Quantitative BOLD: the effect of diffusion

Quantitative BOLD (qBOLD) imaging of oxygen metabolism and blood oxygenation in the human body: A scoping review

PURPOSE

There are many approaches to the quantitative BOLD (qBOLD) technique described in the literature, differing in pulse sequences, MRI parameters and data processing. Thus, in this review, we summarized the acquisition methods, approaches used for oxygenation quantification and clinical populations investigated.

METHODS

Three databases were systematically searched (Medline, Embase, and Web of Science) for published research that used qBOLD methods for quantification of oxygen metabolism. Data extraction and synthesis were performed by one author and reviewed by a second author.

RESULTS

A total of 93 relevant papers were identified. Acquisition strategies were summarized, and oxygenation parameters were found to have been investigated in many pathologies such as steno-occlusive diseases, stroke, glioma, and multiple sclerosis disease.

CONCLUSION

A summary of qBOLD approaches for oxygenation measurements and applications could help researchers to identify good practice and provide objective information to inform the development of future consensus recommendations.

Streamlined quantitative BOLD for detecting visual stimulus-induced changes in oxygen extraction fraction in healthy participants: toward clinical application in human glioma

OBJECTIVE

Monitoring brain oxygenation is critical in brain tumors, as low oxygenation influences tumor growth, pathological angiogenesis, and treatment resistance. This study examined the ability of the streamlined quantitative (sq)BOLD MRI technique to detect oxygenation changes in healthy individuals, as well as its potential application in a clinical setting.

METHODS

We used the asymmetric spin echo (ASE) technique with FLAIR preparation, along with model-based Bayesian inference to quantify the reversible transverse relaxation rate (R2') and oxygen extraction fraction (OEF) across the brain at baseline and during visual stimulation in eight healthy participants at 3T; and two patients with glioma at rest only.

RESULTS

Comparing sqBOLD-derived parameters between baseline and visual stimulation revealed a decrease in OEF from 0.56 ± 0.09 at baseline to 0.54 ± 0.07 at the activated state (p = 0.04, paired t test) within a functional localizer-defined volume of interest, and a decline in R2' from 6.5 ± 1.3s-1 at baseline to 6.2 ± 1.4s-1 at the activated state (p = 0.006, paired t test) in the visual cortex.

CONCLUSION

The sqBOLD technique is sensitive enough to detect and quantify changes in oxygenation in the healthy brain and shows potential for integration into clinical settings to provide valuable information on oxygenation in glioma.

Microvascular Specificity of Spin Echo BOLD fMRI: Impact of EPI Echo Train Length

A spatially specific fMRI acquisition requires specificity to the microvasculature that serves active neuronal sites. Macrovascular contributions will reduce the microvascular specificity but can be reduced by using spin echo (SE) sequences that use a π pulse to refocus static field inhomogeneities near large veins. The microvascular specificity of a SE-echo planar imaging (SE-EPI) scan depends on the echo train length (ETL)-duration, but the dependence is not well-characterized in humans at 7T. To determine how microvascular-specific SE-EPI BOLD is in humans at 7T, we developed a Monte Carlo voxel model that computes the signal of a proton ensemble residing in a vasculature subjected to a SE-EPI pulse sequence. We characterized the ETL-duration dependence of the microvascular specificity by simulating the BOLD signal as a function of ETL, the range adhering to experimentally realistic readouts. We performed a validation experiment for our simulation observations, in which we acquired a set of SE-EPI BOLD time series with varying ETL during a hyperoxic gas challenge. Both our simulations and measurements show an increase in macrovascular contamination as a function of ETL, with an increase of 30% according to our simulation and 60% according to our validation experiment between the shortest and longest ETL durations (23.1 - 49.7 ms). We conclude that the microvascular specificity decreases heavily with increasing ETL-durations. We recommend reducing the ETL-duration as much as possible to minimize macrovascular contamination in SE-EPI BOLD experiments. We additionally recommend scanning at high resolutions to minimize partial volume effects with CSF. CSF voxels show a large BOLD response, which can be attributed to both the presence of large veins (high blood volume) and molecular oxygen-induced T1-shortening (significant in a hyperoxia experiment). The magnified BOLD signal in a GM-CSF partial volume voxel reduces the desired microvascular specificity and, therefore, will hinder the interpretation of functional MRI activation patterns.

Measurement of Cerebral Oxygen Extraction Fraction Using Quantitative BOLD Approach: A Review

Quantification of brain oxygenation and metabolism, both of which are indicators of the level of brain activity, plays a vital role in understanding the cerebral perfusion and the pathophysiology of brain disorders. Magnetic resonance imaging (MRI), a widely used clinical imaging technique, which is very sensitive to magnetic susceptibility, has the possibility of substituting positron emission tomography (PET) in measuring oxygen metabolism. This review mainly focuses on the quantitative blood oxygenation level-dependent (qBOLD) method for the evaluation of oxygen extraction fraction (OEF) in the brain. Here, we review the theoretic basis of qBOLD, as well as existing acquisition and quantification methods. Some published clinical studies are also presented, and the pros and cons of qBOLD method are discussed as well.

