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An analysis of the use of hyperoxia for measuring venous cerebral blood volume: Comparison of the existing method with a new analysis approach
Abstract
Hyperoxia is known to cause an increase in the blood oxygenation level dependent (BOLD) signal that is primarily localised to the venous vasculature. This contrast mechanism has been proposed as a way to measure venous cerebral blood volume (CBVv) without the need for more invasive contrast media. In the existing method the analysis modelled the data as a dynamic contrast agent experiment, with the assumption that the BOLD signal of tissue was dominated by intravascular signal. The effects on the accuracy of the method due to extravascular BOLD signal changes, as well as signal modulation by intersubject differences in baseline physiology, such as haematocrit and oxygen extraction fraction, have so far been unexplored. In this study the effect of extravascular signal and intersubject physiological variability was investigated by simulating the hyperoxia CBVv experiment using a detailed BOLD signal model. This analysis revealed substantial uncertainty in the measurement of CBVv using the existing analysis based on dynamic contrast agent experiments. Instead, the modelling showed a simple and direct relationship between the BOLD signal change and CBVv, and an alternative analysis method with much reduced uncertainty was proposed based on this finding. Both methods were tested experimentally, with the new method producing results that are consistent with the limited literature in this area.
... These markers can provide quantitative profiles that aid in the explanation of differences between vasodilatory response across cortical and sub-cortical tissues (Donahue et al., 2014;Thomas et al., 2014;Champagne et al., 2019) as well as pathological tissues with impaired or temporally altered hemodynamics due to collateralization (Donahue et al., 2016). The general consensus is that temporal characteristics of the vascular response reflect a combination of factors including arterial transit time, blood redistribution, and vascular response speed, which may be partially separated using a combination of hypercapnic (HC) respiratory challenges to stress the cerebral vasculature and hyperoxic (HO) respiratory challenges that have previously been implemented to act as endogenous contrast agents via O2mediated changes in deoxyhemoglobin (Blockley et al., 2013;Champagne et al., 2019). ...
... While HC modulates the BOLD signal via changes in perfusion, the BOLD contrast can also be manipulated when combined with non-vasoactive HO breathing challenges (Blockley et al., 2013). As the arterial partial pressure of oxygen (P a O 2 ) increases, complete hemoglobin saturation at the lungs drives the dissolution of abundant O 2 into the blood plasma. ...
... This O 2 based mechanism has been proposed as a means through which arrival time (Champagne et al., 2019) and cerebral blood volume (CBV) (Lu et al., 2003) can be assessed and assumes limited vasoconstriction and minor reduction in venous CBV (Bulte et al., 2007;Mark and Pike, 2012;Xu et al., 2012). Irrespective of potential vaso-constrictive effects, the bolus of highly saturated blood formed during HO breathing can act as a non-invasive endogenous contrast agent for estimation of bolus arrival time (Blockley et al., 2013;Liu et al., 2017;Champagne et al., 2019) since only minor reductions in blood velocity would be expected. Consequently, HO may be used to calibrate HC-derived CVR delays, and untangle physiological factors that contribute to the (patho)physiological mechanisms associated with diseases causing vascular impairments. ...
Cerebrovascular reactivity (CVR) mapping is finding increasing clinical applications as a non-invasive probe for vascular health. Further analysis extracting temporal delay information from the CVR response provide additional insight that reflect arterial transit time, blood redistribution, and vascular response speed. Untangling these factors can help better understand the (patho)physiology and improve diagnosis/prognosis associated with vascular impairments. Here, we use hypercapnic (HC) and hyperoxic (HO) challenges to gather insight about factors driving temporal delays between gray-matter (GM) and white-matter (WM). Blood Oxygen Level Dependent (BOLD) datasets were acquired at 7T in nine healthy subjects throughout BLOCK- and RAMP-HC paradigms. In a subset of seven participants, a combined HC+HO block, referred as the “BOOST” protocol, was also acquired. Tissue-based differences in Rapid Interpolation at Progressive Time Delays (RIPTiDe) were compared across stimulus to explore dynamic (BLOCK-HC) versus progressive (RAMP-HC) changes in CO2, as well as the effect of bolus arrival time on CVR delays (BLOCK-HC versus BOOST). While GM delays were similar between the BLOCK- (21.80 ± 10.17 s) and RAMP-HC (24.29 ± 14.64 s), longer WM lag times were observed during the RAMP-HC (42.66 ± 17.79 s), compared to the BLOCK-HC (34.15 ± 10.72 s), suggesting that the progressive stimulus may predispose WM vasculature to longer delays due to the smaller arterial content of CO2 delivered to WM tissues, which in turn, decreases intravascular CO2 gradients modulating CO2 diffusion into WM tissues. This was supported by a maintained ∼10 s offset in GM (11.66 ± 9.54 s) versus WM (21.40 ± 11.17 s) BOOST-delays with respect to the BLOCK-HC, suggesting that the vasoactive effect of CO2 remains constant and that shortening of BOOST delays was be driven by blood arrival reflected through the non-vasodilatory HO contrast. These findings support that differences in temporal and magnitude aspects of CVR between vascular networks reflect a component of CO2 sensitivity, in addition to redistribution and steal blood flow effects. Moreover, these results emphasize that the addition of a BOOST paradigm may provide clinical insights into whether vascular diseases causing changes in CVR do so by way of severe blood flow redistribution effects, alterations in vascular properties associated with CO2 diffusion, or changes in blood arrival time.
... 11 The second class of methods for baseline CBV v quantification uses a hyperoxic stimulus that reduces [dHb] v and therefore increases the BOLD signal. 12,13 Using hyperoxic gas mixtures as a contrast agent, Bulte et al derived absolute CBV v by comparing a signal fraction (ie, hyperoxia-induced signal change relative to a normoxic condition) in a large vein with that in brain tissue. 12 More recently, the method's estimation uncertainty due to intersubject variations of hematocrit and oxygen extraction fraction has been substantially reduced using empirical parameters that determine a linear relationship between CBV v and the BOLD signal change. ...
... 12 More recently, the method's estimation uncertainty due to intersubject variations of hematocrit and oxygen extraction fraction has been substantially reduced using empirical parameters that determine a linear relationship between CBV v and the BOLD signal change. 13 Nonetheless, neither of these approaches is able to achieve reliable estimation of CBV v because of inherent limitations. Common to both is the sensitivity to magnetic field variations due to macroscopic field inhomogeneities. ...
... 8 The parameter estimation in the hyperoxia-based method depends highly on the validity of the critical assumption that both cerebral blood flow and cerebral metabolic rate of oxygen (CMRO 2 ) remain unchanged by hyperoxia. 13 In fact, a reduction of cerebral blood flow has been reported under hyperoxic conditions, 14,15 which is likely caused by an accompanying hypocapnic effect, 16 although reports on the direction and magnitude of hyperoxia-induced CMRO 2 alterations substantially differ across studies in the literature. [17][18][19] Furthermore, prerequisites and procedures for gas administration make the method less accessible and attractive. ...
Purpose
Venous cerebral blood volume (CBVv) is a major contributor to BOLD contrast, and therefore is an important parameter for understanding the underlying mechanism. Here, we propose a velocity‐selective venous spin labeling (VS‐VSL)‐prepared 3D turbo spin echo pulse sequence for whole‐brain baseline CBVv mapping.
Methods
Unlike previous CBVv measurement techniques that exploit the interrelationship between BOLD signals and CBVv, in the proposed VS‐VSL technique both arterial blood and cerebrospinal fluid (CSF) signals were suppressed before the VS pulse train for exclusive labeling of venous blood, while a single‐slab 3D turbo spin echo readout was used because of its relative immunity to magnetic field variations. Furthermore, two approximations were made to the VS‐VSL signal model for simplified derivation of CBVv. In vivo studies were performed at 3T field strength in 8 healthy subjects. The performance of the proposed VS‐VSL method in baseline CBVv estimation was first evaluated in comparison to the existing, hyperoxia‐based method. Then, data were also acquired using VS‐VSL under hypercapnic and hyperoxic gas breathing challenges for further validation of the technique.
Results
The proposed technique yielded physiologically plausible baseline CBVv values, and when compared with the hyperoxia‐based method, showed no statistical difference. Furthermore, data acquired using VS‐VSL yielded average CBVv of 2.89%/1.78%, 3.71%/2.29%, and 2.88%/1.76% for baseline, hypercapnia, and hyperoxia, respectively, in gray/white matter regions. As expected, hyperoxia had negligible effect (P > .8), whereas hypercapnia demonstrated vasodilation (P << .01).
Conclusion
Upon further validation of the quantification model, the method is expected to have merit for 3D CBVv measurements across the entire brain.
... Here, we report results using a promising approach for a more definitive test of CBV dHb dynamics based on the effects of hyperoxia ( Blockley et al., 2013Blockley et al., , 2012. This approach exploits the idea that increasing the arterial pO 2 leads to a decrease in the tissue relaxation rate R 2 * -a hyperoxia-BOLD effect-that is proportional to the deoxygenated blood volume. ...
... For each period, the average ΔBOLD h-n was calculated. Based on the modeling of the effects of hyperoxia ( Blockley et al., 2013), for the ideal experiment each of these ΔBOLD h-n values should be proportional to the absolute CBV dHb in that state. In practice, we expect that additional effects of administering hyperoxia may lead to an additional shift of R 2 * (Pilkinton et al., 2011). ...
... We assume that the effect of hyperoxia is to lower the venous dHb concentration by a small amount w ( Blockley et al., 2013), so that C = C 0 -w, with w estimated above to be about 12% of C 0 for these experiments. For the ideal hyperoxia experiment there is no change in blood volume due ...
Cerebral blood flow (CBF) and blood oxygenation level dependent (BOLD) signal measurements make it possible to estimate steady-state changes in the cerebral metabolic rate of oxygen (CMRO2) with a calibrated BOLD method. However, extending this approach to measure the dynamics of CMRO2 requires an additional assumption: that deoxygenated cerebral blood volume (CBVdHb) follows CBF in a predictable way. A test-case for this assumption is the BOLD post-stimulus undershoot, for which one proposed explanation is a strong uncoupling of flow and blood volume with an elevated level of CBVdHb during the post-stimulus period compared to baseline due to slow blood volume recovery (Balloon Model). A challenge in testing this model is that CBVdHb differs from total blood volume, which can be measured with other techniques. In this study, the basic hypothesis of elevated CBVdHb during the undershoot was tested, based on the idea that the BOLD signal change when a subject switches from breathing a normoxic gas to breathing a hyperoxic gas is proportional to the absolute CBVdHb. In 19 subjects (8F), dual-echo BOLD responses were measured in primary visual cortex during a flickering radial checkerboard stimulus in normoxia, and the identical experiment was repeated in hyperoxia (50% O2/balance N2). The BOLD signal differences between normoxia and hyperoxia for the pre-stimulus baseline, stimulus, and post-stimulus periods were compared using an equivalent BOLD signal calculated from measured R2* changes to eliminate signal drifts. Relative to the pre-stimulus baseline, the average BOLD signal change from normoxia to hyperoxia was negative during the undershoot period (p = 0.0251), consistent with a reduction of CBVdHb and contrary to the prediction of the Balloon Model. Based on these results, the BOLD post-stimulus undershoot does not represent a case of strong uncoupling of CBVdHb and CBF, supporting the extension of current calibrated BOLD methods to estimate the dynamics of CMRO2.
... Absolute CBVv can be calculated from the ratio of steady-state tissue signals during the hyperoxia and normoxia periods, normalized by the same ratio from a pure blood voxel (sagittal sinus). Blockley et al. later showed that the normalization step may introduce additional error due to variations of baseline physiological parameters such as hematocrit and OEF (Blockley et al., 2013a). Instead, a quantitative model based on an empirical relationship between CBVv, and the BOLD signal change, PaO2 change and echo time (TE) was proposed, which does not require a normalization step with signals from a pure blood voxel. ...
... First, CBF is assumed to remain constant during hyperoxia in current models. However, the increase in blood O2 levels (Bulte et al., 2007b) and the accompanying decrease in blood CO2 levels (Iscoe and Fisher, 2005) during hyperoxia may cause CBF reduction, which will generally lead to an overestimate of CBVv from the BOLD signal (Blockley et al., 2013a). This confound can be minimized by keeping the duration of gas inhalation relatively short, or by accounting for blood O2 and CO2 changes in the analysis (Liu et al., 2017b;Mark and Pike, 2012;Xu et al., 2012). ...
... However, there are still debates on this question with studies from the literature showing increase (Rockswold et al., 2010), decrease (Richards et al., 2007;Xu et al., 2012), or same (Diringer et al., 2007) CMRO2 during hyperoxia compared to normoxia. An increase in CMRO2 during hyperoxia will result in an overestimate of CBVv with current theories, and vice versa (Blockley et al., 2013a). This issue warrants further investigation, and the CMRO2 response during hyperoxia may alter under different physiological and pathological conditions. ...
The measurement of cerebral blood volume (CBV) has been the topic of numerous neuroimaging studies. To date, however, most in vivo imaging approaches can only measure CBV summed over all types of blood vessels, including arterial, capillary and venous vessels in the microvasculature (i.e. total CBV or CBVtot). As different types of blood vessels have intrinsically different anatomy, function and physiology, the ability to quantify CBV in different segments of the microvascular tree may furnish information that is not obtainable from CBVtot, and may provide a more sensitive and specific measure for the underlying physiology. This review attempts to summarize major efforts in the development of MRI techniques to measure arterial (CBVa) and venous CBV (CBVv) separately. Advantages and disadvantages of each type of method are discussed. Applications of some of the methods in the investigation of flow-volume coupling in healthy brains, and in the detection of pathophysiological abnormalities in brain diseases such as arterial steno-occlusive disease, brain tumors, schizophrenia, Huntington's disease, Alzheimer's disease, and hypertension are demonstrated. We believe that the continual development of MRI approaches for the measurement of compartment-specific CBV will likely provide essential imaging tools for the advancement and refinement of our knowledge on the exquisite details of the microvasculature in healthy and diseased brains.
