Blood oxygenation level-dependent (BOLD)-based techniques for the quantification of brain hemodynamic and metabolic properties - theoretical models and experimental approaches.
ABSTRACT: The quantitative evaluation of brain hemodynamics and metabolism, particularly the relationship between brain function and oxygen utilization, is important for the understanding of normal human brain operation, as well as the pathophysiology of neurological disorders. It can also be of great importance for the evaluation of hypoxia within tumors of the brain and other organs. A fundamental discovery by Ogawa and coworkers of the blood oxygenation level-dependent (BOLD) contrast opened up the possibility to use this effect to study brain hemodynamic and metabolic properties by means of MRI measurements. Such measurements require the development of theoretical models connecting the MRI signal to brain structure and function, and the design of experimental techniques allowing MR measurements to be made of the salient features of theoretical models. In this review, we discuss several such theoretical models and experimental methods for the quantification of brain hemodynamic and metabolic properties. The review's main focus is on methods for the evaluation of the oxygen extraction fraction (OEF) based on the measurement of the blood oxygenation level. A combination of the measurement of OEF and the cerebral blood flow (CBF) allows an evaluation to be made of the cerebral metabolic rate of oxygen consumption (CMRO2 ). We first consider in detail the magnetic properties of blood - magnetic susceptibility, MR relaxation and theoretical models of the intravascular contribution to the MR signal under different experimental conditions. We then describe a 'through-space' effect - the influence of inhomogeneous magnetic fields, created in the extravascular space by intravascular deoxygenated blood, on the formation of the MR signal. Further, we describe several experimental techniques taking advantage of these theoretical models. Some of these techniques - MR susceptometry and T2 -based quantification of OEF - utilize the intravascular MR signal. Another technique - quantitative BOLD - evaluates OEF by making use of through-space effects. In this review, we target both scientists just entering the MR field and more experienced MR researchers interested in the application of advanced BOLD-based techniques to the study of the brain in health and disease.
Project description:Magnetic resonance (MR)-based oxygen extraction fraction (OEF) measurement techniques that use blood oxygen level-dependent (BOLD)-based approaches require the measurement of the R2' decay rate and deoxygenated blood volume to derive the local oxygen saturation in vivo. We describe here a novel approach to measure OEF using rapid local frequency mapping. By modeling the MR decay process in the static dephasing regime as two separate dissipative and oscillatory effects, we calculate the OEF from local frequencies measured across the brain by assuming that the biophysical mechanisms causing OEF-related frequency changes can be determined from the oscillatory effects. The Parameter Assessment by Retrieval from Signal Encoding (PARSE) technique was used to acquire the local frequency change maps. The PARSE images were taken on 11 normal volunteers, and 1 patient exhibiting hemodynamic stress. The mean MR-OEF in 11 normal subjects was 36.66±7.82%, in agreement with positron emission tomography (PET) literature. In regions of hemodynamic stress induced by vascular steal, OEF exhibits the predicted focal increases. These preliminary results show that it is possible to measure OEF using a rapid frequency mapping technique. Such a technique has numerous advantages including speed of acquisition, is noninvasive, and has sufficient spatial and temporal resolution.
Project description:Quantitative BOLD (qBOLD) is a technique for mapping oxygen extraction fraction (OEF) and deoxygenated blood volume (DBV) in the human brain. Recent measurements using an asymmetric spin echo (ASE) based qBOLD approach produced estimates of DBV which were systematically higher than measurements from other techniques. In this study, we investigate two hypotheses for the origin of this DBV overestimation using simulations and consider the implications for experimental measurements. Investigations were performed by combining Monte Carlo simulations of extravascular signal with an analytical model of the intravascular signal. HYPOTHESIS 1: DBV overestimation is due to the presence of intravascular signal which is not accounted for in the analysis model. Intravascular signal was found to have a weak effect on qBOLD parameter estimates. HYPOTHESIS 2: DBV overestimation is due to the effects of diffusion which are not accounted for in the analysis model. The effect of diffusion on the extravascular signal was found to result in a vessel radius dependent variation in qBOLD parameter estimates. In particular, DBV overestimation peaks for vessels with radii from 20 to 30??m and is OEF dependent. This results in the systematic underestimation of OEF. IMPLICATIONS: The impact on experimental qBOLD measurements was investigated by simulating a more physiologically realistic distribution of vessel sizes with a small number of discrete radii. Overestimation of DBV consistent with previous experiments was observed, which was also found to be OEF dependent. This results in the progressive underestimation of the measured OEF. Furthermore, the relationship between the measured OEF and the true OEF was found to be dependent on echo time and spin echo displacement time. The results of this study demonstrate the limitations of current ASE based qBOLD measurements and provide a foundation for the optimisation of future acquisition approaches.