Review of the Research Progress of Human Brain Oxygen Extraction Fraction by Magnetic Resonance Imaging

In recent years, the incidence of cerebrovascular diseases (CVD) is increasing, which seriously endangers human health. The study on hemodynamics of cerebrovascular disease can help us to understand, prevent, and treat the disease. As one of the important parameters of human cerebral hemodynamics and tissue metabolism, OEF (oxygen extraction fraction) is of great value in central nervous system diseases. The use of BOLD (blood oxygen level dependent) effect offers the possibility to study cerebral hemodynamic and metabolic characteristics by MRI (magnetic resonance imaging) measurements. Therefore, this paper reviews the hemodynamic parameters of brain tissue, discusses the principles and methods of quantitative BOLD-based MRI measurements of OEF, and discusses the advantages and disadvantages of each method.

Mapping oxidative metabolism in the human brain with calibrated fMRI in health and disease

Conventional functional MRI (fMRI) with blood-oxygenation level dependent (BOLD) contrast is an important tool for mapping human brain activity non-invasively. Recent interest in quantitative fMRI has renewed the importance of oxidative neuroenergetics as reflected by cerebral metabolic rate of oxygen consumption (CMR_O2) to support brain function. Dynamic CMR_O2 mapping by calibrated fMRI require multi-modal measurements of BOLD signal along with cerebral blood flow (CBF) and/or volume (CBV). In human subjects this "calibration" is typically performed using a gas mixture containing small amounts of carbon dioxide and/or oxygen-enriched medical air, which are thought to produce changes in CBF (and CBV) and BOLD signal with minimal or no CMR_O2 changes. However non-human studies have demonstrated that the "calibration" can also be achieved without gases, revealing good agreement between CMR_O2 changes and underlying neuronal activity (e.g., multi-unit activity and local field potential). Given the simpler set-up of gas-free calibrated fMRI, there is evidence of recent clinical applications for this less intrusive direction. This up-to-date review emphasizes technological advances for such translational gas-free calibrated fMRI experiments, also covering historical progression of the calibrated fMRI field that is impacting neurological and neurodegenerative investigations of the human brain.

Cerebral oxygen extraction fraction MRI: Techniques and applications

The human brain constitutes 2% of the body's total mass but uses 20% of the oxygen. The rate of the brain's oxygen utilization can be derived from a knowledge of cerebral blood flow and the oxygen extraction fraction (OEF). Therefore, OEF is a key physiological parameter of the brain's function and metabolism. OEF has been suggested to be a useful biomarker in a number of brain diseases. With recent advances in MRI techniques, several MRI-based methods have been developed to measure OEF in the human brain. These MRI OEF techniques are based on the T₂ of blood, the blood signal phase, the magnetic susceptibility of blood-containing voxels, the effect of deoxyhemoglobin on signal behavior in extravascular tissue, and the calibration of the BOLD signal using gas inhalation. Compared to ¹⁵ O PET, which is considered the "gold standard" for OEF measurement, MRI-based techniques are non-invasive, radiation-free, and are more widely available. This article provides a review of these emerging MRI-based OEF techniques. We first briefly introduce the role of OEF in brain oxygen homeostasis. We then review the methodological aspects of different categories of MRI OEF techniques, including their signal mechanisms, acquisition methods, and data analyses. The strengths and limitations of the techniques are discussed. Finally, we review key applications of these techniques in physiological and pathological conditions.

Whole-brain 3D mapping of oxygen metabolism using constrained quantitative BOLD

Quantitative BOLD (qBOLD) MRI permits noninvasive evaluation of hemodynamic and metabolic states of the brain by quantifying parametric maps of deoxygenated blood volume (DBV) and hemoglobin oxygen saturation level of venous blood (Y_v), and along with a measurement of cerebral blood flow (CBF), the cerebral metabolic rate of oxygen (CMRO₂). The method, thus should have potential to provide important information on many neurological disorders as well as normal cerebral physiology. One major challenge in qBOLD is to separate de-oxyhemoglobin’s contribution to R₂′ from other sources modulating the voxel signal, for instance, R₂, R₂′ from non-heme iron (R′_2,nh), and macroscopic magnetic field variations. Further, even with successful separation of the several confounders, it is still challenging to extract DBV and Y_v from the heme-originated R₂′ because of limited sensitivity of the qBOLD model. These issues, which have not been fully addressed in currently practiced qBOLD methods, have so far precluded 3D whole-brain implementation of qBOLD. Thus, the purpose of this work was to develop a new 3D MRI oximetry technique that enables robust qBOLD parameter mapping across the entire brain. To achieve this goal, we employed a rapid, R₂′-sensitive, steady-state 3D pulse sequence (termed ‘AUSFIDE’) for data acquisition, and implemented a prior-constrained qBOLD processing pipeline that exploits a plurality of preliminary parameters obtained via AUSFIDE, along with additionally measured cerebral venous blood volume. Numerical simulations and in vivo studies at 3 T were performed to evaluate the performance of the proposed, constrained qBOLD mapping in comparison to the parent qBOLD method. Measured parameters (Y_v, DBV, R′_2,nh, nonblood magnetic susceptibility) in ten healthy subjects demonstrate the expected contrast across brain territories, while yielding group-averages of 64.0 ± 2.3 % and 62.2 ± 3.1 % for Y_v and 2.8 ± 0.5 % and 1.8 ± 0.4 % for DBV in cortical gray and white matter, respectively. Given the Y_v measurements, additionally quantified CBF in seven of the ten study subjects enabled whole-brain 3D CMRO₂ mapping, yielding group averages of 134.2 ± 21.1 and 79.4 ± 12.6 µmol/100 g/min for cortical gray and white matter, in good agreement with literature values. The results suggest feasibility of the proposed method as a practical and reliable means for measuring neurometabolic parameters over an extended brain coverage.