... However, it is the driving factor for errors in CBV. This result is consistent with the idea that the hyperoxic signal change is predominantly a CBV weighted signal (Blockley et al., 2013), where calibration against ΔP ET O 2 can be used to estimate CBV. Consideration of Fig. 4 demonstrates that, for OEF greater than approximately 0.25, the calibrated hyperoxic signal does indeed correspond closely to the CBV. ...
... Thus, refinement of the method is required to produce reliable voxelwise estimates and the current implementation is likely to be more suited to ROI analysis. However, compared to individual parameter estimation methods (Blockley et al., 2013;Bulte et al., 2012;Jochimsen et al., 2010), the combined estimation approach has the advantage of requiring fewer physiological assumptions. For example, in the estimation of vessel size it has previously been necessary to assume a resting OEF. ...
... Although not implemented here, by restricting the range of possible OEF values, it is apparent that such a calibrated measurement could also be used to produce a simultaneous estimate of CBV (see Fig. 4). This method of CBV determination is similar to that proposed by Blockley et al. (2013), where gradient-echo data was shown to produce CBV estimates for OEF values in the range of 0.35 to 0.55 when calibrated against ΔP ET O 2 . However, because only the GE signal is acquired in the Blockley method, an assumed vessel size is implicitly used (via assuming a fixed contribution of diffusion effects with a β value of 1). ...
Functional magnetic resonance imaging measures signal increases arising from a variety of interrelated effects and physiological sources. Recently there has been some success in disentangling this signal in order to quantify baseline physiological parameters, including the resting oxygen extraction fraction (OEF), cerebral blood volume (CBV) and mean vessel size. However, due to the complicated nature of the signal, each of these methods relies on certain physiological assumptions to derive a solution. In this work we present a framework for the simultaneous, voxelwise measurement of these three parameters. The proposed method removes the assumption of a fixed vessel size from the quantification of OEF and CBV, while simultaneously removing the need for an assumed OEF in the calculation of vessel size. The new framework is explored through simulations and validated with a pilot study in healthy volunteers. The MRI protocol uses a combined hyperoxia and hypercapnia paradigm with a modified spin labelling sequence collecting multi-slice gradient echo and spin echo data.
... [31][32][33][34] To further suppress noise propagation in OEF, we integrate tissue-type information with CAT and apply total variation (TV) regularization in this study. Limited clusters using magnitude signal time evolution in CAT 31 may be improved by additional tissue type information, particularly gray matter (GM) versus white matter (WM), which helps to determine tissue-specific QQ model parameters including venous blood volume 35,36 and R 2 . 17 Furthermore, TV regularization should help alleviate the propagation of measurement noise into the parameter map. ...
... 6 Furthermore, the v from QQ-CCTV falls into previously reported MRI-based v values (e.g., 2.46 ± 0.28%, 42 2.68 ± 0.47%, 69 and 3.6 ± 0.4%). 70 Also, the clear CGM/WM contrast from QQ-CCTV is in line with the v contrast in MRI literature 35,36 and may be caused by tissue-type (GM/WM) integration into clustering, which leads to a more realistic v initialization in optimization. The R 2 in CGM estimated with CAT, CATV, and CCTV (16.2 ± 0.6 Hz, 16.2 ± 0.6 Hz, and 15.8 ± 0.6 Hz) agree with the values from other MR techniques (15.1 ± 0.6 Hz 17 and 17.1 ± 2 Hz). ...
Purpose
To improve the accuracy of quantitative susceptibility mapping plus quantitative blood oxygen level‐dependent magnitude (QSM+qBOLD or QQ) based mapping of oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO2) using temporal clustering, tissue composition, and total variation (CCTV).
Methods
Three‐dimensional multi‐echo gradient echo and arterial spin labeling images were acquired from 11 healthy subjects and 33 ischemic stroke patients. Diffusion‐weighted imaging (DWI) was also obtained from patients. The CCTV mapping was developed for incorporating tissue‐type information into clustering of the previous cluster analysis of time evolution (CAT) and applying total variation (TV). The QQ‐based OEF and CMRO2 were reconstructed with CAT, CAT+TV (CATV), and the proposed CCTV, and results were compared using region‐of‐interest analysis, Kruskal‐Wallis test, and post hoc Wilcoxson rank sum test.
Results
In simulation, CCTV provided more accurate and precise OEF than CAT or CATV. In healthy subjects, QQ‐based OEF was less noisy and more uniform with CCTV than CAT. In subacute stroke patients, OEF with CCTV had a greater contrast‐to‐noise ratio between DWI‐defined lesions and the unaffected contralateral side than with CAT or CATV: 1.9 ± 1.3 versus 1.1 ± 0.7 (P = .01) versus 0.7 ± 0.5 (P < .001).
Conclusion
The CCTV mapping significantly improves the robustness of QQ‐based OEF against noise.
... Calibrated BOLD methods using gas-inhalation assumes that CBF and CMRO 2 remain constant during hyperoxia. 66,67 However, CBF may decrease and/or CMRO 2 may increase during hyperoxia, which leads to an v overestimation. 65,66 The v values from the PET methods are the difference the between the total and arterial blood volume, 61,62 which includes both venous and capillary blood. ...
... 66,67 However, CBF may decrease and/or CMRO 2 may increase during hyperoxia, which leads to an v overestimation. 65,66 The v values from the PET methods are the difference the between the total and arterial blood volume, 61,62 which includes both venous and capillary blood. This may lead to larger v than the one in this study. ...
Purpose
To improve the accuracy of QSM plus quantitative blood oxygen level‐dependent magnitude (QSM + qBOLD or QQ)‐based mapping of the oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO2) using cluster analysis of time evolution (CAT).
Methods
3D multi‐echo gradient echo and arterial spin labeling images were acquired in 11 healthy subjects and 5 ischemic stroke patients. DWI was also carried out on patients. CAT was developed for analyzing signal evolution over TE. QQ‐based OEF and CMRO2 were reconstructed with and without CAT, and results were compared using region of interest analysis and a paired t‐test.
Results
Simulations demonstrated that CAT substantially reduced noise error in QQ‐based OEF. In healthy subjects, QQ‐based OEF appeared less noisy and more uniform with CAT than without CAT; average OEF with and without CAT in cortical gray matter was 32.7 ± 4.0% and 37.9 ± 4.5%, with corresponding CMRO2 of 148.4 ± 23.8 and 171.4 ± 22.4 μmol/100 g/min, respectively. In patients, regions of low OEF were confined within the ischemic lesions defined on DWI when using CAT, which was not observed without CAT.
Conclusion
The cluster analysis of time evolution (CAT) significantly improves the robustness of QQ‐based OEF against noise.
... It should therefore be possible to quantify maps of R₂ 0 in terms of deoxyhaemoglobin content with appropriate scaling. Likewise with improved quantification of DBV, either through improvements to the qBOLD technique or via an additional experimental technique (Blockley et al., 2013;Lee et al., 2018), accurate measurements of OEF are possible. A large amount of uncertainty was observed in the apparent DBV (Fig. 8b). ...
... Likewise Fig. 9 would predict the percentage error in the apparent DBV is 100%, which would reduce the measured value above to 1.8%. This would bring these measurements in line with other MR based measurements of DBV at 1.75% (He and Yablonskiy, 2007) and venous CBV at 2.2% (Blockley et al., 2013). For the alternative ASE pulse sequence parameters Fig. S7 predicts an apparent OEF of 40% for a true OEF value of 40%, which is consistent with experiments (An and Lin, 2003). ...
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.
... (2) and (3) using a linearised relationship between [dHb] and the BOLD signal (β = 1) recently explored by Griffeth et al. (2013). The BOLD response to hypercapnia therefore becomes, As previously shown the hyperoxia BOLD signal is not dependent on the baseline [dHb] level, [dHb] 0 , (Blockley et al., 2013), hence the signal is predicted to only be sensitive to V 0 . By taking the ratio of Eqs. ...
... The predictions of the simple model were investigated using a detailed BOLD signal model, incorporating multiple vascular compartments and a single tissue compartment.Fig. 2 demonstrates the relationship between the hypercapnia and hyperoxia BOLD responses and the deoxyhaemoglobin content and venous CBV, respectively. Consistent with previous work, the hyperoxia BOLD signal was shown to be proportional to venous CBV, as predicted by Eq. (5) (Blockley et al., 2013). Similarly, the hypercapnia BOLD signal response was shown to vary linearly with deoxyhaemoglobin content, as predicted by Eq. (6). ...
Recently a new class of calibrated blood oxygen level dependent (BOLD) functional magnetic resonance imaging (MRI) methods were introduced to quantitatively measure the baseline oxygen extraction fraction (OEF). These methods rely on two respiratory challenges and a mathematical model of the resultant changes in the BOLD functional MRI signal to estimate the OEF. However, this mathematical model does not include all of the effects that contribute to the BOLD signal, it relies on several physiological assumptions and it may be affected by intersubject physiological variability. The aim of this study was to investigate these sources of systematic error and their effect on estimating the OEF. This was achieved through simulation using a detailed model of the BOLD signal. Large ranges for intersubject variability in baseline physiological parameters such as haematocrit and cerebral blood volume were considered. Despite this the uncertainty in the relationship between the measured BOLD signals and the OEF was relatively low. Investigations of the physiological assumptions that underlie the mathematical model revealed that OEF measurements are likely to be overestimated if oxygen metabolism changes during hypercapnia or cerebral blood flow changes under hyperoxia. Hypoxic hypoxia was predicted to result in an underestimation of the OEF, whilst anaemic hypoxia was found to have only a minimal effect.
Copyright © 2015. Published by Elsevier Inc.
... Our choice of prior means for OEF = 40% and DBV = 2.5% was supported from previous literature that found an OEF of 41 ± 9% using Oxygen PET [Derdeyn et al., 2001] and 38.3 ± 5.3 using qBOLD [He and Yablonskiy, 2007]. DBV was estimated at 1.75 ± 0.13% using qBOLD [He and Yablonskiy, 2007], 2.18 ± 0.41 in [Blockley et al., 2013], and was estimated at 3.1 ± 0.5% using interleaved qBOLD [Lee et al., 2018]. We experimented with the standard deviations for these and found that OEF ∼ T N (40%, 20% 2 ) and DBV ∼ T N (2.5%, 2% 2 ), provides a good compromise in terms of ELBO and tightness of the distribution, where T N refers to a truncated Normal distribution to avoid values outside [0%, 100%]. ...
Streamlined qBOLD acquisitions enable experimentally straightforward observations of brain oxygen metabolism. $R_2^\prime$ maps are easily inferred; however, the Oxygen extraction fraction (OEF) and deoxygenated blood volume (DBV) are more ambiguously determined from the data. As such, existing inference methods tend to yield very noisy and underestimated OEF maps, while overestimating DBV. This work describes a novel probabilistic machine learning approach that can infer plausible distributions of OEF and DBV. Initially, we create a model that produces informative voxelwise prior distribution based on synthetic training data. Contrary to prior work, we model the joint distribution of OEF and DBV through a scaled multivariate logit-Normal distribution, which enables the values to be constrained within a plausible range. The prior distribution model is used to train an efficient amortized variational Bayesian inference model. This model learns to infer OEF and DBV by predicting real image data, with few training data required, using the signal equations as a forward model. We demonstrate that our approach enables the inference of smooth OEF and DBV maps, with a physiologically plausible distribution that can be adapted through specification of an informative prior distribution. Other benefits include model comparison (via the evidence lower bound) and uncertainty quantification for identifying image artefacts. Results are demonstrated on a small study comparing subjects undergoing hyperventilation and at rest. We illustrate that the proposed approach allows measurement of gray matter differences in OEF and DBV and enables voxelwise comparison between conditions, where we observe significant increases in OEF and $R_2^\prime$ during hyperventilation.
... In our study, venous CBV was assumed to be 50% of the total CBV based on literature that the total CBV in GM was reported to be 4%-5%, 70,71 whereas CBV v was measured to be 2%-3%. [72][73][74] However, there are studies reporting proportions of CBV v to range from 50% to 80% of the total CBV. [75][76][77][78][79] Rerunning the analysis reveals that differing CBV v /total CBV from 50% to 80% only results in about 0.4% GM OEF difference for HO QSM-OEF and 1% difference in HC QSM-OEF results. ...
Purpose
To use hyperoxia in combination with QSM to quantify microvascular oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO2) in healthy subjects and to cross‐validate results with those from hypercapnia QSM‐OEF.
Methods
Ten healthy subjects were scanned on a 3T MRI scanner. At baseline normoxia and during hyperoxia (PetO2 = +300 mmHg), QSM data were acquired using a multi‐echo gradient‐echo (GRE) sequence, and cerebral blood flow data were acquired using a pseudocontinuous arterial spin labeling sequence. The OEF and CMRO2 maps were computed and compared with those from hypercapnia QSM‐OEF, acquired in the same subjects, using correlation and Bland‐Altman analysis in 16 vascular territories.
Results
Hyperoxia QSM‐OEF produced physiologically reasonable OEF and CMRO2 values in all subjects (gray‐matter region of interest average OEF = 0.42 ± 0.04, average CMRO2 = 181 ± 34 μmol O2/min/100 g). When compared with hypercapnia QSM‐OEF, Bland‐Altman plots revealed small deviations (mean OEF difference = 0.015, mean CMRO2 difference = 4.9 μmol O2/min/100 g, P < .05). Good and excellent correlations of regional OEF and CMRO2 were found for the two methods. In addition, hyperoxia had minimal impact on cerebral blood flow (average gray‐matter cerebral blood flow was reduced by 7.5 ± 5.4%).