Project description:Streamlined Quantitative BOLD (sqBOLD) is an MR technique that can non-invasively measure physiological parameters including Oxygen Extraction Fraction (OEF) and deoxygenated blood volume (DBV) in the brain. Current sqBOLD methodology rely on fitting a linear model to log-transformed data acquired using an Asymmetric Spin Echo (ASE) pulse sequence. In this paper, a non-linear model implemented in a Bayesian framework was used to fit physiological parameters to ASE data. This model makes use of the full range of available ASE data, and incorporates the signal contribution from venous blood, which was ignored in previous analyses. Simulated data are used to demonstrate the intrinsic difficulty in estimating OEF and DBV simultaneously, and the benefits of the proposed non-linear model are shown. In vivo data are used to show that this model improves parameter estimation when compared with literature values. The model and analysis framework can be extended in a number of ways, and can incorporate prior information from external sources, so it has the potential to further improve OEF estimation using sqBOLD.
Project description:Parenchymal extravascular R2* is an important parameter for quantitative blood oxygenation level-dependent (BOLD) studies. Total and intravascular R2* values and changes in R2* values during functional stimulations have been reported in a number of studies. The purpose of this study was to measure absolute extravascular R2* values in human visual cortex and to estimate the intra- and extravascular contributions to the BOLD effect at 7 T. Vascular space occupancy (VASO) MRI was employed to separate out the extravascular tissue signal. Multi-echo VASO and BOLD functional MRI (fMRI) with visual stimulation were performed at 7 T for R2* measurement at a spatial resolution of 2.5 × 2.5 × 2.5 mm(3) in healthy volunteers (n = 6). The ratio of changes in extravascular and total R2* (ΔR2*) was used to estimate the extravascular fraction of the BOLD effect. Extravascular R2* values were found to be 44.66 ± 1.55 and 43.38 ± 1.51 s(-1) (mean ± standard error of the mean, n = 6) at rest and activation, respectively, in human visual cortex at 7 T. The extravascular BOLD fraction was estimated to be 91 ± 3%. The parenchymal oxygen extraction fraction (OEF) during activation was estimated to be 0.24 ± 0.01 based on the R2* measurements, indicating an approximately 37% decrease compared with OEF at rest.
Project description:After its discovery in 1990, blood oxygenation level-dependent (BOLD) contrast in functional magnetic resonance imaging (fMRI) has been widely used to map brain activation in humans and animals. Since fMRI relies on signal changes induced by neural activity, its signal source can be complex and is also dependent on imaging parameters and techniques. In this review, we identify and describe the origins of BOLD fMRI signals, including the topics of (1) effects of spin density, volume fraction, inflow, perfusion, and susceptibility as potential contributors to BOLD fMRI, (2) intravascular and extravascular contributions to conventional gradient-echo and spin-echo BOLD fMRI, (3) spatial specificity of hemodynamic-based fMRI related to vascular architecture and intrinsic hemodynamic responses, (4) BOLD signal contributions from functional changes in cerebral blood flow (CBF), cerebral blood volume (CBV), and cerebral metabolic rate of O(2) utilization (CMRO(2)), (5) dynamic responses of BOLD, CBF, CMRO(2), and arterial and venous CBV, (6) potential sources of initial BOLD dips, poststimulus BOLD undershoots, and prolonged negative BOLD fMRI signals, (7) dependence of stimulus-evoked BOLD signals on baseline physiology, and (8) basis of resting-state BOLD fluctuations. These discussions are highly relevant to interpreting BOLD fMRI signals as physiological means.