Effects of mild hypoxia on oxygen extraction fraction responses to brain stimulation

Characterizing the effect of limited oxygen availability on brain metabolism during brain activation is an essential step towards a better understanding of brain homeostasis and has obvious clinical implications. However, how the cerebral oxygen extraction fraction (OEF) depends on oxygen availability during brain activation remains unclear, which is mostly attributable to the scarcity and safety of measurement techniques. Recently, a magnetic resonance imaging (MRI) method that enables noninvasive and dynamic measurement of the OEF has been developed and confirmed to be applicable to functional MRI studies. Using this novel method, the present study investigated the motor-evoked OEF response in both normoxia (21% O₂) and hypoxia (12% O₂). Our results showed that OEF activation decreased in the brain areas involved in motor task execution. Decreases in the motor-evoked OEF response were greater under hypoxia (-21.7% ± 5.5%) than under normoxia (-11.8% ± 3.7%) and showed a substantial decrease as a function of arterial oxygen saturation. These findings suggest a different relationship between oxygen delivery and consumption during hypoxia compared to normoxia. This methodology may provide a new perspective on the effects of mild hypoxia on brain function.

Model-based Bayesian inference of brain oxygenation using quantitative BOLD

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.

The potential for gas-free measurements of absolute oxygen metabolism during both baseline and activation states in the human brain

Quantitative functional magnetic resonance imaging methods make it possible to measure cerebral oxygen metabolism (CMRO₂) in the human brain. Current methods require the subject to breathe special gas mixtures (hypercapnia and hyperoxia). We tested a noninvasive suite of methods to measure absolute CMRO₂ in both baseline and dynamic activation states without the use of special gases: arterial spin labeling (ASL) to measure baseline and activation cerebral blood flow (CBF), with concurrent measurement of the blood oxygenation level dependent (BOLD) signal as a dynamic change in tissue R₂*; VSEAN to estimate baseline O₂ extraction fraction (OEF) from a measurement of venous blood R₂, which in combination with the baseline CBF measurement yields an estimate of baseline CMRO₂; and FLAIR-GESSE to measure tissue R₂' to estimate the scaling parameter needed for calculating the change in CMRO₂ in response to a stimulus with the calibrated BOLD method. Here we describe results for a study sample of 17 subjects (8 female, mean age = 25.3 years, range 21-31 years). The primary findings were that OEF values measured with the VSEAN method were in good agreement with previous PET findings, while estimates of the dynamic change in CMRO₂ in response to a visual stimulus were in good agreement between the traditional hypercapnia calibration and calibration based on R₂'. These results support the potential of gas-free methods for quantitative physiological measurements.

Simulations of the effect of diffusion on asymmetric spin echo based quantitative BOLD: An investigation of the origin of deoxygenated blood volume overestimation

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 μm 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.

Using an artificial neural network for fast mapping of the oxygen extraction fraction with combined QSM and quantitative BOLD

PURPOSE

To apply an artificial neural network (ANN) for fast and robust quantification of the oxygen extraction fraction (OEF) from a combined QSM and quantitative BOLD analysis of gradient echo data and to compare the ANN to a traditional quasi-Newton (QN) method for numerical optimization.

METHODS

Random combinations of OEF, deoxygenated blood volume ( ν ), R₂ , and nonblood magnetic susceptibility ( χ nb ) with each parameter following a Gaussian distribution that represented physiological gray matter and white matter values were used to simulate quantitative BOLD signals and QSM values. An ANN was trained with the simulated data with added Gaussian noise. The ANN was applied to multigradient echo brain data of 7 healthy subjects, and the reconstructed parameters and maps were compared to QN results using Student t test and Bland-Altman analysis.

RESULTS

Intersubject means and SDs of gray matter were OEF = 43.5 ± 0.8 %, R 2 = 13.5 ± 0.3 Hz, ν = 3.4 ± 0.1 %, χ nb = - 25 ± 5 ppb for ANN; and OEF = 43.8 ± 5.2 %, R 2 = 12.2 ± 0.8 Hz, ν = 4.2 ± 0.6 %, χ nb = - 39 ± 7 ppb for QN, with a significant difference ( P < 0.05 ) for R 2 , ν , and χ nb . For white matter, they were OEF = 47.5 ± 1.1 %, R 2 = 17.1 ± 0.4 Hz, ν = 2.5 ± 0.2 %, χ nb = - 38 ± 5 ppb for ANN; and OEF = 42.3 ± 5.6 %, R 2 = 16.7 ± 0.7 Hz, ν = 2.9 ± 0.3 %, χ nb = - 45 ± 9 ppb for QN, with a significant difference ( P < 0.05 ) for OEF and ν . ANN revealed more gray-white matter contrast but less intersubject variation in OEF than QN. In contrast to QN, the ANN reconstruction did not need an additional sequence for parameter initialization and took approximately 1 s rather than roughly 1 h.