Conclusions
Hyperoxia in combination with QSM is a robust approach to measure OEF. Compared with hypercapnia, hyperoxia is more comfortable and has minimal impact on cerebral blood flow.
... Adding the BOLD data back in but with only an O 2 stimulus does little to improve the performance of the network (R 2 = 0.63). This is not unexpected as the hyperoxic BOLD signal is largely related to venous blood volume (Blockley et al., 2013) with little influence from OEF. Perhaps unexpectedly, including the CO 2 stimulus but not the O 2 stimulus significantly improves the ability of the network to infer resting CMRO 2 (R 2 = 0.71). ...
Magnetic resonance imaging (MRI) offers the possibility to non-invasively map the brain's metabolic oxygen consumption (CMRO2), which is essential for understanding and monitoring neural function in both health and disease. However, in depth study of oxygen metabolism with MRI has so far been hindered by the lack of robust methods. One MRI method of mapping CMRO2 is based on the simultaneous acquisition of cerebral blood flow (CBF) and blood oxygen level dependent (BOLD) weighted images during respiratory modulation of both oxygen and carbon dioxide. Although this dual-calibrated methodology has shown promise in the research setting, current analysis methods are unstable in the presence of noise and/or are computationally demanding. In this paper, we present a machine learning implementation for the multi-parametric assessment of dual-calibrated fMRI data. The proposed method aims to address the issues of stability, accuracy, and computational overhead, removing significant barriers to the investigation of oxygen metabolism with MRI. The method utilizes a time-frequency transformation of the acquired perfusion and BOLD-weighted data, from which appropriate feature vectors are selected for training of machine learning regressors. The implemented machine learning methods are chosen for their robustness to noise and their ability to map complex non-linear relationships (such as those that exist between BOLD signal weighting and blood oxygenation). An extremely randomized trees (ET) regressor is used to estimate resting blood flow and a multi-layer perceptron (MLP) is used to estimate CMRO2 and the oxygen extraction fraction (OEF). Synthetic data with additive noise are used to train the regressors, with data simulated to cover a wide range of physiologically plausible parameters. The performance of the implemented analysis method is compared to published methods both in simulation and with in-vivo data (n = 30). The proposed method is demonstrated to significantly reduce computation time, error, and proportional bias in both CMRO2 and OEF estimates. The introduction of the proposed analysis pipeline has the potential to not only increase the detectability of metabolic difference between groups of subjects, but may also allow for single subject examinations within a clinical context.
... It would also be possible to use values from other imaging modalities to define prior means. For example, a hyperoxia experiment could be used to estimate venous cerebral blood volume in grey matter (Blockley et al., 2013), which could be used to inform the prior on DBV. It was, however, shown that significantly changing the prior means does not have a detrimental effect on the accuracy of parameter estimation. ...
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.
... Adding the BOLD data back in but with only an O 2 stimulus does 200 little to improve the performance of the network (R 2 = 0.63). This is not unexpected as the hyperoxic 201 BOLD signal is largely related to venous blood volume(Blockley et al., 2013) with little influence 202 from OEF. Perhaps unexpectedly, including the CO 2 stimulus but not the O 2 stimulus significantly 203 ...
Magnetic resonance imaging (MRI) offers the ability to non-invasively map the brain's metabolic oxygen consumption (CMRO 2 ), which is essential for understanding and monitoring neural function in both health and disease. One MRI method of mapping CMRO 2 is based on the simultaneous acquisition of cerebral blood flow (CBF) and blood oxygen level dependent (BOLD) weighted images during respiratory modulation of both oxygen and carbon dioxide. Although this dual-calibrated methodology has shown promise in the research setting, current analysis methods are unstable in the presence of noise and/or are computationally demanding. In this paper, we present a machine learning implementation for the multi-parametric assessment of dual-calibrated fMRI data. An extremely randomized trees regressor and a multi-layer perceptron (MLP) are cascaded to provide quantitative estimates of the resting CBF, CMRO 2 , and oxygen extraction fraction (OEF). The proposed implementation takes advantage of the inherent noise immunity of tree-based ensemble methods and MLPs to provide robust and computationally efficient estimates of CBF, CMRO 2 , and OEF. Synthetic data with additive noise are used to train the regressors, and their performance is compared to conventional analysis methods both in simulation and with in-vivo data (n=30). The proposed method is demonstrated to significantly reduce computation time, error, and proportional bias in both CMRO 2 and OEF estimates.
... This causes a BOLD signal effect similar to that described above for CO 2. However, oxygen143 mediated BOLD responses are considered to be uncoupled from CVR, assuming limited 144 vasoconstriction ( Mark and Pike, 2012) and a minor reduction in CBF, and thus, CBV V (D. P. 145 Xu et al., 2012). Using this model, hyperoxic changes in BOLD signal can be 146 used to reflect the arrival of blood containing increased O 2 dissolved in plasma, making O 2-rich 147 plasma an endogenous contrast agent for estimation of baseline CBV V ( Blockley et al., 2013;Liu 148 et al., 2017). 149 M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT 8 overlooks the possibility that intrinsic blood flow redistribution, the speed of the vascular 152 response to hypercapnia, and response lag related to blood-arrival time are convolved to 153 determine the temporal BOLD-CVR response. ...
Redistribution of blood flow across different brain regions, arising from the vasoactive nature of hypercapnia, can introduce errors when examining cerebrovascular reactivity (CVR) response delays. In this study, we propose a novel analysis method to characterize hemodynamic delays in the blood oxygen level dependent (BOLD) response to hypercapnia, and hyperoxia, as a way to provide insight into transient differences in vascular reactivity between cortical regions, and across tissue depths. A pseudo-continuous arterial spin labeling sequence was used to acquire BOLD and cerebral blood flow simultaneously in 19 healthy adults (12 F; 20 ± 2 years) during boxcar CO2 and O2 gas inhalation paradigms. Despite showing distinct differences in hypercapnia-induced response delay times (P < 0.05; Bonferroni corrected), grey matter regions showed homogenous hemodynamic latencies (P > 0.05) once calibrated for bolus arrival time derived using non-vasoactive hyperoxic gas challenges. Longer hypercapnic temporal delays were observed as the depth of the white matter tissue increased, although no significant differences in response lag were found during hyperoxia across tissue depth, or between grey and white matter. Furthermore, calibration of hypercapnic delays using hyperoxia revealed that deeper white matter layers may be more prone to dynamic redistribution of blood flow, which introduces response lag times ranging between 1 and 3 s in healthy subjects. These findings suggest that the combination of hypercapnic and hyperoxic gas-inhalation MRI can be used to distinguish between differences in CVR that arise as a result of delayed stimulus arrival time (due to the local architecture of the cerebrovasculature), or preferential blood flow distribution. Calibrated response delays to hypercapnia provide important insights into cerebrovascular physiology, and may be used to correct response delays associated with vascular impairment.
... Measuring CBV with MRI without the use of contrast agents is not trivial and there is no gold-standard approach. BOLD fMRI methods exist, but are intrinsically more weighted towards the venous (deoxygenated) blood volume compartment (Blockley et al., 2013). ASL is a well-established MRI method that utilises arterial blood water as an endogenous tracer for non-invasive quantification of CBF, but which can also be used to obtain a measure of arterial CBV (CBV a ) by waiting only a short time after tagging to acquire an image (Brookes et al., 2007, Francis et al., 2008, Petersen et al., 2006, Warnert et al., 2015b. ...
Cerebral Autoregulation (CA), defined as the ability of the cerebral vasculature to maintain stable levels of blood flow despite changes in systemic blood pressure, is a critical factor in neurophysiological health. Magnetic resonance imaging (MRI) is a powerful technique for investigating cerebrovascular function, offering high spatial resolution and wide fields of view (FOV), yet it is relatively underutilized as a tool for assessment of CA. The aim of this study was to demonstrate the potential of using MRI to measure changes in cerebrovascular resistance in response to lower body negative pressure (LBNP). A Pulsed Arterial Spin Labeling (PASL) approach with short inversion times (TI) was used to estimate cerebral arterial blood volume (CBVa) in eight healthy subjects at baseline and −40mmHg LBNP. We estimated group mean CBVa values of 3.13±1.00 and 2.70±0.38 for baseline and lbnp respectively, which were the result of a differential change in CBVa during −40 mmHg LBNP that was dependent on baseline CBVa. These data suggest that the PASL CBVa estimates are sensitive to the complex cerebrovascular response that occurs during the moderate orthostatic challenge delivered by LBNP, which we speculatively propose may involve differential changes in vascular tone within different segments of the arterial vasculature. These novel data provide invaluable insight into the mechanisms that regulate perfusion of the brain, and establishes the use of MRI as a tool for studying CA in more detail.
... However, DBV in the qBOLD model refers specifically to the deoxygenated blood volume, a subset of the total blood volume, which is difficult to directly localise and measure, and is largely situated on the venous side of the vasculature. Attempts have been made to measure DBV using hyperoxic contrast (Blockley et al., 2013a;Bulte et al., 2007), but these approaches haven't been combined with qBOLD so far. However, combining estimates of R 2 ′ made in this study (2.6 s -1 ) with estimates of DBV made using hyperoxic contrast (2.2 % (Blockley et al., 2013b)) produces an OEF estimate of 33 % in cortical grey matter, suggesting this could be a promising approach. ...
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.
... Short-duration O 2 inhalation does not cause vasodilation or vasoconstriction (Mark and Pike, 2012;Xu et al., 2012), but it can serve as an intravascular contrast agent and alters BOLD MRI signal via its effect on the concentration of deoxyhemoglobin. Thus, MRI signal changes associated with O 2 inhalation provides an estimation of baseline venous cerebral blood volume (vCBV) (Blockley et al., 2013;Bulte et al., 2007). In our technique, the timing of CO 2 and O 2 modulation was designed such that their contributions to BOLD signal could be separately assessed. ...
Diagnosis and treatment monitoring of cerebrovascular diseases routinely require hemodynamic imaging of the brain. Current methods either only provide part of the desired information or require the injection of multiple exogenous agents. In this study, we developed a multiparametric imaging scheme for the imaging of brain hemodynamics and function using gas-inhalation MRI. The proposed technique uses a single MRI scan to provide simultaneous measurements of baseline venous cerebral blood volume (vCBV), cerebrovascular reactivity (CVR), bolus arrival time (BAT), and resting-state functional connectivity (fcMRI). This was achieved with a novel, concomitant O2 and CO2 gas inhalation paradigm, rapid MRI image acquisition with a 9.3 min BOLD sequence, and an advanced algorithm to extract multiple hemodynamic information from the same dataset. In healthy subjects, CVR and vCBV values were 0.23±0.03%/mmHg and 0.0056±0.0006%/mmHg, respectively, with a strong correlation (r=0.96 for CVR and r=0.91 for vCBV) with more conventional, separate acquisitions that take twice the scan time. In patients with Moyamoya syndrome, CVR in the stenosis-affected flow territories (typically anterior-cerebral-artery, ACA, and middle-cerebral-artery, MCA, territories) was significantly lower than that in posterior-cerebral-artery (PCA), which typically has minimal stenosis, flow territories (0.12±0.06%/mmHg vs. 0.21±0.05%/mmHg, p<0.001). BAT of the gas bolus was significantly longer (p=0.008) in ACA/MCA territories, compared to PCA, and the maps were consistent with the conventional contrast-enhanced CT perfusion method. FcMRI networks were robustly identified from the gas-inhalation MRI data after factoring out the influence of CO2 and O2 on the signal time course. The spatial correspondence between the gas-data-derived fcMRI maps and those using a separate, conventional fcMRI scan was excellent, showing a spatial correlation of 0.58±0.17 and 0.64±0.20 for default mode network and primary visual network, respectively. These findings suggest that advanced gas-inhalation MRI provides reliable measurements of multiple hemodynamic parameters within a clinically acceptable imaging time and is suitable for patient examinations.
... The present study also employed O 2 inhalation to provide an estimate of venous CBV. 45,48 CBV can be measured with gadolinium contrast agents. The O 2 method provides an alternative approach which may be useful for patients who cannot undergo the traditional gadolinium scan because of potential allergic reaction, nephrogenic systemic fibrosis or concerns with regard to the long-term deposition of the contrast agent. ...
Hemodynamic mapping using gas inhalation has received increasing interest in recent years. Cerebrovascular reactivity (CVR), which reflects the ability of the brain vasculature to dilate in response to a vasoactive stimulus, can be measured by CO2 inhalation with continuous acquisition of blood oxygen level-dependent (BOLD) magnetic resonance images. Cerebral blood volume (CBV) can be measured by O2 inhalation. These hemodynamic mapping methods are appealing because of their absence of gadolinium contrast agent, their ability to assess both baseline perfusion and vascular reserve, and their utility in calibrating the functional magnetic resonance imaging (fMRI) signal. However, like other functional and physiological indices, a major drawback of these measurements is their poor sensitivity and reliability. Simultaneous multi-slice echo planar imaging (SMS EPI) is a fast imaging technology that allows the excitation and acquisition of multiple two-dimensional slices simultaneously, and has been shown to enhance the sensitivity of several MRI applications. To our knowledge, the benefit of SMS in gas inhalation imaging has not been investigated. In this work, we compared the sensitivity of CO2 and O2 inhalation data collected using SMS factor 2 (SMS2) and SMS factor 3 (SMS3) with those collected using conventional EPI (SMS1). We showed that the sensitivity of SMS scans was significantly (p = 0.01) higher than that of conventional EPI, although no difference was found between SMS2 and SMS3 (p = 0.3). On a voxel-wise level, approximately 20-30% of voxels in the brain showed a significant enhancement in sensitivity when using SMS compared with conventional EPI, with other voxels showing an increase, but not reaching statistical significance. When using SMS, the scan duration can be reduced by half, whilst maintaining the sensitivity of conventional EPI. The availability of a sensitive acquisition technique can further enhance the potential of gas inhalation MRI in clinical applications.
