Whole-brain mapping of venous vessel size in humans using the hypercapnia-induced BOLD effect

Tale of Two Cities: narrative review of oxygen

The human brain contributes 2% of the body weight yet receives 15% of cardiac output and demands a constant supply of oxygen (O ₂) and nutrients to meet its metabolic needs. Cerebral autoregulation is responsible for maintaining a constant cerebral blood flow that provides the supply of oxygen and maintains the energy storage capacity. We selected oxygen administration-related studies published between 1975-2021 that included meta-analysis, original research, commentaries, editorial, and review articles. In the present narrative review, several important aspects of the oxygen effects on brain tissues and cerebral autoregulation are discussed, as well the role of exogenous O ₂ administration in patients with chronic ischemic cerebrovascular disease: We aimed to revisit the utility of O ₂ administration in pathophysiological situations whether or not being advantageous. Indeed, a compelling clinical and experimental body of evidence questions the utility of routine oxygen administration in acute and post-recovery brain ischemia, as evident by studies in neurophysiology imaging. While O ₂ is still part of common clinical practice, it remains unclear whether its routine use is safe.

Detection of functional activity in brain white matter using fiber architecture informed synchrony mapping

A general linear model is widely used for analyzing fMRI data, in which the blood oxygenation-level dependent (BOLD) signals in gray matter (GM) evoked in response to neural stimulation are modeled by convolving the time course of the expected neural activity with a canonical hemodynamic response function (HRF) obtained a priori. The maps of brain activity produced reflect the magnitude of local BOLD responses. However, detecting BOLD signals in white matter (WM) is more challenging as the BOLD signals are weaker and the HRF is different, and may vary more across the brain. Here we propose a model-free approach to detect changes in BOLD signals in WM by measuring task-evoked increases of BOLD signal synchrony in WM fibers. The proposed approach relies on a simple assumption that, in response to a functional task, BOLD signals in relevant fibers are modulated by stimulus-evoked neural activity and thereby show greater synchrony than when measured in a resting state, even if their magnitudes do not change substantially. This approach is implemented in two technical stages. First, for each voxel a fiber-architecture-informed spatial window is created with orientation distribution functions constructed from diffusion imaging data. This provides the basis for defining neighborhoods in WM that share similar local fiber architectures. Second, a modified principal component analysis (PCA) is used to estimate the synchrony of BOLD signals in each spatial window. The proposed approach is validated using a 3T fMRI dataset from the Human Connectome Project (HCP) at a group level. The results demonstrate that neural activity can be reliably detected as increases in fMRI signal synchrony within WM fibers that are engaged in a task with high sensitivities and reproducibility.

Diffusion-informed spatial smoothing of fMRI data in white matter using spectral graph filters

Brain activation mapping using functional magnetic resonance imaging (fMRI) has been extensively studied in brain gray matter (GM), whereas in large disregarded for probing white matter (WM). This unbalanced treatment has been in part due to controversies in relation to the nature of the blood oxygenation level-dependent (BOLD) contrast in WM and its detectability. However, an accumulating body of studies has provided solid evidence of the functional significance of the BOLD signal in WM and has revealed that it exhibits anisotropic spatio-temporal correlations and structure-specific fluctuations concomitant with those of the cortical BOLD signal. In this work, we present an anisotropic spatial filtering scheme for smoothing fMRI data in WM that accounts for known spatial constraints on the BOLD signal in WM. In particular, the spatial correlation structure of the BOLD signal in WM is highly anisotropic and closely linked to local axonal structure in terms of shape and orientation, suggesting that isotropic Gaussian filters conventionally used for smoothing fMRI data are inadequate for denoising the BOLD signal in WM. The fundamental element in the proposed method is a graph-based description of WM that encodes the underlying anisotropy observed across WM, derived from diffusion-weighted MRI data. Based on this representation, and leveraging graph signal processing principles, we design subject-specific spatial filters that adapt to a subject's unique WM structure at each position in the WM that they are applied at. We use the proposed filters to spatially smooth fMRI data in WM, as an alternative to the conventional practice of using isotropic Gaussian filters. We test the proposed filtering approach on two sets of simulated phantoms, showcasing its greater sensitivity and specificity for the detection of slender anisotropic activations, compared to that achieved with isotropic Gaussian filters. We also present WM activation mapping results on the Human Connectome Project's 100-unrelated subject dataset, across seven functional tasks, showing that the proposed method enables the detection of streamline-like activations within axonal bundles.

