerebral blood flow (CBF), CBF-related cerebrovascular reactivity (CVR) and CMRO 2 based on a forward model that describes analytically the acquired dual echo GRE signal.Indices of within-and between-session repeatability are calculated from two different datasets both at a bulk grey matter and at a voxel-wise resolution and finally compared with similar indices obtained from previous MRI and PET measurements. Within-and between-session values of intra-subject coefficient of variation (CV intra ) calculated from bulk grey matter estimates 6.7 AE 6.6% (mean AE std.) and 10.5 AE 9.7% for OEF, 6.9 AE 6% and 5.5 AE 4.7% for CBF, 12 AE 9.7% and 12.3 AE 10% for CMRO 2 . Coefficient of variation (CV) and intraclass correlation coefficient (ICC) maps showed the spatial distribution of the repeatability metrics, informing on the feasibility limits of the method.In conclusion, results show an overall consistency of the estimated physiological parameters with literature reports and a satisfactory level of repeatability considering the higher spatial sensitivity compared to other MRI methods, with varied performance depending on the specific parameter under analysis, on the spatial resolution considered and on the study design. IntroductionBrain activity is reliant on energy release principally through oxidative metabolism. For this reason, a number of MRI methods are under development to directly quantify the rate of cerebral metabolic oxygen consumption (CMRO 2 ). CMRO 2 offers a marker of the physiological state of brain tissue (Lin et al., 2010), with potential applications in tumour (Brown and Wilson, 2004), stroke (Derdeyn et al., 2002), neurological (Santens et al., 1997) and neurodegenerative disorders (Ishii et al., 1996).PET imaging based on an oxygen isotope ( 15 O) is often still regarded as the gold standard for obtaining whole brain CMRO 2 maps despite the technical complexity, the risks related to the administration of ionising radiation and the implicit limits for longitudinal studies. Recent MRI methods for measurement of CMRO 2 have been introduced based on exploiting the magnetic field differences between the superior sagit...
The measurement of the absolute rate of cerebral metabolic oxygen consumption (CMRO) is likely to offer a valuable biomarker in many brain diseases and could prove to be important in our understanding of neural function. As such there is significant interest in developing robust MRI techniques that can quantify CMRO non-invasively. One potential MRI method for the measurement of CMRO is via the combination of fMRI and cerebral blood flow (CBF) data acquired during periods of hypercapnic and hyperoxic challenges. This method is based on the combination of two, previously independent, signal calibration techniques. As such analysis of the data has been approached in a stepwise manner, feeding the results of one calibration experiment into the next. Analysing the data in this manner can result in unstable estimates of the output parameter (CMRO), due to the propagation of errors along the analysis pipeline. Here we present a forward modelling approach that estimates all the model parameters in a one-step solution. The method is implemented using a regularized non-linear least squares approach to provide a robust and computationally efficient solution. The proposed framework is compared with previous analytical approaches using modelling studies and in vivo acquisitions in healthy volunteers (n=10). The stability of parameter estimates is demonstrated to be superior to previous methods (both in vivo and in simulation). In vivo estimates made with the proposed framework also show better agreement with expected physiological variation, demonstrating a strong negative correlation between baseline CBF and oxygen extraction fraction. It is anticipated that the proposed analysis framework will increase the reliability of absolute CMRO measurements made with calibrated BOLD.
This study aims to map the acute effects of caffeine ingestion on grey matter oxygen metabolism and haemodynamics with a novel MRI method. Sixteen healthy caffeine consumers (8 males, age=24.7±5.1) were recruited to this randomised, double-blind, placebo-controlled study. Each participant was scanned on two days before and after the delivery of an oral caffeine (250mg) or placebo capsule. Our measurements were obtained with a newly proposed estimation approach applied to data from a dual calibration fMRI experiment that uses hypercapnia and hyperoxia to modulate brain blood flow and oxygenation. Estimates were based on a forward model that describes analytically the contributions of cerebral blood flow (CBF) and of the measured end-tidal partial pressures of CO and O to the acquired dual-echo GRE signal. The method allows the estimation of grey matter maps of: oxygen extraction fraction (OEF), CBF, CBF-related cerebrovascular reactivity (CVR) and cerebral metabolic rate of oxygen consumption (CMRO). Other estimates from a multi inversion time ASL acquisition (mTI-ASL), salivary samples of the caffeine concentration and behavioural measurements are also reported. We observed significant differences between caffeine and placebo on average across grey matter, with OEF showing an increase of 15.6% (SEM±4.9%, p<0.05) with caffeine, while CBF and CMRO showed differences of -30.4% (SEM±1.6%, p<0.01) and -18.6% (SEM±2.9%, p<0.01) respectively with caffeine administration. The reduction in oxygen metabolism found is somehow unexpected, but consistent with a hypothesis of decreased energetic demand, supported by previous electrophysiological studies reporting reductions in spectral power with EEG. Moreover the maps of the physiological parameters estimated illustrate the spatial distribution of changes across grey matter enabling us to localise the effects of caffeine with voxel-wise resolution. CBF changes were widespread as reported by previous findings, while changes in OEF were found to be more restricted, leading to unprecedented mapping of significant CMRO reductions mainly in frontal gyrus, parietal and occipital lobes. In conclusion, we propose the estimation framework based on our novel forward model with a dual calibrated fMRI experiment as a viable MRI method to map the effects of drugs on brain oxygen metabolism and haemodynamics with voxel-wise resolution.
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