... The in--vivo estimates of venous CBV in this work have a group mean grey matter value of 2.25 ± 0.36 % and show the expected variation with grey matter content. These results are comparable to those reported in (Blockley et al., 2013) 2.18 %, (An and Lin, 2002) 2.46 % and (He and Yablonskiy, 2007) 1.75 %. ...
The measurement of the absolute rate of cerebral metabolic oxygen consumption (CMRO2) 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 CMRO2 non-invasively. One potential MRI method for the measurement of CMRO2 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 (CMRO2), due to the propagation of errors along the analysis pipeline. Here we present a forward modeling 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 modeling 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 CMRO2 measurements made with calibrated BOLD.
... It is important to keep in mind that the BOLD signal is only an indirect indicator of hemodynamic events in the brain and that the relationship of the BOLD signal to neuronal activity remains unsettled. 19 Recent studies show that variables affecting cerebral blood flow, such as respiration rate, caffeine, and psychotropic drugs, [20][21][22] require close attention in comparisons of BOLD signal activations between subjects with neuropsychiatric disorders and healthy control subjects. ...
Major depressive disorder continues to challenge medical and psychological resources worldwide. A marked surge has occurred recently in China in neuroimaging studies of major depressive disorder. Those studies represent an emerging trend in neuropsychiatry in that such research has previously been extremely rare in China. The present article provides a systematic review of reports published in English by research institutes in China on resting-state functional connectivity studied by MRI in depressed subjects and healthy control subjects. Particular attention is given to whether the information may advance effective diagnosis and treatment options for patients with major depressive disorder.
... Then the assumed value of OEF in the analysis of the hyperoxia data is adjusted until the M-values agree. Another recent work from Blockley et al [227] suggests another way of looking at this basic approach, based on the idea that the primary physiological sensitivity of the hyperoxia experiment is really to venous blood volume, rather than M itself. Then the value of M derived from the hypercapnia experiment depends on both baseline venous CBV and baseline OEF, while the hyperoxia experiment primarily provides a measure of venous CBV, and so the two together provide the information needed to estimate baseline OEF. ...
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.
... However, Bulte et al. (2012) estimate that likely modulations in CMRO 2 , should they exist, have a minor effect on the estimated OEF. Unlike Bulte et al. (2012) we have not used the hyperoxia related signal changes to estimate CBV, those calculations relying on an intravascular tracer (Bulte et al., 2007a) whereas most of the BOLD contrast arising in hyperoxia at 3T is extravascular (Lu and Van Zijl, 2005;Blockley et al., 2013). A further subtle effect of hyperoxia is a reduction in CBF through a combination of vasoconstriction and lowering of arterial carbon dioxide tension (Floyd et al., 2003). ...
Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (FMRI) is most commonly used in a semi-quantitative manner to infer changes in brain activity. Despite the basis of the image contrast lying in the cerebral venous blood oxygenation level, quantification of absolute cerebral metabolic rate of oxygen consumption (CMRO2) has only recently been demonstrated. Here we examine two approaches to the calibration of FMRI signal to measure absolute CMRO2 using hypercapnic and hyperoxic respiratory challenges. The first approach is to apply hypercapnia and hyperoxia separately but interleaved in time and the second is a combined approach in which we apply hyperoxic challenges simultaneously with different levels of hypercapnia. Eleven healthy volunteers were studied at 3T using a dual gradient-echo spiral readout pulsed arterial spin labelling (ASL) imaging sequence. Respiratory challenges were conducted using an automated system of dynamic end-tidal forcing. A generalised BOLD signal model was applied, within a Bayesian estimation framework, that aims to explain the effects of modulation of CBF and arterial oxygen content to estimate venous deoxyhaemoglobin concentration ([dHb]0). Using CBF measurements combined with the estimated oxygen extraction fraction (OEF), absolute CMRO2 was calculated. The interleaved approach to hypercapnia and hyperoxia, as well as yielding estimates of CMRO2 and OEF demonstrated a significant increase in regional CBF, venous oxygen saturation (SvO2) (a decrease in OEF) and absolute CMRO2 in visual cortex in response to a continuous (20minute) visual task, demonstrating the potential for the method in measuring long term changes in CMRO2. The combined approach to oxygen and carbon dioxide modulation, as well as taking less time to acquire data, yielded whole brain grey matter estimates of CMRO2 and OEF of 184±45μmol/100g/min and 0.42±0.12 respectively, along with additional estimates of the vascular parameters α = 0.33±0.06, the exponent relating relative increases in CBF to CBV, and β = 1.35±0.13, the exponent relating deoxyhaemoglobin concentration to the relaxation rate R2*. Maps of cerebrovascular and cerebral metabolic parameters were also calculated. We show that combined modulation of oxygen and carbon dioxide can offer an experimentally more efficient approach to estimating OEF and absolute CMRO2 along with the additional vascular parameters that form an important part of the commonly used calibrated FMRI signal model.
Cerebrovascular reactivity (CVR) is a prognostic indicator of cerebrovascular health. Estimating CVR from endogenous end-tidal carbon dioxide (CO2) fluctuation and MRI signal recorded under resting state can be difficult due to the poor signal-to-noise ratio (SNR) of signals. Thus, we aimed to improve the method of estimating CVR from end-tidal CO2 and MRI signals. We proposed a coherence weighted general linear model (CW-GLM) to estimate CVR from the Fourier coefficients weighted by the signal coherence in frequency domain, which confers two advantages. First, it requires no signal alignment in time domain, which simplifies experimental methods. Second, it limits the GLM analysis within the frequency band where CO2 and MRI signals are highly correlated, which automatically suppresses noise and nuisance signals. We compared the performance of our method with time-domain GLM (TD-GLM) and frequency-domain GLM (FD-GLM) in both synthetic and in-vivo data; wherein we calculated CVR from signals recorded under both resting state and sinusoidal stimulus. In synthetic data, CW-GLM has a remarkable performance on CVR estimation from narrow band signals with a mean-absolute error of 0.7 % (gray matter) and 1.2 % (white matter), which was lower than all the other methods. Meanwhile, CW-GLM maintains a comparable performance on CVR estimation from resting signals, with a mean-absolute error of 4.1 % (gray matter) and 8 % (white matter). The superior performance was maintained across the 36 in-vivo measurements, with CW-GLM exhibiting limits of agreement of −16.7 % – 9.5 % between CVR calculated from the resting and sinusoidal CO2 paradigms which was 12 % – 209 % better than current time-domain methods. Evaluating of the cross-coherence spectrum revealed highest signal coherence within the frequency band from 0.01 Hz to 0.05 Hz, which overlaps with previously recommended frequency band (0.02 Hz to 0.04 Hz) for CVR analysis. Our data demonstrates that CW-GLM can work as a self-adaptive band-pass filter to improve CVR robustness, while also avoiding the need for signal temporal alignment.
Non-invasive mapping of cerebral perfusion is critical for understanding neurovascular and neurodegenerative diseases. However, perfusion MRI methods cannot be easily implemented for whole-brain studies in mice because of their small size. To overcome this issue, a transient hypoxia stimulus was applied to induce a bolus of deoxyhemoglobins as an endogenous paramagnetic contrast in blood oxygenation level-dependent (BOLD) MRI. Based on stimulus-duration-dependent studies, 5 s anoxic stimulus was chosen, which induced a decrease in arterial oxygenation to 59%. Dynamic susceptibility changes were acquired with whole-brain BOLD MRI using both all-vessel-sensitive gradient-echo and microvascular-sensitive spin-echo readouts. Cerebral blood flow (CBF) and cerebral blood volume (CBV) were quantified by modeling BOLD dynamics using a partial-volume-corrected arterial input function. In the mouse under ketamine/xylazine anesthesia, total CBF and CBV were 112.0 ± 15.0 ml/100 g/min and 3.39 ± 0.59 ml/100 g (n = 15 mice), respectively, whereas microvascular CBF and CBV were 85.8 ± 6.9 ml/100 g/min and 2.23 ± 0.27 ml/100 g (n = 7 mice), respectively. Regional total vs. microvascular perfusion metrics were highly correlated but a slight mismatch was observed in the large-vessel areas and cortical depth profiles. Overall, this non-invasive, repeatable, simple hypoxia BOLD-MRI approach is viable for perfusion mapping of rodents.
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 ¹⁵O 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.
One promising approach for mapping CMRO2 is dual-calibrated functional MRI (dc-fMRI). This method exploits the Fick Principle to combine estimates of CBF from ASL, and OEF derived from BOLD-ASL measurements during arterial O2 and CO2 modulations. Multiple gas modulations are required to decouple OEF and deoxyhemoglobin-sensitive blood volume. We propose an alternative single gas calibrated fMRI framework, integrating a model of oxygen transport, that links blood volume and CBF to OEF and creates a mapping between the maximum BOLD signal, CBF and OEF (and CMRO2). Simulations demonstrated the method's viability within physiological ranges of mitochondrial oxygen pressure, PmO2, and mean capillary transit time. A dc-fMRI experiment, performed on 20 healthy subjects using O2 and CO2 challenges, was used to validate the approach. The validation conveyed expected estimates of model parameters (e.g., low PmO2), with spatially uniform OEF maps (grey matter, GM, OEF spatial standard deviation ≈ 0.13). GM OEF estimates obtained with hypercapnia calibrated fMRI correlated with dc-fMRI (r = 0.65, p = 2·10-3). For 12 subjects, OEF measured with dc-fMRI and the single gas calibration method were correlated with whole-brain OEF derived from phase measures in the superior sagittal sinus (r = 0.58, p = 0.048; r = 0.64, p = 0.025 respectively). Simplified calibrated fMRI using hypercapnia holds promise for clinical application.
Purpose
To demonstrate the feasibility of mapping cerebral perfusion metrics with BOLD MRI during modulation of pulmonary venous oxygen saturation.
Methods
A gas blender with a sequential gas delivery breathing circuit was used to implement rapid isocapnic changes in the partial pressure of oxygen of the arterial blood. Partial pressure of oxygen was initially lowered to a baseline of 40 mmHg. It was then rapidly raised to 95 mmHg for 20 s before rapidly returning to baseline. The induced cerebral changes in deoxyhemoglobin concentration were tracked over time using BOLD MRI in 6 healthy subjects and 1 patient with cerebral steno‐occlusive disease. BOLD signal change, contrast‐to‐noise ratio, and time delay metrics were calculated. Perfusion metrics such as mean transit time, relative cerebral blood volume, and relative cerebral blood flow were calculated using a parametrized method with a mono‐exponential residue function. An arterial input function from within the middle cerebral artery was used to scale relative cerebral blood volume and calculate absolute cerebral blood volume and cerebral blood flow.
Results
In normal subjects, average gray and white matter were: BOLD change = 6.3 ± 1.2% and 2.5 ± 0.6%, contrast‐to‐noise ratio = 4.3 ± 1.3 and 2.6 ± 0.7, time delay = 2.3 ± 0.6 s and 3.6 ± 0.7 s, mean transit time = 3.9 ± 0.6 s and 5.5 ± 0.6 s, relative cerebral blood volume = 3.7 ± 0.9 and 1.6 ± 0.4, relative cerebral blood flow = 70.1 ± 8.3 and 20.6 ± 4.0, cerebral blood flow volume = 4.1 ± 0.9 mL/100 g and 1.8 ± 0.5 mL/100 g, and cerebral blood flow = 97.2 ± 18.7 mL/100 g/min and 28.7 ± 5.9 mL/100 g/min.
Conclusion
This study demonstrates that induced abrupt changes in deoxyhemoglobin can function as a noninvasive vascular contrast agent that may be used for cerebral perfusion imaging.
Magnetic resonance imaging (MRI) offers the possibility to non-invasively map the rate of cerebral metabolic oxygen consumption (CMRO 2 ), which is essential for understanding and monitoring neural function in both health and disease. Existing methods of mapping CMRO 2 , based on respiratory modulation of arterial spin labelling (ASL) and blood oxygen level dependent (BOLD) signals, require lengthy acquisitions and independent modulation of both arterial oxygen and carbon dioxide levels. Here, we present a new simplified method for mapping the rate of cerebral oxygen metabolism that can be performed using a simple breath-holding paradigm. The method incorporates flow-diffusion modelling of oxygen transport and physiological constraints to create a non-linear mapping between the maximum BOLD signal, M, baseline blood flow (CBF0), and CMRO 2 . A gradient boosted decision tree is used to learn this mapping directly from simulated MRI data. Modelling studies demonstrate that the proposed method is robust to variation in cerebral physiology and metabolism. This new gas-free methodology offers a rapid and pragmatic alternative to existing dual-calibrated methods, removing the need for specialist respiratory equipment and long acquisition times. In-vivo testing of the method, using an 8-minute 45 second protocol of repeated breath-holding, was performed on 15 healthy volunteers, producing quantitative maps of cerebral blood flow (CBF), oxygen extraction fraction (OEF), and CMRO 2 .
Objective: Identify alterations in cerebrovascular reactivity (CVR) based on the history of sport-related concussion (SRC). Further explore possible mechanisms underlying differences in vascular physiology using hemodynamic parameters modeled using calibrated magnetic resonance imaging (MRI).
Method: End-tidal targeting and dual-echo MRI were combined to probe hypercapnic and hyperoxic challenges in athletes with (n = 32) and without (n = 31) a history of SRC. Concurrent blood oxygenation level dependent (BOLD) and arterial spin labeling (ASL) data were used to compute BOLD-CVR, ASL-CVR, and other physiological parameters including resting oxygen extraction fraction (OEF0) and cerebral blood volume (CBV0). Multiple linear and logistic regressions were then used to identify dominant parameters driving group-differences in BOLD-CVR.