Retrospective Correction of Physiological Noise: Impact on Sensitivity, Specificity, and Reproducibility of Resting-State Functional Connectivity in a Reading Network Model

It is well accepted that physiological noise (PN) obscures the detection of neural fluctuations in resting-state functional connectivity (rsFC) magnetic resonance imaging. However, a clear consensus for an optimal PN correction (PNC) methodology and how it can impact the rsFC signal characteristics is still lacking. In this study, we probe the impact of three PNC methods: RETROICOR: (Glover et al., 2000 ), ANATICOR: (Jo et al., 2010 ), and RVTMBPM: (Bianciardi et al., 2009 ). Using a reading network model, we systematically explore the effects of PNC optimization on sensitivity, specificity, and reproducibility of rsFC signals. In terms of specificity, ANATICOR was found to be effective in removing local white matter (WM) fluctuations and also resulted in aggressive removal of expected cortical-to-subcortical functional connections. The ability of RETROICOR to remove PN was equivalent to removal of simulated random PN such that it artificially inflated the connection strength, thereby decreasing sensitivity. RVTMBPM maintained specificity and sensitivity by balanced removal of vasodilatory PN and local WM nuisance edges. Another aspect of this work was exploring the effects of PNC on identifying reading group differences. Most PNC methods accounted for between-subject PN variability resulting in reduced intersession reproducibility. This effect facilitated the detection of the most consistent group differences. RVTMBPM was most effective in detecting significant group differences due to its inherent sensitivity to removing spatially structured and temporally repeating PN arising from dense vasculature. Finally, results suggest that combining all three PNC resulted in "overcorrection" by removing signal along with noise.

Iron, Myelin, and the Brain: Neuroimaging Meets Neurobiology

Although iron is crucial for neuronal functioning, many aspects of cerebral iron biology await clarification. The ability to quantify specific iron forms in the living brain would open new avenues for diagnosis, therapeutic monitoring, and understanding pathogenesis of diseases. A modality that allows assessment of brain tissue composition in vivo, in particular of iron deposits or myelin content on a submillimeter spatial scale, is magnetic resonance imaging (MRI). Multimodal strategies combining MRI with complementary analytical techniques ex vivo have emerged, which may lead to improved specificity. Interdisciplinary collaborations will be key to advance beyond simple correlative analyses in the biological interpretation of MRI data and to gain deeper insights into key factors leading to iron accumulation and/or redistribution associated with neurodegeneration.

BOLD-based cerebrovascular reactivity vascular transfer function isolates amplitude and timing responses to better characterize cerebral small vessel disease

Cerebrovascular reactivity (CVR) is a dynamic measure of the cerebral blood vessel response to vasoactive stimulus. Conventional CVR measures amplitude changes in the blood-oxygenation-level-dependent (BOLD) signal per unit change in end-tidal CO₂ (P_ET CO₂ ), effectively discarding potential timing information. This study proposes a deconvolution procedure to characterize CVR responses based on a vascular transfer function (VTF) that separates amplitude and timing CVR effects. We implemented the CVR-VTF to primarily evaluate normal-appearing white matter (WM) responses in those with a range of small vessel disease. Comparisons between simulations of P_ET CO₂ input models revealed that boxcar and ramp hypercapnia paradigms had the lowest relative deconvolution error. We used a T₂ * BOLD-MRI sequence on a 3 T MRI scanner, with a boxcar delivery model of CO₂ , to test the CVR-VTF approach in 18 healthy adults and three white matter hyperintensity (WMH) groups: 20 adults with moderate WMH, 12 adults with severe WMH, and 10 adults with genetic WMH (CADASIL). A subset of participants performed a second CVR session at a one-year follow-up. Conventional CVR, area under the curve of VTF (VTF-AUC), and VTF time-to-peak (VTF-TTP) were assessed in WM and grey matter (GM) at baseline and one-year follow-up. WMH groups had lower WM VTF-AUC compared with the healthy group (p < 0.0001), whereas GM CVR did not differ between groups (p > 0.1). WM VTF-TTP of the healthy group was less than that in the moderate WMH group (p = 0.016). Baseline VTF-AUC was lower than follow-up VTF-AUC in WM (p = 0.013) and GM (p = 0.026). The intraclass correlation for VTF-AUC in WM was 0.39 and coefficient of repeatability was 0.08 [%BOLD/mm Hg]. This study assessed CVR timing and amplitude information without applying model assumptions to the CVR response; this approach may be useful in the development of robust clinical biomarkers of CSVD.

MRI techniques to measure arterial and venous cerebral blood volume

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.

Isotropically weighted intravoxel incoherent motion brain imaging at 7T

Perfusion magnetic resonance imaging (MRI) is a promising non-invasive technique providing insights regarding the brain's microvascular architecture in vivo. The scalar perfusion metrics can be used for quantitative diagnostics of various brain abnormalities, in particular, in the stroke cases and tumours. However, conventional MRI-based perfusion approaches such as dynamic contrast-enhanced perfusion imaging or arterial spin labelling have a few weaknesses, for instance, contrast agent deposition, low signal-to-noise ratio, limited temporal and spatial resolution, and specific absorption rate constraints. As an alternative, the intravoxel incoherent motion (IVIM) approach exploits an extension of diffusion MRI in order to estimate perfusion parameters in the human brain. Application of IVIM imaging at ultra-high field MRI might employ the advantage of a higher signal-to-noise ratio, and thereby the use of higher spatial and temporal resolutions. In the present work, we demonstrate an application of recently developed isotropic diffusion weighted sequences to the evaluation of IVIM parameters at an ultra-high 7T field. The used sequence exhibits high immunity to image degrading factors and allows one to acquire the data in a fast and efficient way. Utilising the bi-exponential fitting model of the signal attenuation, we performed an extensive analysis of the IVIM scalar metrics obtained by a isotropic diffusion weighted sequence in vivo and compared results with a conventional pulsed gradient sequence at 7T. In order to evaluate a possible metric bias originating from blood flows, we additionally used a truncated b-value protocol (b-values from 100 to 200 s/mm² with the step 20 s/mm²) accompanied to the full range (b-values from 0 to 200 s/mm²). The IVIM scalar metrics have been assessed and analysed together with a large and middle vessel density atlas of the human brain. We found that the diffusion coefficients and perfusion fractions of the voxels consisting of large and middle vessels have higher values in contrast to other tissues. Additionally, we did not find a strong dependence of the IVIM metrics on the density values of the vessel atlas. Perspectives and limitations of the developed isotropic diffusion weighted perfusion are presented and discussed.