Project description:As energy metabolism in the brain is largely oxidative, the measurement of cerebral metabolic rate of oxygen consumption (CMRO<sub>2</sub>) 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<sub>2</sub> 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<sub>2</sub> 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<sub>intra</sub>) calculated from bulk grey matter estimates 6.7?±?6.6% (mean?±?std.) and 10.5?±?9.7% for OEF, 6.9?±?6% and 5.5?±?4.7% for CBF, 12?±?9.7% and 12.3?±?10% for CMRO<sub>2</sub>. 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.
Project description:PURPOSE:T2 -relaxation-under-spin-tagging (TRUST) is an MR technique for the non-invasive assessment of whole-brain cerebral oxygen extraction fraction (OEF), through measurement of the venous blood T2 relaxation time in the sagittal sinus. A key limitation of TRUST, however, is the lack of spatial specificity of the measurement. We sought to develop a modified TRUST sequence, selective localized TRUST (SL-TRUST), having sensitivity to venous blood T2 within a targeted brain region, and therefore achieving spatially localized measurements of cerebral tissue OEF, while still retaining acquisition in the sagittal sinus. METHODS:A method for selective localization of TRUST sequence was developed, and the reproducibility of the technique was evaluated in healthy participants. Regional measurements were achieved for a single hemisphere and for a 3D-localized 70 × 70 × 80 mm3 tissue region using SL-TRUST and compared to a global TRUST measure. An additional measure of venous blood T1 in the sagittal sinus was used to estimate subject-specific hematocrit. Six subjects were scanned over 4 sessions, including intra-session repeat measurements. RESULTS:The average T2 in the sagittal sinus was found to be 60.8 ± 8.9, 62.7 ± 7.9, 64.6 ± 8.4, and 66.3 ± 10.3 ms (mean ± SD) for conventional TRUST, global SL-TRUST, hemispheric SL-TRUST, and 3D-localized SL-TRUST, respectively. Intra-, inter-session, and inter-subject coefficients of variation for OEF using SL-TRUST were found to be comparable and in some cases superior to those obtained using TRUST. CONCLUSION:OEF comparison of 2 contralateral regions was achievable in under 5 min suggesting SL-TRUST offers potential for quantifying regional OEF differences in both healthy and clinical populations.
Project description:We describe the use of the three dimensional characteristics of the functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) and cerebral blood volume (CBV) MRI signal changes to refine a two dimensional optical imaging spectroscopy (OIS) algorithm. The cortical depth profiles of the BOLD and CBV changes following neural activation were used to parameterise a 5-layer heterogeneous tissue model used in the Monte Carlo simulations (MCS) of light transport through tissue in the OIS analysis algorithm. To transform the fMRI BOLD and CBV measurements into deoxy-haemoglobin (Hbr) profiles we inverted an MCS of extra-vascular MR signal attenuation under the assumption that the extra-/intravascular ratio is 2:1 at a magnetic field strength of 3 T. The significant improvement in the quantitative accuracy of haemodynamic measurements using the new heterogeneous tissue model over the original homogeneous tissue model OIS algorithm was demonstrated on new concurrent OIS and fMRI data covering a range of stimulus durations.
Project description:Traumatic brain injury (TBI) is a leading cause of death and disability in children. Metabolic failure is an integral component of the pathological aftermath of TBI. The oxygen extraction fraction (OEF) is a valuable parameter for characterization and description of metabolic abnormalities; however, OEF measurement has required either invasive procedures or the use of ionizing radiation, which significantly limits its use in pediatric research.Patients with TBI had depressed OEF levels that correlated with the severity of injury. In addition, the OEF measured within 2 weeks of injury was predictive of patient outcome at 3 mo after injury. In pediatric TBI patients, low OEF-a marker of metabolic dysfunction-correlates with the severity of injury and outcome.Our findings support previous literature on the role of metabolic dysfunction after TBI.Using a recently developed magnetic resonance (MR) technique for the measurement of oxygen saturation, we determined the whole-brain OEF in both pediatric TBI patients and in healthy controls. Injury and outcome were classified using pediatric versions of the Glasgow Coma Scale (GCS) and Glasgow Outcome Scale-Extended (GOS-E), respectively.