Results: Robust evidence for elevated BOLD-CVR were found in athletes with SRC history spreading over parts of the cortical hemispheres. Follow-up analyses showed co-localized differences in ASL-CVR (representing modulation of cerebral blood flow) and hemodynamic factors representing static vascular (i.e., CBV0) and metabolic (i.e., OEF0) effects suggesting that group-based differences in BOLD-CVR may be driven by a mixed effect from factors with vascular and metabolic origins.
Conclusion: These results emphasize that while BOLD-CVR offers promises as a surrogate non-specific biomarker for cerebrovascular health following SRC, multiple hemodynamic parameters can affect its relative measurements.
Abbreviations: [dHb]: concentration of deoxyhemoglobin; AFNI: Analysis of Functional NeuroImages (https://afni.nimh.nih.gov); ASL: arterial spin labeling; BIG: position group: defensive and offensive linemen; BIG-SKILL: position group: full backs, linebackers, running backs, tight-ends; BOLD: blood oxygen level dependent; CBF: cerebral blood flow; CMRO2: cerebral metabolic rate of oxygen consumption; CTL: group of control subjects; CVR: cerebrovascular reactivity; fMRI: functional magnetic resonance imaging; FSL: FMRIB software library (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/); HC: hypercapnia; HO: hyperoxia; HX: group with history of concussion; M: maximal theoretical BOLD signal upon complete removal of venous dHb; pCASL: pseudo-continuous arterial spin labeling; PETCO2: end-tidal carbon dioxide; PETO2: end-tidal oxygen; SCAT: sport-concussion assessment tool; SKILL: position group: defensive backs, kickers, quarterbacks, safeties, wide-receivers; SRC: sport-related concussion.
A new method is proposed for obtaining cerebral perfusion measurements whereby blood oxygen level dependent (BOLD) MRI is used to dynamically monitor hyperoxia-induced changes in the concentration of deoxygenated hemoglobin in the cerebral vasculature. The data is processed using kinetic modeling to yield perfusion metrics, namely: cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT). Ten healthy human subjects were continuously imaged with BOLD sequence while a hyperoxic (70% O2) state was interspersed with baseline periods of normoxia. The BOLD time courses were fit with exponential uptake and decay curves and a biophysical model of the BOLD signal was used to estimate oxygen concentration functions. The arterial input function was derived from end-tidal oxygen measurements, and a deconvolution operation between the tissue and arterial concentration functions was used to yield CBF. The venous component of the CBV was calculated from the ratio of the integrals of the estimated tissue and arterial concentration functions. Mean gray and white matter measurements were found to be: 61.6 ± 13.7 and 24.9 ± 4.0 ml 100 g-1 min-1 for CBF; 1.83 ± 0.32 and 1.10 ± 0.19 ml 100 g-1 for venous CBV; and 2.94 ± 0.52 and 3.73 ± 0.60 s for MTT, respectively. We conclude that it is possible to derive CBF, CBV and MTT metrics within expected physiological ranges via analysis of dynamic BOLD fMRI acquired during a period of hyperoxia.
Quantitative BOLD (qBOLD), a non-invasive MRI method for assessment of hemodynamic and metabolic properties of the brain in the baseline state, provides spatial maps of deoxygenated blood volume fraction (DBV) and hemoglobin oxygen saturation (HbO2) by means of an analytical model for the temporal evolution of free-induction-decay signals in the extravascular compartment. However, mutual coupling between DBV and HbO2in the signal model results in considerable estimation uncertainty precluding achievement of a unique set of solutions. To address this problem, we developed an interleaved qBOLD method (iqBOLD) that combines extravascular R2' and intravascular R2mapping techniques so as to obtain prior knowledge for the two unknown parameters. To achieve these goals, asymmetric spin echo and velocity-selective spin-labeling (VSSL) modules were interleaved in a single pulse sequence. Prior to VSSL, arterial blood and CSF signals were suppressed to produce reliable estimates for cerebral venous blood volume fraction (CBVv) as well as venous blood R2(to yield HbO2). Parameter maps derived from the VSSL module were employed to initialize DBV and HbO2in the qBOLD processing. Numerical simulations and in vivo experiments at 3 T were performed to evaluate the performance of iqBOLD in comparison to the parent qBOLD method. Data obtained in eight healthy subjects yielded plausible values averaging 60.1 ± 3.3% for HbO2and 3.1 ± 0.5 and 2.0 ± 0.4% for DBV in gray and white matter, respectively. Furthermore, the results show that prior estimates of CBVvand HbO2from the VSSL component enhance the solution stability in the qBOLD processing, and thus suggest the feasibility of iqBOLD as a promising alternative to the conventional technique for quantifying neurometabolic parameters.
Cerebrovascular reactivity (CVR) is an indicator of cerebrovascular reserve and provides important information about vascular health in a range of brain conditions and diseases. Unlike steady-state vascular parameters, such as cerebral blood flow (CBF) and cerebral blood volume (CBV), CVR measures the ability of cerebral vessels to dilate or constrict in response to challenges or maneuvers. Therefore, CVR mapping requires a physiological challenge while monitoring the corresponding hemodynamic changes in the brain. The present review primarily focuses on methods that use CO2 inhalation as a physiological challenge while monitoring changes in hemodynamic MRI signals. CO2 inhalation has been increasingly used in CVR mapping in recent literature due to its potency in causing vasodilation, rapid onset and cessation of the effect, as well as advances in MRI-compatible gas delivery apparatus. In this review, we first discuss the physiological basis of CVR mapping using CO2 inhalation. We then review the methodological aspects of CVR mapping, including gas delivery apparatus, the timing paradigm of the breathing challenge, the MRI imaging sequence, and data analysis. In addition, we review alternative approaches for CVR mapping that do not require CO2 inhalation.
The ultimate goal of calibrated fMRI is the quantitative imaging of oxygen metabolism (CMRO2), and this has been the focus of numerous methods and approaches. However, one underappreciated aspect of this quest is that in the drive to measure CMRO2, many other physiological parameters of interest are often acquired along the way. This can significantly increase the value of the dataset, providing greater information that is clinically relevant, or detail that can disambiguate the cause of signal variations. This can also be somewhat of a double-edged sword: calibrated fMRI experiments combine multiple parameters into a physiological model that requires multiple steps, thereby providing more opportunity for error propagation and increasing the noise and error of the final derived values. As with all measurements, there is a trade-off between imaging time, spatial resolution, coverage, and accuracy. In this review, we provide a brief overview of the benefits and pitfalls of extracting multiparametric measurements of cerebral physiology through calibrated fMRI experiments.
The brain is almost entirely dependent on oxidative metabolism to meet its energy requirements. As such, the cerebral metabolic rate of oxygen (CMRO2) is a direct measure of brain energy use. CMRO2 provides insight into brain functional architecture and has demonstrated potential as a clinical tool for assessing many common neurological disorders. Recent developments in magnetic resonance imaging (MRI)-based CMRO2 quantification have shown promise in spatially resolving CMRO2 in clinically feasible scan times. However, brain energy requirements are both spatially heterogeneous and temporally dynamic, responding to rapid changes in oxygen supply and demand in response to physiologic stimuli and neuronal activation. Methods for dynamic quantification of CMRO2 are lacking, and this dissertation aims to address this gap. Given the fundamental tradeoff between spatial and temporal resolution in MRI, we focus initially on the latter. Central to each proposed method is a model-based approach for deriving venous oxygen saturation (Yv) – the critical parameter for CMRO2 quantification – from MRI signal phase using susceptometry-based oximetry (SBO). First, a three-second-temporal-resolution technique for whole-brain quantification of Yv and CMRO2 is presented. This OxFlow method is applied to measure a small but highly significant increase in CMRO2 in response to volitional apnea. Next, OxFlow is combined with a competing approach for Yv quantification based on blood T2 relaxometry (TRUST). The resulting interleaved-TRUST (iTRUST) pulse sequence greatly improves T2-based CMRO2 quantification, while allowing direct, simultaneous comparison of SBO- and T2-based Yv. iTRUST is applied to assess the CMRO2 response to hypercapnia – a topic of great interest in functional neuroimaging – demonstrating significant biases between SBO- and T2-derived Yv and CMRO2. To address the need for dynamic and spatially resolved CMRO2 quantification, we explore blood-oxygen-level-dependent (BOLD) calibration, introducing a new calibration model and hybrid pulse sequence combining OxFlow with standard BOLD/CBF measurement. Preliminary results suggest Ox-BOLD provides improved calibration “M-maps” for converting BOLD signal to CMRO2. Finally, OxFlow is applied clinically to patients with obstructive sleep apnea (OSA). A small clinical pilot study demonstrates OSA-associated reductions in CMRO2 at baseline and in response to apnea, highlighting the potential utility of dynamic CMRO2 quantification in assessing neuropathology.
PurposeIt has been predicted that, during hyperoxia, excess O2 dissolved in arterial blood will significantly alter the blood's magnetic susceptibility. This would confound the interpretation of the hyperoxia-induced blood oxygenation level-dependent signal as arising solely from changes in deoxyhemoglobin. This study, therefore, aimed to determine how dissolved O2 affects the susceptibility of blood.Theory and Methods
We present a comprehensive model for the effect of dissolved O2 on the susceptibility of blood and compare it with another recently published model, referred to here as the ideal gas model (IGM). For validation, distilled water and samples of bovine plasma were oxygenated over a range of hyperoxic O2 concentrations and their susceptibilities were determined using multiecho gradient echo phase imaging.ResultsIn distilled water and plasma, the measured changes in susceptibility were very linear, with identical slopes of 0.062 ppb/mm Hg of O2. This change was dramatically less than previously predicted using the IGM and was close to that predicted by our model. The primary source of error in the IGM is the overestimation of the volume fraction occupied by dissolved O2.Conclusion
Under most physiological conditions, the susceptibility of dissolved O2 can be disregarded in MRI studies employing hyperoxia. Magn Reson Med, 2015. © 2015 Wiley Periodicals, Inc.
Probability theory is applied to the analysis of fMRI data. The posterior distribution of the parameters is shown to incorporate all the information available from the data, the hypotheses, and the prior information. Under appropriate simplifying conditions, the theory reduces to the standard statistical test, including the general linear model. The theory is particularly suited to handle the spatial variations in the noise present in fMRI, allowing the comparison of activated voxels that have different, and unknown, noise. The theory also explicitly includes prior information, which is shown to be critical in the attainment of reliable activation maps.
Characterizing the effect of oxygen (O(2)) modulation on the brain may provide a better understanding of several clinically relevant problems, including acute mountain sickness and hyperoxic therapy in patients with traumatic brain injury or ischemia. Quantifying the O(2) effects on brain metabolism is also critical when using this physiologic maneuver to calibrate functional magnetic resonance imaging (fMRI) signals. Although intuitively crucial, the question of whether the brain's metabolic rate depends on the amount of O(2) available has not been addressed in detail previously. This can be largely attributed to the scarcity and complexity of measurement techniques. Recently, we have developed an MR method that provides a noninvasive (devoid of exogenous agents), rapid (<5 minutes), and reliable (coefficient of variant, CoV <3%) measurement of the global cerebral metabolic rate of O(2) (CMRO(2)). In the present study, we evaluated metabolic and vascular responses to manipulation of the fraction of inspired O(2) (FiO(2)). Hypoxia with 14% FiO(2) was found to increase both CMRO(2) (5.0±2.0%, N=16, P=0.02) and cerebral blood flow (CBF) (9.8±2.3%, P<0.001). However, hyperoxia decreased CMRO(2) by 10.3±1.5% (P<0.001) and 16.9±2.7% (P<0.001) for FiO(2) of 50% and 98%, respectively. The CBF showed minimal changes with hyperoxia. Our results suggest that modulation of inspired O(2) alters brain metabolism in a dose-dependent manner.
Previous studies have shown that sensory stimulation and voluntary motor activity increase regional cerebral glucose consumption and regional cerebral blood flow (rCBF). The present study had 3 purposes: (1) to examine whether pure mental activity changed the oxidative metabolism of the brain and, if so, (2) to examine which anatomical structures were participating in the mental activity; and to examine whether there was any coupling of the rCBF to the physiological changes in the regional cerebral oxidative metabolism (rCMRO2). With a positron-emission tomograph (PET), we measured the rCMRO2, rCBF, and regional cerebral blood volume (rCBV) in independent sessions lasting 100 sec each. A dynamic method was used for the measurement of rCMRO2. The rCMRO2, rCBF, and rCBV were measured in 2 different states in 10 young, healthy volunteers: at rest and when visually imagining a specific route in familiar surroundings. The rCBF at rest was linearly correlated to the rCMRO2: rCBF (in ml/100 gm/min) = 11.4 rCMRO2 + 11.9. The specific mental visual imagery increased the rCMRO2 in 25 cortical fields, ranging in size from 2 to 10 cm3, located in homotypical cortex. Active fields were located in the superior and lateral prefrontal cortex and the frontal eye fields. The strongest increase of rCMRO2 appeared in the posterior superior lateral parietal cortex and the posterior superior medial parietal cortex in precuneus. Subcortically, the rCMRO2 increased in neostriatum and posterior thalamus. These focal metabolic increases were so strong that the CMRO2 of the whole brain increased by 10%. The rCBF increased proportionally in these active fields and structures, such that d(rCBF) in ml/100 gm/min = 11.1 d(rCMRO2). Thus, a dynamic coupling of the rCBF to the rCMRO2 was observed during the physiological increase in neural metabolism. On the basis of previous functional activation studies and our knowledge of anatomical connections in man and other primates, the posterior medial and lateral parietal cortices were classified as remote visual-association areas participating in the generation of visual images of spatial scenes from memory, and the posterior thalamus was assumed to participate in the retrieval of such memories.