CONCLUSION

ANNs allow faster and, with regard to initialization, more robust reconstruction of OEF maps with lower intersubject variation than QN approaches.

A streamlined acquisition for mapping baseline brain oxygenation using quantitative BOLD

Quantitative BOLD (qBOLD) is a non-invasive MR technique capable of producing quantitative measurements of the haemodynamic and metabolic properties of the brain. Here we propose a refinement of the qBOLD methodology, dubbed streamlined-qBOLD, in order to provide a clinically feasible method for mapping baseline brain oxygenation. In streamlined-qBOLD confounding signal contributions are minimised during data acquisition through the application of (i) a Fluid Attenuated Inversion Recovery (FLAIR) preparation to remove cerebral spinal fluid (CSF) signal contamination, (ii) a Gradient Echo Slice Excitation Profile Imaging (GESEPI) acquisition to reduce the effect of macroscopic magnetic field gradients and (iii) an Asymmetric Spin Echo (ASE) pulse sequence to directly measure the reversible transverse relaxation rate, R₂'. Together these features simplify the application of the qBOLD model, improving the robustness of the resultant parametric maps. A theoretical optimisation framework was used to optimise acquisition parameters in relation to signal to noise ratio. In a healthy subject group (n = 7) apparent elevations in R₂' caused by partial volumes of CSF were shown to be reduced with the application of CSF nulling. Significant decreases in R₂' (p < 0.001) and deoxygenated blood volume (p < 0.01) were seen in cortical grey matter, across the group, with the application of CSF suppression. Quantitative baseline brain oxygenation parameter maps were calculated using qBOLD modelling and compared with literature values.

A novel Bayesian approach to accounting for uncertainty in fMRI-derived estimates of cerebral oxygen metabolism fluctuations

Calibrated blood oxygenation level dependent (BOLD) imaging is a multimodal functional MRI technique designed to estimate changes in cerebral oxygen metabolism from measured changes in cerebral blood flow and the BOLD signal. This technique addresses fundamental ambiguities associated with quantitative BOLD signal analysis; however, its dependence on biophysical modeling creates uncertainty in the resulting oxygen metabolism estimates. In this work, we developed a Bayesian approach to estimating the oxygen metabolism response to a neural stimulus and used it to examine the uncertainty that arises in calibrated BOLD estimation due to the presence of unmeasured model parameters. We applied our approach to estimate the CMRO2 response to a visual task using the traditional hypercapnia calibration experiment as well as to estimate the metabolic response to both a visual task and hypercapnia using the measurement of baseline apparent R2' as a calibration technique. Further, in order to examine the effects of cerebral spinal fluid (CSF) signal contamination on the measurement of apparent R2', we examined the effects of measuring this parameter with and without CSF-nulling. We found that the two calibration techniques provided consistent estimates of the metabolic response on average, with a median R2'-based estimate of the metabolic response to CO2 of 1.4%, and R2'- and hypercapnia-calibrated estimates of the visual response of 27% and 24%, respectively. However, these estimates were sensitive to different sources of estimation uncertainty. The R2'-calibrated estimate was highly sensitive to CSF contamination and to uncertainty in unmeasured model parameters describing flow-volume coupling, capillary bed characteristics, and the iso-susceptibility saturation of blood. The hypercapnia-calibrated estimate was relatively insensitive to these parameters but highly sensitive to the assumed metabolic response to CO2.

Comparison of R2' measurement methods in the normal brain at 3 Tesla

PURPOSE

R2', the reversible component of transverse relaxation, is an important susceptibility measurement for studies of brain physiology and pathologies. In existing literature, different R2' measurement methods are used with assumption of equivalency. This study explores the choice of measurement method in healthy, young subjects at 3T.

METHODS

In this study, a modified gradient-echo sampling of free induction decay and echo (GESFIDE) sequence was used to compare four standard R2' measurement methods: asymmetric spin echo (ASE), standard GESFIDE, gradient echo sampling of the spin echo (GESSE), and separate R2 and R2* mapping.

RESULTS

GESSE returned lower R2' measurements than other methods (P < 0.05). Intersubject mean R2' in gray matter was found to be 2.7 s(-1) using standard GESFIDE and GESSE, versus 3.4-3.8 s(-1) using other methods. In white matter, mean R2' from GESSE was 2.3 s(-1) while other methods produced 3.7-4.3 s(-1) . R2 correction was applied to partially reduce the discrepancies between the methods, but significant differences remained, likely due to violation of the fundamental assumption of a single-compartmental tissue model, and hence monoexponential decay.

CONCLUSION

R2' measurements are influenced significantly by the choice of method. Awareness of this issue is important when designing and interpreting studies that involve R2' measurements.