This paper is devoted to a theory of the NMR signal behavior in biological tissues in the presence of static magnetic field inhomogeneities. We have developed an approach that analytically describes the NMR signal in the static dephasing regime where diffusion phenomena may be ignored. This approach has been applied to evaluate the NMR signal in the presence of a blood vessel network (with an application to functional imaging), bone marrow (for two specific trabecular structures, asymmetrical and columnar) and a ferrite contrast agent. All investigated systems have some common behavior. If the echo time TE is less than a known characteristic time tc for a given system, then the signal decays exponentially with an argument which depends quadratically on TE. This is equivalent to an R2* relaxation rate which is a linear function of TE. In the opposite case, when TE is greater than tc, the NMR signal follows a simple exponential decay and the relaxation rate does not depend on the echo time. For this time interval, R2* is a linear function of a) volume fraction sigma occupied by the field-creating objects, b) magnetic field Bo or just the objects' magnetic moment for ferrite particles, and c) susceptibility difference delta chi between the objects and the medium.
Arterial spine labeling (ASL) techniques have matured to the point that they can provide robust quantitative multislice measurements of cerebral blood flow (CBF) under most circumstances. These techniques provide better spatial and temporal resolution than positron-emission tomography (PET) and are entirely noninvasive, requiring no injections or radiation. The most obvious clinical application is in the evaluation of acute stroke, in which the primary pathology is a lack of CBF, precisely the quantity that is measured directly by ASL. The one major technical challenge that currently prevents more general application in the brain is the sensitivity to abnormally long transit delays.
Graded levels of supplemental inspired oxygen were investigated for their viability as a noninvasive method of obtaining intravascular magnetic resonance image contrast. Administered hyperoxia has been shown to be effective as a blood oxygenation level-dependent contrast agent for magnetic resonance imaging (MRI); however, it is known that high levels of inspired fraction of oxygen result in regionally decreased perfusion in the brain potentially confounding the possibility of using hyperoxia as a means of measuring blood flow and volume. Although the effects of hypoxia on blood flow have been extensively studied, the hyperoxic regime between normoxia and 100% inspired oxygen has been only intermittently studied. Subjects were studied at four levels of hyperoxia induced during a single session while perfusion was measured using arterial spin labelling MRI. Reductions in regional perfusion of grey matter were found to occur even at moderate levels of hyperoxia; however, perfusion changes at all oxygen levels were relatively mild (less than 10%) supporting the viability of hyperoxia-induced contrast.
Investigations into the blood oxygenation level-dependent (BOLD) functional MRI signal have used respiratory challenges with the aim of probing cerebrovascular physiology. Such challenges have altered the inspired partial pressures of either carbon dioxide or oxygen, typically to a fixed and constant level (fixed inspired challenge (FIC)). The resulting end-tidal gas partial pressures then depend on the subject's metabolism and ventilatory responses. In contrast, dynamic end-tidal forcing (DEF) rapidly and independently sets end-tidal oxygen and carbon dioxide to desired levels by altering the inspired gas partial pressures on a breath-by-breath basis using computer-controlled feedback. This study implements DEF in the MRI environment to map BOLD signal reactivity to CO(2). We performed BOLD (T2(*)) contrast FMRI in four healthy male volunteers, while using DEF to provide a cyclic normocapnic-hypercapnic challenge, with each cycle lasting 4 mins (PET(CO(2)) mean+/-s.d., from 40.9+/-1.8 to 46.4+/-1.6 mm Hg). This was compared with a traditional fixed-inspired (FI(CO(2))=5%) hypercapnic challenge (PET(CO(2)) mean+/-s.d., from 38.2+/-2.1 to 45.6+/-1.4 mm Hg). Dynamic end-tidal forcing achieved the desired target PET(CO(2)) for each subject while maintaining PET(O(2)) constant. As a result of CO(2)-induced increases in ventilation, the FIC showed a greater cyclic fluctuation in PET(O(2)). These were associated with spatially widespread fluctuations in BOLD signal that were eliminated largely by the control of PET(O(2)) during DEF. The DEF system can provide flexible, convenient, and physiologically well-controlled respiratory challenges in the MRI environment for mapping dynamic responses of the cerebrovasculature.
Recent observations indicate that traumatic brain injury (TBI) may be associated with mitochondrial dysfunction. This, along with growing use of brain tissue PO2 monitors, has led to considerable interest in the potential use of ventilation with 100% oxygen to treat patients who have suffered a TBI. To date, the impact of normobaric hyperoxia has only been evaluated using indirect measures of its impact on brain metabolism. To determine if normobaric hyperoxia improves brain oxygen metabolism following acute TBI, the authors directly measured the cerebral metabolic rate for oxygen (CMRO2) with positron emission tomography before and after ventilation with 100% oxygen.
Baseline measurements of arterial and jugular venous blood gases, mean arterial blood pressure, intracranial pressure, cerebral blood flow (CBF), cerebral blood volume, oxygen extraction fraction, and CMRO2 were made at baseline while the patients underwent ventilation with a fraction of inspired oxygen (FiO2) of 0.3 to 0.5. The FiO2 was then increased to 1.0, and 1 hour later all measurements were repeated. Five patients were studied a mean of 17.9 +/- 5.8 hours (range 12-23 hours) after trauma. The median admission Glasgow Coma Scale score was 7 (range 3-9). During ventilation with 100% oxygen, there was a marked rise in PaO2 (from 117 +/- 31 to 371 +/- 99 mm Hg, p < 0.0001) and a small rise in arterial oxygen content (12.7 +/- 4.0 to 13.3 +/- 4.6 vol %, p = 0.03). There were no significant changes in systemic hemodynamic or other blood gas measurements. At the baseline evaluation, bihemispheric CBF was 39 +/- 12 ml/100 g/min and bihemispheric CMRO2 was 1.9 +/- 0.6 ml/ 100 g/min. During hyperoxia there was no significant change in either of these measurements. (Values are given as the mean +/- standard deviation throughout.)
Normobaric hyperoxia did not improve brain oxygen metabolism. In the absence of outcome data from clinical trials, these preliminary data do not support the use of 100% oxygen in patients with acute TBI, although larger confirmatory studies are needed.
PurposeTo assess the effect of changes in end-tidal partial pressure of O2 (PETO2) on cerebrovascular reactivity (CVR) estimated from changes in blood oxygen level–dependent (BOLD) signal during cyclic changes in end-tidal partial pressure of CO2 (PETCO2).Materials and MethodsBOLD response to fixed cyclic step changes in PETCO2 (range = 30.4–48.8 mmHg) and PETO2 (range = 100.6–444.0 mmHg) was studied in four healthy volunteers.ResultsThe BOLD reactivity to PETCO2 and PETO2 were 0.283 (0.188–0.379) (median, range) and 0.004 (0.003–0.006)%/mmHg, respectively, in the whole brain; 0.438 (0.382–0.614) vs. 0.006 (0.004–0.009)%/mmHg, respectively, in the gray matter; and 0.075 (0.065–0.093) vs. 0.002 (0.001–0.002)%/mmHg, respectively, in the white matter.Conclusion
The BOLD reactivity to PETO2 was much smaller than that to PETCO2. However, BOLD reactivity can be significantly distorted by CO2-induced changes in PETO2. We conclude that PETO2 should be carefully controlled during studies that use BOLD reactivity as an indicator of CVR. J. Magn. Reson. Imaging 2007. © 2007 Wiley-Liss, Inc.
At high and medium magnetic field, the transverse NMR relaxation rate (T2−1) of water protons in blood is determined predominantly by the oxygenation state of haemoglobin. T2−1 dependes quadratically on the field strength and on the proportion of haemoglobin that is deoxygenated. Deoxygenation increases the volume magnetic susceptibility within the erythrocytes and thus creates local field gradients around these cells. From volume susceptibility measurements and the dependence of T2−1 on the pulse rate in the Carr-Purcell-Meiboom-Gill experiment, we show that the increase in T2−1 with increasing blood deoxygenation arises from diffusion of water through these field gradients.
Functional magnetic resonance imaging typically measures signal increases arising from changes in the transverse relaxation rate over small regions of the brain and associates these with local changes in cerebral blood flow, blood volume and oxygen metabolism. Recent developments in pulse sequences and image analysis methods have improved the specificity of the measurements by focussing on changes in blood flow or changes in blood volume alone. However, FMRI is still unable to match the physiological information obtainable from positron emission tomography (PET), which is capable of quantitative measurements of blood flow and volume, and can indirectly measure resting metabolism. The disadvantages of PET are its cost, its availability, its poor spatial resolution and its use of ionising radiation. The MRI techniques introduced here address some of these limitations and provide physiological data comparable with PET measurements. We present an 18-minute MRI protocol that produces multi-slice whole-brain coverage and yields quantitative images of resting cerebral blood flow, cerebral blood volume, oxygen extraction fraction, CMRO(2), arterial arrival time and cerebrovascular reactivity of the human brain in the absence of any specific functional task. The technique uses a combined hyperoxia and hypercapnia paradigm with a modified arterial spin labelling sequence.
The amplitude of the BOLD response to a stimulus is not only determined by changes in cerebral blood flow (CBF) and oxygen metabolism (CMRO(2)), but also by baseline physiological parameters such as haematocrit, oxygen extraction fraction (OEF) and blood volume. The calibrated BOLD approach aims to account for this physiological variation by performing an additional calibration scan. This calibration typically consists of a hypercapnia or hyperoxia respiratory challenge, although we propose that a measurement of the reversible transverse relaxation rate, R(2)', might also be used. A detailed model of the BOLD effect was used to simulate each of the calibration experiments, as well as the activation experiment, whilst varying a number of physiological parameters associated with the baseline state and response to activation. The effectiveness of the different calibration methods was considered by testing whether the BOLD response to activation scaled by the calibration parameter combined with the measured CBF provides sufficient information to reliably distinguish different levels of CMRO(2) response despite underlying physiological variability. In addition the effect of inaccuracies in the underlying assumptions of each technique were tested, e.g. isometabolism during hypercapnia. The three primary findings of the study were: 1) The new calibration method based on R(2)' worked reasonably well, although not as well as the ideal hypercapnia method; 2) The hyperoxia calibration method was significantly worse because baseline haematocrit and OEF must be assumed, and these physiological parameters have a significant effect on the measurements; and 3) the venous blood volume change with activation is an important confounding variable for all of the methods, with the hypercapnia method being the most robust when this is uncertain.
Quantitative arterial spin labeling (ASL) estimates of cerebral blood flow (CBF) during oxygen inhalation are important in several contexts, including functional experiments calibrated with hyperoxia and studies investigating the effect of hyperoxia on regional CBF. However, ASL measurements of CBF during hyperoxia are confounded by the reduction in the longitudinal relaxation time of arterial blood (T(1a) ) from paramagnetic molecular oxygen dissolved in blood plasma. The aim of this study is to accurately quantify the effect of arbitrary levels of hyperoxia on T(1a) and correct ASL measurements of CBF during hyperoxia on a per-subject basis. To mitigate artifacts, including the inflow of fresh spins, partial voluming, pulsatility, and motion, a pulsed ASL approach was implemented for in vivo measurements of T(1a) in the rat brain at 3 Tesla. After accounting for the effect of deoxyhemoglobin dilution, the relaxivity of oxygen on blood was found to closely match phantom measurements. The results of this study suggest that the measured ASL signal changes are dominated by reductions in T(1a) for brief hyperoxic inhalation epochs, while the physiologic effects of oxygen on the vasculature account for most of the measured reduction in CBF for longer hyperoxic exposures.
Calibrated blood oxygenation level dependent (BOLD) imaging, a technique used to measure changes in cerebral O(2) metabolism, depends on an accurate model of how the BOLD signal is affected by the mismatch between changes in cerebral blood flow (CBF) and cerebral metabolic rate of O(2) (CMRO(2)). However, other factors such as the cerebral blood volume (CBV) distribution at rest and with activation also affect the BOLD signal. The Davis model originally proposed for calibrated BOLD studies (Davis et al., 1998) is widely used because of its simplicity, but it assumes CBV changes are uniformly distributed across vascular compartments, neglects intravascular signal changes, and ignores blood-tissue signal exchange effects as CBV increases and supplants tissue volume. More recent studies suggest that venous CBV changes are smaller than arterial changes, and that intravascular signal changes and CBV exchange effects can bias estimated CMRO(2). In this paper, recent experimental results for the relationship between deoxyhemoglobin and BOLD signal changes are integrated in order to simulate the BOLD signal in detail by expanding a previous model to include a tissue compartment and three blood compartments rather than only the venous blood compartment. The simulated data were then used to test the accuracy of the Davis model of calibrated BOLD, demonstrating that the errors in estimated CMRO(2) responses across the typical CBF-CMRO(2) coupling range are modest despite the simplicity of the assumptions underlying the original derivation of the model. Nevertheless, the accuracy of the model can be improved by abandoning the original physical meaning of the two parameters α and β and treating them as adjustable parameters that capture several physical effects. For a 3Tesla field and a dominant arterial volume change with activation, the accuracy of the Davis model is improved with new values of α=0.14 and β=0.91.
The transverse relaxation rate (R(2)) of fresh human blood has been investigated at high and ultrahigh field, to characterize the R(2) dependency on blood sample oxygenation, hematocrit, and Carr-Purcell Meiboom-Gill sequence inter-echo spacing. Data were fitted to chemical exchange and diffusion models to assess their performance at different field strengths. The diffusion model gave a slightly superior fit at both field strengths, but the difference is unlikely to be relevant for the signal to noise ratio achieved in most in vivo experiments. Fitted model parameters were similar to those found in literature.
Oxygen delivered in supraphysiological amounts is currently under investigation as a therapy for severe traumatic brain injury (TBI). Hyperoxia can be delivered to the brain under normobaric as well as hyperbaric conditions. In this study the authors directly compare hyperbaric oxygen (HBO2) and normobaric hyperoxia (NBH) treatment effects.