Correlation of oxygenation and perfusion sensitive MRI with invasive micro probe measurements in healthy mice brain

The non-invasive assessment of (patho-)physiological parameters such as, perfusion and oxygenation, is of great importance for the characterization of pathologies e.g., tumors, which may be helpful to better predict treatment response and potential outcome. To better understand the influence of physiological parameters on the investigated oxygenation and perfusion sensitive MRI methods, MRI measurements were correlated with subsequent invasive micro probe measurements during free breathing conditions of air, air+10% CO2 and 100% O2 in healthy mice brain. MRI parameters were the irreversible (R2), reversible (R2') and effective (R2*) transverse relaxation rates, venous blood oxygenation level assessed by quantitative blood oxygenation level dependent (qBOLD) method and cerebral blood flow (CBF) assessed by arterial spin labeling (ASL) using a 7 T small animal MRI scanner. One to two days after MRI, tissue perfusion and pO2 were measured by Laser-Doppler flowmetry and fluorescence quenching micro probes, respectively. The tissue pO2 values were converted to blood oxygen saturation by using the Hill equation. The animals were anesthetized by intra peritoneal injection of ketamine-xylazine-acepromazine (10-2-0.3 mg/ml · kg). Results for normal/hypercapnia/hyperoxia conditions were: R2[s(∧)-1] = 20.7/20.4/20.1, R2*[s(∧)-1] = 31.6/29.6/25.9, R2'[s-(∧)1] = 10.9/9.2/5.7, qBOLD venous blood oxygenation level = 0.43/0.51/0.56, CBF[ml · min(∧)-1 · 100 g(∧)-1] = 70.6/105.5/81.8, Laser-Doppler flowmetry[a.u.] = 89.2/120.2/90.6 and pO2[mmHg] = 6.3/32.3/46.7. All parameters were statistically significantly different with P < 0.001 between all breathing conditions. All MRI and the corresponding micro probe measurements were also statistically significantly (P ≤ 0.03) correlated with each other. However, converting the tissue pO2 to blood oxygen saturation = 0.02/0.34/0.63, showed only very limited agreement with the qBOLD venous blood oxygenation level. We found good correlation between MRI and micro probe measurements. However, direct conversion of tissue pO2 to blood oxygen saturation by using the Hill equation is very limited. Furthermore, adverse effects of anesthesia and trauma due to micro probe insertion are strong confounding factors and need close attention for study planning and conduction of experiments. Investigation of the correlation of perfusion and oxygenation sensitive MRI methods with micro probe measurements in pathologic tissue such as tumors is now of compelling interest.

Numerical modeling of susceptibility-related MR signal dephasing with vessel size measurement: phantom validation at 3T

PURPOSE

MRI is used to obtain quantitative oxygenation and blood volume information from the susceptibility-related MR signal dephasing induced by blood vessels. However, analytical models that fit the MR signal are usually not accurate over the range of small blood vessels. Moreover, recent studies have demonstrated limitations in the simultaneous assessment of oxygenation and blood volume. In this study, a multiparametric MRI framework that aims to measure vessel radii in addition to magnetic susceptibility and volume fraction was introduced.

METHODS

The protocol consisted of gradient-echo sampling of the spin-echo, diffusion, T2, and B0 acquisitions. After correction steps, the data were postprocessed with a versatile numerical model of the MR signal. An important analytical model was implemented for comparison. The approach was validated in phantoms with coiling strings as proxy for blood vessels.

RESULTS

The feasibility of the vessel radius measurement is demonstrated. The numerical model shows an improved accuracy compared with the analytical approach. However, both methods overestimate the radius. The simultaneous measurement of the magnetic susceptibility and the volume fraction remains challenging.

CONCLUSION

The results suggest that this approach could be interesting in vivo to better characterize the microvasculature without contrast agent.

The physics of functional magnetic resonance imaging (fMRI)

Functional magnetic resonance imaging (fMRI) is a methodology for detecting dynamic patterns of activity in the working human brain. Although the initial discoveries that led to fMRI are only about 20 years old, this new field has revolutionized the study of brain function. The ability to detect changes in brain activity has a biophysical basis in the magnetic properties of deoxyhemoglobin, and a physiological basis in the way blood flow increases more than oxygen metabolism when local neural activity increases. These effects translate to a subtle increase in the local magnetic resonance signal, the blood oxygenation level dependent (BOLD) effect, when neural activity increases. With current techniques, this pattern of activation can be measured with resolution approaching 1 mm(3) spatially and 1 s temporally. This review focuses on the physical basis of the BOLD effect, the imaging methods used to measure it, the possible origins of the physiological effects that produce a mismatch of blood flow and oxygen metabolism during neural activation, and the mathematical models that have been developed to understand the measured signals. An overarching theme is the growing field of quantitative fMRI, in which other MRI methods are combined with BOLD methods and analyzed within a theoretical modeling framework to derive quantitative estimates of oxygen metabolism and other physiological variables. That goal is the current challenge for fMRI: to move fMRI from a mapping tool to a quantitative probe of brain physiology.

Blood oxygenation level-dependent (BOLD)-based techniques for the quantification of brain hemodynamic and metabolic properties - theoretical models and experimental approaches

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.

A review of calibrated blood oxygenation level-dependent (BOLD) methods for the measurement of task-induced changes in brain oxygen metabolism

The dynamics of the blood oxygenation level-dependent (BOLD) response are dependent on changes in cerebral blood flow, cerebral blood volume and the cerebral metabolic rate of oxygen consumption. Furthermore, the amplitude of the response is dependent on the baseline physiological state, defined by the haematocrit, oxygen extraction fraction and cerebral blood volume. As a result of this complex dependence, the accurate interpretation of BOLD data and robust intersubject comparisons when the baseline physiology is varied are difficult. The calibrated BOLD technique was developed to address these issues. However, the methodology is complex and its full promise has not yet been realised. In this review, the theoretical underpinnings of calibrated BOLD, and issues regarding this theory that are still to be resolved, are discussed. Important aspects of practical implementation are reviewed and reported applications of this methodology are presented.

A simulation tool for dynamic contrast enhanced MRI

The quantification of bolus-tracking MRI techniques remains challenging. The acquisition usually relies on one contrast and the analysis on a simplified model of the various phenomena that arise within a voxel, leading to inaccurate perfusion estimates. To evaluate how simplifications in the interstitial model impact perfusion estimates, we propose a numerical tool to simulate the MR signal provided by a dynamic contrast enhanced (DCE) MRI experiment. Our model encompasses the intrinsic and relaxations, the magnetic field perturbations induced by susceptibility interfaces (vessels and cells), the diffusion of the water protons, the blood flow, the permeability of the vessel wall to the the contrast agent (CA) and the constrained diffusion of the CA within the voxel. The blood compartment is modeled as a uniform compartment. The different blocks of the simulation are validated and compared to classical models. The impact of the CA diffusivity on the permeability and blood volume estimates is evaluated. Simulations demonstrate that the CA diffusivity slightly impacts the permeability estimates ( for classical blood flow and CA diffusion). The effect of long echo times is investigated. Simulations show that DCE-MRI performed with an echo time may already lead to significant underestimation of the blood volume (up to 30% lower for brain tumor permeability values). The potential and the versatility of the proposed implementation are evaluated by running the simulation with realistic vascular geometry obtained from two photons microscopy and with impermeable cells in the extravascular environment. In conclusion, the proposed simulation tool describes DCE-MRI experiments and may be used to evaluate and optimize acquisition and processing strategies.

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

The transverse decay of the arterial spin labeling (ASL) signal was measured at four inflow times in the rat brain cortex at 9.4 T. Biexponential T2 decay was observed that appears to derive from different T2 values associated with labeled water in the intravasculature (IV) and extravascular (EV) compartments. A two compartment biexponential model was used to assess the relative contribution of the IV and EV compartments to the ASL signal, without assuming a value for T2 of labeled blood water in the vessels. This novel methodology was applied to estimate the exchange time of blood water into EV tissue space and the oxygen saturation of blood on the arterial side of the vasculature. The mean exchange time of labeled blood water was estimated to be 370±40 ms. The oxygen saturation of the arterial side of the vasculature was significantly less than 100% (∼85%), which may have implications for quantitative functional magnetic resonance imaging studies where the arterial oxygen saturation is frequently assumed to be 100%.

Parallel MR imaging

Parallel imaging is a robust method for accelerating the acquisition of magnetic resonance imaging (MRI) data, and has made possible many new applications of MR imaging. Parallel imaging works by acquiring a reduced amount of k-space data with an array of receiver coils. These undersampled data can be acquired more quickly, but the undersampling leads to aliased images. One of several parallel imaging algorithms can then be used to reconstruct artifact-free images from either the aliased images (SENSE-type reconstruction) or from the undersampled data (GRAPPA-type reconstruction). The advantages of parallel imaging in a clinical setting include faster image acquisition, which can be used, for instance, to shorten breath-hold times resulting in fewer motion-corrupted examinations. In this article the basic concepts behind parallel imaging are introduced. The relationship between undersampling and aliasing is discussed and two commonly used parallel imaging methods, SENSE and GRAPPA, are explained in detail. Examples of artifacts arising from parallel imaging are shown and ways to detect and mitigate these artifacts are described. Finally, several current applications of parallel imaging are presented and recent advancements and promising research in parallel imaging are briefly reviewed.

Approaches to brain stress testing: BOLD magnetic resonance imaging with computer-controlled delivery of carbon dioxide

Background

An impaired vascular response in the brain regionally may indicate reduced vascular reserve and vulnerability to ischemic injury. Changing the carbon dioxide (CO₂) tension in arterial blood is commonly used as a cerebral vasoactive stimulus to assess the cerebral vascular response, changing cerebral blood flow (CBF) by up to 5–11 percent/mmHg in normal adults. Here we describe two approaches to generating the CO₂ challenge using a computer-controlled gas blender to administer: i) a square wave change in CO₂ and, ii) a ramp stimulus, consisting of a continuously graded change in CO₂ over a range. Responses were assessed regionally by blood oxygen level dependent (BOLD) magnetic resonance imaging (MRI).

Methodology/Principal Findings

We studied 8 patients with known cerebrovascular disease (carotid stenosis or occlusion) and 2 healthy subjects. The square wave stimulus was used to study the dynamics of the vascular response, while the ramp stimulus assessed the steady-state response to CO₂. Cerebrovascular reactivity (CVR) maps were registered by color coding and overlaid on the anatomical scans generated with 3 Tesla MRI to assess the corresponding BOLD signal change/mmHg change in CO₂, voxel-by-voxel. Using a fractal temporal approach, detrended fluctuation analysis (DFA) maps of the processed raw BOLD signal per voxel over the same CO₂ range were generated. Regions of BOLD signal decrease with increased CO₂ (coded blue) were seen in all of these high-risk patients, indicating regions of impaired CVR. All patients also demonstrated regions of altered signal structure on DFA maps (Hurst exponents less than 0.5; coded blue) indicative of anti-persistent noise. While ‘blue’ CVR maps remained essentially stable over the time of analysis, ‘blue’ DFA maps improved.