Sixty-nine patients who had sustained severe TBIs (mean Glasgow Coma Scale Score 5.8) were prospectively randomized to 1 of 3 groups within 24 hours of injury: 1) HBO2, 60 minutes of HBO(2) at 1.5 ATA; 2) NBH, 3 hours of 100% fraction of inspired oxygen at 1 ATA; and 3) control, standard care. Treatments occurred once every 24 hours for 3 consecutive days. Brain tissue PO(2), microdialysis, and intracranial pressure were continuously monitored. Cerebral blood flow (CBF), arteriovenous differences in oxygen, cerebral metabolic rate of oxygen (CMRO2), CSF lactate and F2-isoprostane concentrations, and bronchial alveolar lavage (BAL) fluid interleukin (IL)-8 and IL-6 assays were obtained pretreatment and 1 and 6 hours posttreatment. Mixed-effects linear modeling was used to statistically test differences among the treatment arms as well as changes from pretreatment to posttreatment.
In comparison with values in the control group, the brain tissue PO2 levels were significantly increased during treatment in both the HBO2 (mean +/- SEM, 223 +/- 29 mm Hg) and NBH (86 +/- 12 mm Hg) groups (p < 0.0001) and following HBO2 until the next treatment session (p = 0.003). Hyperbaric O2 significantly increased CBF and CMRO2 for 6 hours (p < or = 0.01). Cerebrospinal fluid lactate concentrations decreased posttreatment in both the HBO2 and NBH groups (p < 0.05). The dialysate lactate levels in patients who had received HBO2 decreased for 5 hours posttreatment (p = 0.017). Microdialysis lactate/pyruvate (L/P) ratios were significantly decreased posttreatment in both HBO2 and NBH groups (p < 0.05). Cerebral blood flow, CMRO2, microdialysate lactate, and the L/P ratio had significantly greater improvement when a brain tissue PO2 > or = 200 mm Hg was achieved during treatment (p < 0.01). Intracranial pressure was significantly lower after HBO2 until the next treatment session (p < 0.001) in comparison with levels in the control group. The treatment effect persisted over all 3 days. No increase was seen in the CSF F2-isoprostane levels, microdialysate glycerol, and BAL inflammatory markers, which were used to monitor potential O2 toxicity.
Hyperbaric O2 has a more robust posttreatment effect than NBH on oxidative cerebral metabolism related to its ability to produce a brain tissue PO2 > or = 200 mm Hg. However, it appears that O2 treatment for severe TBI is not an all or nothing phenomenon but represents a graduated effect. No signs of pulmonary or cerebral O2 toxicity were present.
To understand and predict the blood-oxygenation level-dependent (BOLD) fMRI signal, an accurate knowledge of the relationship between cerebral blood flow (DeltaCBF) and volume (DeltaCBV) changes is critical. Currently, this relationship is widely assumed to be characterized by Grubb's power-law, derived from primate data, where the power coefficient (alpha) was found to be 0.38. The validity of this general formulation has been examined previously, and an alpha of 0.38 has been frequently cited when calculating the cerebral oxygen metabolism change (DeltaCMRo(2)) using calibrated BOLD. However, the direct use of this relationship has been the subject of some debate, since it is well established that the BOLD signal is primarily modulated by changes in 'venous' CBV (DeltaCBV(v), comprising deoxygenated blood in the capillary, venular, and to a lesser extent, in the arteriolar compartments) instead of total CBV, and yet DeltaCBV(v) measurements in humans have been extremely scarce. In this work, we demonstrate reproducible DeltaCBV(v) measurements at 3 T using venous refocusing for the volume estimation (VERVE) technique, and report on steady-state DeltaCBV(v) and DeltaCBF measurements in human subjects undergoing graded visual and sensorimotor stimulation. We found that: (1) a BOLD-specific flow-volume power-law relationship is described by alpha = 0.23 +/- 0.05, significantly lower than Grubb's constant of 0.38 for total CBV; (2) this power-law constant was not found to vary significantly between the visual and sensorimotor areas; and (3) the use of Grubb's value of 0.38 in gradient-echo BOLD modeling results in an underestimation of DeltaCMRo(2).
Gradient and spin echo (GRE and SE, respectively) weighted magnetic resonance images report on neuronal activity via changes in deoxygenated hemoglobin content and cerebral blood volume induced by alterations in neuronal activity. Hence, vasculature plays a critical role in these functional signals. However, how the different blood vessels (e.g. arteries, arterioles, capillaries, venules and veins) quantitatively contribute to the functional MRI (fMRI) signals at each field strength, and consequently, how spatially specific these MRI signals are remain a source of discussion. In this study, we utilize an integrative model of the fMRI signals up to 16.4 T, exploiting the increasing body of published information on relevant physiological parameters. Through simulations, extra- and intravascular functional signal contributions were determined as a function of field strength, echo time (TE) and MRI sequence used. The model predicted previously reported effects, such as feasibility of optimization of SE but not the GRE approach to yield larger micro-vascular compared to macro-vascular weighting. In addition, however, micro-vascular effects were found to peak with increasing magnetic fields even in the SE approach, and further increases in magnetic fields imparted no additional benefits besides beyond the inherent signal-to-noise (SNR) gains. Furthermore, for SE, using a TE larger than the tissue T(2) enhances micro-vasculature signal relatively, though compromising SNR for spatial specificity. In addition, the intravascular SE MRI signals do not fully disappear even at high field strength as arteriolar and capillary contributions persist. The model, and the physiological considerations presented here can also be applied in contrast agent experiments and to other models, such as calibrated BOLD approach and vessel size imaging.
Hill's equation can be slightly modified to fit the standard human blood O2 dissociation curve to within plus or minus 0.0055 fractional saturation (S) from O less than S less than 1. Other modifications of Hill's equation may be used to compute Po2 (Torr) from S (Eq. 2), and the temperature coefficient of Po2 (Eq. 3). Variations of the Bohr coefficient with Po2 are given by Eq. 4. S = (((Po2(3) + 150 Po2)(-1) x 23,400) + 1)(-1) (1) In Po2 = 0.385 In (S-1 - 1)(-1) + 3.32 - (72 S)(-1) - 0.17(S6) (2) DELTA In Po2/delta T = 0.058 ((0.243 X Po2/100)(3.88) + 1)(-1) + 0.013 (3) delta In Po2/delta pH = (Po2/26.6)(0.184) - 2.2 (4) Procedures are described to determine Po2 and S of blood iteratively after extraction or addition of a defined amount of O2 and to compute P50 of blood from a single sample after measuring Po2, pH, and S.
Using high-resolution positron emission tomography and the oxygen 15 continuous inhalation method, we examined the changes in cerebral metabolic rate of oxygen, blood flow, blood volume, and oxygen extraction fraction as a function of age in 25 optimally healthy, unmedicated volunteers who ranged in age from 20 to 68 years. Subjects were strictly selected for absence of cerebrovascular risk factors, dementia, or mental disorders; they had neither biological nor clinical abnormalities, and no focal anomaly on computed tomographic scan. Regions of interest were determined according to the anatomical structures defined on corresponding computed tomographic scan cuts obtained using a stereotaxic head-positioning method. This same method was also used for positron emission tomographic imaging. There was no significant effect of aging on PaCO2 values, hematocrit, arterial blood pressure, cholesterol and triglyceride levels, and blood glucose levels. In most cerebral cortex gyri, the cerebral metabolic rate of oxygen significantly decreased with age according to a linear pattern, with the same magnitude (about -6% per decade) in all four lobes and on both sides. This effect of age on cortical cerebral metabolic rate of oxygen persisted when the possible influence of cortical atrophy, gender, and head size were partialled out. In contrast, the white matter, deep gray nuclei, thalamus, and cerebellum were not significantly affected. The cerebral blood volume declined with a similar pattern to cerebral metabolic rate of oxygen, while changes in cerebral blood flow were less significant, presumably because of larger variance of data across subjects.(ABSTRACT TRUNCATED AT 250 WORDS)
A new three-dimensional imaging technique which is applicable for 3D MR imaging throughout the body is introduced. In our preliminary investigations we have acquired high-quality 3D image sets of the abdomen showing minimal respiratory artifacts in just over 7 min (voxel size 2.7 X 2.7 X 2.7 mm3), and 3D image sets of the head showing excellent gray/white contrast in less than 6 min (voxel size 1.0 X 2.0 X 1.4 mm3).
Quantification of regional cerebral blood flow (rCBF) and volume (rCBV) with dynamic magnetic resonance (MR) imaging.
After bolus administration of a paramagnetic contrast medium, rapid T2*-weighted gradient-echo images of two sections were acquired for the simultaneous creation of concentration-time curves in the brain-feeding arteries and in brain tissue. Absolute rCBF and rCBV values were determined for gray and white brain matter in 12 subjects with use of principles of the indicator dilution theory.
The mean rCBF value in gray matter was 69.7 mL/min +/- 29.7 per 100 g tissue and in white matter, 33.6 mL/min +/- 11.5 per 100 g tissue; the average rCBV was 8.0 mL +/- 3.1 per 100 g tissue and 4.2 mL +/- 1.0 per 100 g tissue, respectively. An age-related decrease in rCBF and rCBV for gray and white matter was observed.
Preliminary data demonstrate that the proposed technique allows the quantification of rCBF and rCBV. Although the results are in good agreement with data from positron emission tomography studies, further evaluation is needed to establish the validity of method.
It recently has been demonstrated that magnetic resonance imaging can be used to map changes in brain hemodynamics produced by human mental operations. One method under development relies on blood oxygenation level-dependent (BOLD) contrast: a change in the signal strength of brain water protons produced by the paramagnetic effects of venous blood deoxyhemoglobin. Here we discuss the basic quantitative features of the observed BOLD-based signal changes, including the signal amplitude and its magnetic field dependence and dynamic effects such as a pronounced oscillatory pattern that is induced in the signal from primary visual cortex during photic stimulation experiments. The observed features are compared with the results of Monte Carlo simulations of water proton intravoxel phase dispersion produced by local field gradients generated by paramagnetic deoxyhemoglobin in nearby venous blood vessels. The simulations suggest that the effect of water molecule diffusion is strong for the case of blood capillaries, but, for larger venous blood vessels, water diffusion is not an important determinant of deoxyhemoglobin-induced signal dephasing. We provide an expression for the apparent in-plane relaxation rate constant (R2*) in terms of the main magnetic field strength, the degree of the oxygenation of the venous blood, the venous blood volume fraction in the tissue, and the size of the blood vessel.
Recently, several implementations of arterial spin labeling (ASL) techniques have been developed for producing MRI images sensitive to local tissue perfusion. For quantitation of perfusion, both pulsed and continuous labeling methods potentially suffer from a number of systematic errors. In this study, a general kinetic model for the ASL signal is described that can be used to assess these errors. With appropriate assumptions, the general model reduces to models that have been used previously to analyze ASL data, but the general model also provides a way to analyze the errors that result if these assumptions are not accurate. The model was used for an initial assessment of systematic errors due to the effects of variable transit delays from the tagging band to the imaging voxel, the effects of capillary/tissue exchange of water on the relaxation of the tag, and the effects of incomplete water extraction. In preliminary experiments with a human subject, the model provided a good description of pulsed ASL data during a simple sensorimotor activation task.
A theory is presented for describing the effect on the transverse NMR relaxation rate of microscopic spatial inhomogeneities in the static magnetic field. The theory applies when the inhomogeneities are weak in magnitude and the nuclear spins diffuse a significant distance in comparison with a length scale characterizing the inhomogeneities. It is shown that the relaxation rate is determined by a temporal correlation function and depends quadratically on the magnitude of the inhomogeneities. For the case of unrestricted diffusion, a simple algebraic approximation for the temporal correlation function is derived. The theory is illustrated by applying it to a model of randomly distributed magnetized spheres. The theory is also used to fit experimental data for the dependence of the relaxation rate on the interecho time for a Carr-Purcell-Meiboom-Gill pulse sequence. The experimental systems considered are in vitro red blood cell suspensions and samples of human gray matter and rat liver. Magn Reson Med 44:144-156, 2000.
The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogram-based model, the FM has an intrinsic limitation--no spatial information is taken into account. This causes the FM model to work only on well-defined images with low levels of noise; unfortunately, this is often not the the case due to artifacts such as partial volume effect and bias field distortion. Under these conditions, FM model-based methods produce unreliable results. In this paper, we propose a novel hidden Markov random field (HMRF) model, which is a stochastic process generated by a MRF whose state sequence cannot be observed directly but which can be indirectly estimated through observations. Mathematically, it can be shown that the FM model is a degenerate version of the HMRF model. The advantage of the HMRF model derives from the way in which the spatial information is encoded through the mutual influences of neighboring sites. Although MRF modeling has been employed in MR image segmentation by other researchers, most reported methods are limited to using MRF as a general prior in an FM model-based approach. To fit the HMRF model, an EM algorithm is used. We show that by incorporating both the HMRF model and the EM algorithm into a HMRF-EM framework, an accurate and robust segmentation can be achieved. More importantly, the HMRF-EM framework can easily be combined with other techniques. As an example, we show how the bias field correction algorithm of Guillemaud and Brady (1997) can be incorporated into this framework to achieve a three-dimensional fully automated approach for brain MR image segmentation.
In functional magnetic resonance imaging statistical analysis there are problems with accounting for temporal autocorrelations when assessing change within voxels. Techniques to date have utilized temporal filtering strategies to either shape these autocorrelations or remove them. Shaping, or "coloring," attempts to negate the effects of not accurately knowing the intrinsic autocorrelations by imposing known autocorrelation via temporal filtering. Removing the autocorrelation, or "prewhitening," gives the best linear unbiased estimator, assuming that the autocorrelation is accurately known. For single-event designs, the efficiency of the estimator is considerably higher for prewhitening compared with coloring. However, it has been suggested that sufficiently accurate estimates of the autocorrelation are currently not available to give prewhitening acceptable bias. To overcome this, we consider different ways to estimate the autocorrelation for use in prewhitening. After high-pass filtering is performed, a Tukey taper (set to smooth the spectral density more than would normally be used in spectral density estimation) performs best. Importantly, estimation is further improved by using nonlinear spatial filtering to smooth the estimated autocorrelation, but only within tissue type. Using this approach when prewhitening reduced bias to close to zero at probability levels as low as 1 x 10(-5).