Conclusions/Significance

This combined dual stimulus and dual analysis approach may be complementary in identifying vulnerable brain regions and thus constitute a regional as well as global brain stress test.

Imaging brain oxygenation with MRI using blood oxygenation approaches: methods, validation, and clinical applications

SUMMARY

In many pathophysiologic situations, including brain neoplasms, neurodegenerative disease, and chronic and acute ischemia, an imbalance exists between oxygen tissue consumption and delivery. Furthermore, oxygenation changes following a stress challenge, such as with carbogen gas or acetazolamide, can yield information about cerebrovascular reactivity. The unique sensitivity of the BOLD effect to the presence of deoxyhemoglobin has led to its widespread use in the field of cognitive neurosciences. However, the high spatial and temporal resolution afforded by BOLD imaging does not need to be limited to the study of healthy brains. While the complex relationship between the MR imaging signal and tissue oxygenation hinders a direct approach, many different methods have been developed during the past decade to obtain specific oxygenation measurements. These include qBOLD, phase- and susceptibility-based imaging, and intravascular T2-based approaches. The aim of this review is to give an overview of the theoretic basis of these methods as well as their application to measure oxygenation in both healthy subjects and those with disease.

Optimization strategies for evaluation of brain hemodynamic parameters with qBOLD technique

Quantitative blood oxygenation level dependent technique provides an MRI-based method to measure tissue hemodynamic parameters such as oxygen extraction fraction and deoxyhemoglobin-containing (veins and prevenous part of capillaries) cerebral blood volume fraction. It is based on a theory of MR signal dephasing in the presence of blood vessel network and experimental method-gradient echo sampling of spin echo previously proposed and validated on phantoms and animals. In vivo human studies also demonstrated feasibility of this approach but also recognized that obtaining reliable results requires high signal-to-noise ratio in the data. In this paper, we analyze in detail the uncertainties of the quantitative blood oxygenation level dependent parameter estimates in the framework of the Bayesian probability theory, namely, we examine how the estimated parameters oxygen extraction fraction and deoxygenated cerebral blood volume fraction depend on their "true values," signal-to-noise ratio, and data sampling strategies. On the basis of this analysis, we develop strategies for optimization of the quantitative blood oxygenation level dependent technique for deoxygenated cerebral blood volume and oxygen extraction fraction evaluation. In particular, it is demonstrated that the use of gradient echo sampling of spin echo sequence allows substantial decrease of measurement errors as the data are acquired on both sides of spin echo. We test our theory on phantom mimicking the structure of blood vessel network. A 3D gradient echo sampling of spin echo pulse sequence is used for the acquisition of the MRI signal that was subsequently analyzed by Bayesian Application Software. The experimental results demonstrated a good agreement with theoretical predictions.

Oxygen metabolism in ischemic stroke using magnetic resonance imaging

Detecting "at-risk" but potentially salvageable brain tissue, known as the ischemic penumbra, is of importance for identifying patients who may benefit from thrombolytic or other treatments beyond the currently FDA-approved short therapeutic window for tissue plasminogen activator. Since the magnetic resonance blood oxygenation level-dependent (BOLD) contrast may provide information concerning tissue oxygen metabolism, its utilization in ischemic stroke has been explored. The focus of this review is to provide an introduction of several BOLD-based methods, including susceptibility-weighted imaging, R2 BOLD, R2*, R2', MR_OEF, and MR_OMI approaches to assess cerebral oxygenation changes induced by ischemia. Specifically, we will review the underlying pathophysiological basis of the imaging approaches, followed by a brief introduction of BOLD contrast, and finally the applications of BOLD approaches in ischemic stroke. The advantages and disadvantages of each method are addressed. In summary, the BOLD-based methods are promising for imaging oxygenation in ischemic tissue. Future steps would include technical refinement and vigorous validation against another independent method, such as positron emission tomography.

Measuring brain oxygenation in humans using a multiparametric quantitative blood oxygenation level dependent MRI approach

Quantitative blood oxygenation level dependent approaches have been designed to obtain quantitative oxygenation information using MRI. A mathematical model is usually fitted to the time signal decay of a gradient-echo and spin-echo measurements to derive hemodynamic parameters such as the blood oxygen saturation or the cerebral blood volume. Although the results in rats and human brain have been encouraging, recent studies have pointed out the need for independent estimation of one or more variables to increase the accuracy of the method. In this study, a multiparametric quantitative blood oxygenation level dependent approach is proposed. A combination of arterial spin labeling and dynamic susceptibility contrast methods were used to obtain quantitative estimates of cerebral blood volume and cerebral blood flow. These results were combined with T 2 and T(2) measurements to derive maps of blood oxygen saturation or cerebral metabolic rate of oxygen. In 12 normal subjects, a mean cerebral blood volume of 4.33 ± 0.7%, cerebral blood flow of 43.8 ± 5.7 mL/min/100 g, blood oxygen saturation of 60 ± 6% and cerebral metabolic rate of oxygen 157 ± 23 μmol/100 g/min were found, which are in agreement with literature values. The results obtained in this study suggest that this methodology could be applied to study brain hypoxia in the setting of pathology.