The presence of magnetic background field inhomogeneity (DeltaB) may confound quantitative measures of cerebral venous blood volume (vCBV) and cerebral oxygen extraction fraction (MR_OEF) with T2*-based methods. The goal of this study was to correct its effect and obtain more accurate estimates of vCBV and MR_OEF. A 3D high-resolution gradient echo sequence was employed to obtain DeltaB maps by two algorithms. The DeltaB maps were then used to recover the signal loss in images acquired by a 2D multiecho gradient echo / spin echo sequence. Finally, both quantitative estimates of MR_OEF and vCBV were obtained from the DeltaB- corrected 2D multiecho gradient echo / spin echo images. A total of 12 normal subjects were studied. An overestimated vCBV was observed in the brain (4.29 +/- 0.78%) prior to DeltaB correction, while the measured vCBV was substantially reduced after DeltaB correction. Whole brain vCBV of 2.97 +/- 0.44% and 2.68 +/- 0.47% were obtained by the two different DeltaB correction methods, in excellent agreement with the reported results in the literature. Furthermore, when MR_OEF was compared with and without DeltaB correction, no significant differences (P = 0.467) were observed. The ability to simultaneously obtain vCBV and MR_OEF noninvasively may have profound clinical implications for the studies of cerebrovascular disease.
Approaches to obtain quantitative, noninvasive estimates of total cerebral blood volume (tCBV) and cerebral venous blood volume (vCBV) separately in humans are proposed. Two sequences were utilized, including a 3D high-resolution gradient-echo (GE) sequence and a 2D multi-echo GE/spin-echo (MEGESE) sequence. Images acquired by the former sequence provided an estimate of background magnetic field variations (DeltaB), while images obtained by the latter sequence were utilized to obtain separate measures of tCBV and vCBV with and without contrast agent. Prior to the calculation of vCBV and tCBV, the acquired images were corrected for signal loss induced by the presence of DeltaB. vCBV and tCBV were estimated to be 2.46% +/- 0.28% and 3.20% +/- 0.41%, respectively, after the DeltaB correction, which in turn provided a vCBV/tCBV ratio of 0.77 +/- 0.04, in excellent agreement with results reported in the literature. Our results demonstrate that quantitative estimates of vCBV and tCBV can be obtained in vivo.
Linear registration and motion correction are important components of structural and functional brain image analysis. Most modern methods optimize some intensity-based cost function to determine the best registration. To date, little attention has been focused on the optimization method itself, even though the success of most registration methods hinges on the quality of this optimization. This paper examines the optimization process in detail and demonstrates that the commonly used multiresolution local optimization methods can, and do, get trapped in local minima. To address this problem, two approaches are taken: (1) to apodize the cost function and (2) to employ a novel hybrid global-local optimization method. This new optimization method is specifically designed for registering whole brain images. It substantially reduces the likelihood of producing misregistrations due to being trapped by local minima. The increased robustness of the method, compared to other commonly used methods, is demonstrated by a consistency test. In addition, the accuracy of the registration is demonstrated by a series of experiments with motion correction. These motion correction experiments also investigate how the results are affected by different cost functions and interpolation methods.
An automated method for segmenting magnetic resonance head images into brain and non-brain has been developed. It is very robust and accurate and has been tested on thousands of data sets from a wide variety of scanners and taken with a wide variety of MR sequences. The method, Brain Extraction Tool (BET), uses a deformable model that evolves to fit the brain's surface by the application of a set of locally adaptive model forces. The method is very fast and requires no preregistration or other pre-processing before being applied. We describe the new method and give examples of results and the results of extensive quantitative testing against "gold-standard" hand segmentations, and two other popular automated methods.
Gradient-echo (GRE) blood oxygen level-dependent (BOLD) effects have both intra- and extravascular contributions. To better understand the intravascular contribution in quantitative terms, the spin-echo (SE) and GRE transverse relaxation rates, R(2) and R(2)(*), of isolated blood were measured as a function of oxygenation in a perfusion system. Over the normal oxygenation saturation range of blood between veins, capillaries, and arteries, the difference between these rates, R'(2) = R(2)(*) - R(2), ranged from 1.5 to 2.1 Hz at 1.5 T and from 26 to 36 Hz at 4.7 T. The blood data were used to calculate the expected intravascular BOLD effects for physiological oxygenation changes that are typical during visual activation. This modeling showed that intravascular DeltaR(2)(*) is caused mainly by R(2) relaxation changes, namely 85% and 78% at 1.5T and 4.7T, respectively. The simulations also show that at longer TEs (>70 ms), the intravascular contribution to the percentual BOLD change is smaller at high field than at low field, especially for GRE experiments. At shorter TE values, the opposite is the case. For pure parenchyma, the intravascular BOLD signal changes originate predominantly from venules for all TEs at low field and for short TEs at high field. At longer TEs at high field, the capillary contribution dominates. The possible influence of partial volume contributions with large vessels was also simulated, showing large (two- to threefold) increases in the total intravascular BOLD effect for both GRE and SE.
In the present study blood T(1) was determined as a function of hematocrit and oxygen saturation. T(1) showed a significant linear dependency on both of these parameters. In addition, oxygen dissolved in blood plasma in hyperoxygenated blood resulted in relaxation enhancement, comparable in size to that due to the change in oxygenation state of hemoglobin. As blood T(1) is a key factor for quantification of flow with arterial spin labeling methods, the influence of T(1) variation in the physiological range of hematocrit and oxygen saturation to flow determination is discussed.
Since Ogawa et al. (Proc Natl Acad Sci USA 1990;87:9868-9872) made the fundamental discovery of blood oxygenation level-dependent (BOLD) contrast in MRI, most efforts have been directed toward the study of dynamic BOLD (i.e., temporal changes in the MRI signal during changes in brain activity). However, very little progress has been made in elucidating the nature of BOLD contrast during the resting or baseline state of the brain, which is important for understanding normal human performance because it accounts for most of the enormous energy budget of the brain. It is also crucial for deciphering the consequences of baseline-state impairment by cerebral vascular diseases. The objective of this study was to develop a BOLD MR-based method that allows quantitative evaluation of tissue hemodynamic parameters, such as the blood volume, deoxyhemoglobin concentration, and oxygen extraction fraction (OEF). The proposed method, which we have termed quantitative BOLD (qBOLD), is based on an MR signal model that incorporates prior knowledge about brain tissue composition and considers signals from gray matter (GM), white matter (WM), cerebrospinal fluid (CSF), and blood. A 2D gradient-echo sampling of spin-echo (GESSE) pulse sequence is used for the acquisition of the MRI signal. The method is applied to estimate the hemodynamic parameters of the normal human brain in the baseline state.
Previous reports indicate that compared with normoxia, 100% ventilatory O(2) during early reperfusion after global cerebral ischemia decreases hippocampal pyruvate dehydrogenase activity and increases neuronal death. However, current standards of care after cardiac arrest encourage the use of 100% O(2) during resuscitation and for an undefined period thereafter. Using a clinically relevant canine cardiac arrest model, in this study we tested the hypothesis that hyperoxic reperfusion decreases hippocampal glucose metabolism and glutamate synthesis.
After 10 minutes of cardiac arrest, animals were resuscitated and ventilated for 1 hour with 100% O(2) (hyperoxic) or 21% to 30% O(2) (normoxic). At 30 minutes reperfusion, [1-(13)C]glucose was infused, and at 2 hours, brains were rapidly removed and frozen. Extracted metabolites were analyzed by (13)C nuclear magnetic resonance spectroscopy.
Compared with nonischemic controls, the hippocampi from hyperoxic animals had elevated levels of unmetabolized (13)C-glucose and decreased incorporation of (13)C into all isotope isomers of glutamate. These findings indicate impaired neuronal metabolism via the pyruvate dehydrogenase pathway for carbon entry into the tricarboxylic acid cycle and impaired glucose metabolism via the astrocytic pyruvate carboxylase pathway. No differences were observed in the cortex, indicating that the hippocampus is more vulnerable to metabolic changes induced by hyperoxic reperfusion.
These results represent the first direct evidence that hyperoxia after cardiac arrest impairs hippocampal oxidative energy metabolism in the brain and challenge the rationale for using excessively high resuscitative ventilatory O(2).
The estimation of changes in CMR(O2) using functional MRI involves an essential calibration step using a vasoactive agent to induce an isometabolic change in CBF. This calibration procedure is performed most commonly using hypercapnia as the isometabolic stimulus. However, hypercapnia possesses a number of detrimental side effects. Here, a new method is presented using hyperoxia to perform the same calibration step. This procedure requires independent measurement of Pa(O2), the BOLD signal, and CBF. We demonstrate that this method yields results that are comparable to those derived using other methods. Further, the hyperoxia technique is able to provide an estimate of the calibration constant that has lower overall intersubject and intersession variability compared to the hypercapnia approach.
Knowledge of the transverse relaxation rates R2 and R2* of blood is relevant for quantitative assessment of functional MRI (fMRI) results, including calibration of blood oxygenation and measurement of tissue oxygen extraction fractions (OEFs). In a temperature controlled circulation system, these rates were measured for blood in vitro at 3T under conditions akin to the physiological state. Single spin echo (SE) and gradient echo (GRE) sequences were used to determine R2 and R2*, respectively. Both rates varied quadratically with deoxygenation, and changes in R2* were found to be due predominantly to changes in R2. These data were used to estimate intravascular blood oxygenation level dependent (BOLD) contributions during visual activation. Due to the large R2* in venous blood, intravascular SE BOLD signal changes were larger than GRE effects at echo times above 30 ms. When including extravascular effects to estimate the total BOLD effect, GRE BOLD dominated due to the large tissue volume fraction.
To develop a new method of measuring quantitative regional cerebral blood volume (CBV) using epochs of hyperoxia as an intravenous contrast agent with T2*-weighted MRI.
Images were acquired from six subjects (four male, two female, mean age 29 +/- 3.7 years) using a sequence combining pulsed arterial spin labeling interleaved with a gradient echo echo-planar imaging (EPI) blood oxygenation level-dependent (BOLD) sequence at 3T. The hyperoxia paradigm lasted 28 minutes consisting of 4 minutes of normoxia, two 6-minute blocks of hyperoxia separated by 6 minutes of normoxia. During the hyperoxic blocks the subjects were delivered a fractional oxygen concentration of 0.5.
The mean CBV was calculated to be 3.77 +/- 1.05 mL/100 g globally, 3.93 +/- 0.90 mL/100 g in gray matter (GM), and 2.52 +/- 0.78 mL/100 g in white matter (WM). The mean GM/WM ratio was thus found to be 1.56. These values are comparable to those obtained in other studies.
The hyperoxia technique for measuring CBV may be particularly useful for patient groups where an injected bolus of contrast agent is contraindicated. As more functional studies are employing epochs of inspired gases for calibration purposes, this method is easily incorporated into existing paradigms to produce a noninvasive, repeatable, easily tolerated, and quantitative measurement of regional CBV.
A reliable, accurate, and accessible method for measuring cerebral blood volume (CBV) has been developed based on T(*) (2)-weighted MRI and a 1-min infusion of gadolinium instead of a bolus. Computer simulations predict that this infusion CBV method will have a signal-to-noise ratio (SNR) 3-5 times greater than that obtained by area-under-the-curve (AUC) methods, with high accuracy over a wide range of arterial, tissue, and MRI conditions. In six healthy controls, the CBV was 1.87 +/- 0.44 in white matter (WM), 3.40 +/- 0.44 in deep gray matter (DGM), and 3.84 +/- 1.87 ml blood/100 g tissue in cortical GM (CGM). The mean GM/WM ratio was 1.94. In five patients with bilateral carotid disease, the corresponding values were 2.63 +/- 0.33, 4.72 +/- 0.33, and 5.27 +/- 2.40 ml blood/100 g tissue, all of which were significantly different from controls. AUC values were generally higher and failed to demonstrate differences between controls and patients. The infusion method shows great potential for providing reliable, accurate, and accessible CBV values with the ability to discriminate physiologic or pathological volume changes under a wide range of conditions.
Linear registration and motion correction are important components of structural and functional brain image analysis. Most modern methods optimise some intensity-based cost function to determine the best registration.
Pathophysiology of Disease: An Introduction to Clinical Medicine
- S J Mcphee
- G D Hammer
McPhee, S.J., Hammer, G.D., 2009. Pathophysiology of Disease: An Introduction to Clinical
Medicine, Sixth ed. Lange Medical Books.
Quantification of regional cerebral blood flow and volume with dynamic susceptibility contrastenhanced MR imaging
- K A Rempp
- G Brix
- F Wenz
- C R Becker
- F Gückel
- W J Lorenz
Rempp, K.A., Brix, G., Wenz, F., Becker, C.R., Gückel, F., Lorenz, W.J., 1994. Quantification of
regional cerebral blood flow and volume with dynamic susceptibility contrastenhanced MR imaging. Radiology 193, 637-641.
Temporal autocorrelation in univariate linear modeling of FMRI data
- M W Woolrich
- B D Ripley
- M Brady
- S M Smith
Woolrich, M.W., Ripley, B.D., Brady, M., Smith, S.M., 2001. Temporal autocorrelation in
univariate linear modeling of FMRI data. NeuroImage 14, 1370-1386.
- N P Blockley
N.P. Blockley et al. / NeuroImage 72 (2013) 33–40
Pathophysiology of Disease An Introduction to Clinical Medicine. Sixth Edition. Lange Medical Books
- S J Mcphee
- G D Hammer
McPhee, SJ.; Hammer, GD. Pathophysiology of Disease An Introduction to Clinical Medicine. Sixth
Edition. Lange Medical Books; 2009.