Is T2* enough to assess oxygenation? Quantitative blood oxygen level-dependent analysis in brain tumor

PURPOSE

To analyze the contribution of the transverse relaxation parameter (T2), macroscopic field inhomogeneities (B0), and blood volume fraction (BVf) to blood oxygen level-dependent (BOLD)-based magnetic resonance (MR) measurements of blood oxygen saturation (SO2) obtained in a brain tumor model.

MATERIALS AND METHODS

This study was approved by the local committee for animal care and use. Experiments were performed in accordance with permit 380 820 from the French Ministry of Agriculture. The 9L gliosarcoma cells were implanted in the brain of eight rats. Fifteen days later, 4.7-T MR examinations were performed to estimate T2*, T2, BVf, and T2*ΔB0corrected in the tumor and contralateral regions. MR estimates of SO2 were derived by combining T2, BVf, and T2*ΔB0corrected according to a recently described quantitative BOLD approach. Scatterplots and linear regression analysis were used to identify correlation between parameters. Paired Student t tests were used to compare the tumor region with the contralateral region.

RESULTS

No significant correlations were found between T2* and any parameter in either tumor tissue or healthy tissue. T2* in the tumor and T2* in the uninvolved contralateral brain were the same (36 msec±4 [standard deviation] vs 36 msec±5, respectively), which might suggest similar oxygenation. Adding T2 information (98 msec±7 vs 68 msec±2, respectively) alone yields results that suggest apparent hypo-oxygenation of the tumor, while incorporating BVf (5.3%±0.6 vs 2.6%±0.3, respectively) alone yields results that suggest apparent hyperoxygenation. MR estimates of SO2 obtained with a complete quantitative BOLD analysis, although not correlated with T2* values, suggest normal oxygenation (68%±3 vs 65%±4, respectively). MR estimates of SO2 obtained in the contralateral tissue agree with previously reported values.

CONCLUSION

Additional measurements, such as BVf, T2, and B0, are needed to obtain reliable information on oxygenation with BOLD MR imaging. The proposed quantitative BOLD approach, which includes these measurements, appears to be a promising tool with which to map tumor oxygenation.

Quantitative functional MRI: concepts, issues and future challenges

Since its inception 20 years ago, functional magnetic resonance imaging (fMRI) of the human brain based on the blood oxygenation level dependent (BOLD) contrast phenomenon has proliferated and matured. Today it is the predominant functional brain imaging modality with the majority of applications being in basic cognitive neuroscience where it has primarily been used as a tool to localize brain activity. While the magnitude of the BOLD response is often used in these studies as a surrogate for the level of neuronal activity, the link between the two is, in fact, quite indirect. The BOLD response is dependent upon hemodynamic (blood flow and volume) and metabolic (oxygen consumption) responses as well as acquisition details. Furthermore, the relationship between neuronal activity and the hemodynamic response, termed neurovascular coupling, is itself complex and incompletely understood. Quantitative fMRI techniques have therefore been developed to measure the hemodynamic and metabolic responses to modulations in brain activity. These methods have not only helped clarify the behaviour and origins of the BOLD signal under normal physiological conditions but they have also provided a potentially valuable set of tools for exploring pathophysiological conditions. Such quantitative methods will be critical to realize the potential of fMRI in a clinical context, where simple BOLD measurements cannot be uniquely interpreted, and to enhance the power of fMRI in basic neuroscience research. In this article, recent advances in human quantitative fMRI methods are reviewed, outstanding issues discussed and future challenges and opportunities highlighted.

Quantitative phenomenological model of the BOLD contrast mechanism

Different theoretical models of the BOLD contrast mechanism are used for many applications including BOLD quantification (qBOLD) and vessel size imaging, both in health and disease. Each model simplifies the system under consideration, making approximations about the structure of the blood vessel network and diffusion of water molecules through inhomogeneities in the magnetic field created by deoxyhemoglobin-containing blood vessels. In this study, Monte-Carlo methods are used to simulate the BOLD MR signal generated by diffusing water molecules in the presence of long, cylindrical blood vessels. Using these simulations we introduce a new, phenomenological model that is far more accurate over a range of blood oxygenation levels and blood vessel radii than existing models. This model could be used to extract physiological parameters of the blood vessel network from experimental data in BOLD-based experiments. We use our model to establish ranges of validity for the existing analytical models of Yablonskiy and Haacke, Kiselev and Posse, Sukstanskii and Yablonskiy (extended to the case of arbitrary time in the spin echo sequence) and Bauer et al. (extended to the case of randomly oriented cylinders). Although these models are shown to be accurate in the limits of diffusion under which they were derived, none of them is accurate for the whole physiological range of blood vessels radii and blood oxygenation levels. We also show the extent of systematic errors that are introduced due to the approximations of these models when used for BOLD signal quantification.