Transverse NMR relaxation in biological tissues

Transverse NMR relaxation is a fundamental physical phenomenon underpinning a wide range of MRI-based techniques, essential for non-invasive studies in biology, physiology and neuroscience, as well as in diagnostic imaging. Biophysically, transverse relaxation originates from a number of distinct scales - molecular (nanometers), cellular (micrometers), and macroscopic (millimeter-level MRI resolution). Here we review the contributions to the observed relaxation from each of these scales, with the main focus on the cellular level of tissue organization, commensurate with the diffusion length of spin-carrying molecules. We discuss how the interplay between diffusion and spin dephasing in a spatially heterogeneous tissue environment leads to a non-monoexponential time-dependent transverse relaxation signal that contains important biophysical information about tissue microstructure.

Dosimetric evaluation of radionuclides for VCAM-1-targeted radionuclide therapy of early brain metastases

Brain metastases develop frequently in patients with breast cancer, and present a pressing therapeutic challenge. Expression of vascular cell adhesion molecule 1 (VCAM-1) is upregulated on brain endothelial cells during the early stages of metastasis and provides a target for the detection and treatment of early brain metastases. The aim of this study was to use a model of early brain metastasis to evaluate the efficacy of α-emitting radionuclides, 149Tb, 211At, 212Pb, 213Bi and 225Ac; β-emitting radionuclides, 90Y, 161Tb and 177Lu; and Auger electron (AE)-emitters 67Ga, 89Zr, 111In and 124I, for targeted radionuclide therapy (TRT).

METHODS

Histologic sections and two photon microscopy of mouse brain parenchyma were used to inform a cylindrical vessel geometry using the Geant4 general purpose Monte Carlo (MC) toolkit with the Geant4-DNA low energy physics models. Energy deposition was evaluated as a radial function and the resulting phase spaces were superimposed on a DNA model to estimate double-strand break (DSB) yields for representative β- and α-emitters, 177Lu and 212Pb. Relative biological effectiveness (RBE) values were determined by only evaluating DNA damage due to physical interactions.

RESULTS

177Lu produced 2.69 ± 0.08 DSB per GbpGy, without significant variation from the lumen of the vessel to a radius of 100 µm. The DSB yield of 212Pb included two local maxima produced by the 6.1 MeV and 8.8 MeV α-emissions from decay products, 212Bi and 212Po, with yields of 7.64 ± 0.12 and 9.15 ± 0.24 per GbpGy, respectively. Given its higher DSB yield 212Pb may be more effective for short range targeting of early micrometastatic lesions than 177Lu.

CONCLUSION

MC simulation of a model of early brain metastases provides invaluable insight into the potential efficacy of α-, β- and AE-emitting radionuclides for TRT. 212Pb, which has the attributes of a theranostic radionuclide since it can be used for SPECT imaging, showed a favorable dose profile and RBE.

Anisotropic cerebral vascular architecture causes orientation dependency in cerebral blood flow and volume measured with dynamic susceptibility contrast magnetic resonance imaging

Measurements of cerebral perfusion using dynamic susceptibility contrast magnetic resonance imaging rely on the assumption of isotropic vascular architecture. However, a considerable fraction of vessels runs in parallel with white matter tracts. Here, we investigate the effects of tissue orientation on dynamic susceptibility contrast magnetic resonance imaging. Tissue orientation was measured using diffusion tensor imaging and dynamic susceptibility contrast was performed with gradient echo planar imaging. Perfusion parameters and the raw dynamic susceptibility contrast signals were correlated with tissue orientation. Additionally, numerical simulations were performed for a range of vascular volumes of both the isotropic vascular bed and anisotropic vessel components, as well as for a range of contrast agent concentrations. The effect of the contrast agent was much larger in white matter tissue perpendicular to the main magnetic field compared to white matter parallel to the main magnetic field. In addition, cerebral blood flow and cerebral blood volume were affected in the same way with angle-dependent variations of up to 130%. Mean transit time and time to maximum of the residual curve exhibited weak orientation dependency of 10%. Numerical simulations agreed with the measured data, showing that one-third of the white matter vascular volume is comprised of vessels running in parallel with the fibre tracts.

Neuronal or hemodynamic? Grappling with the functional MRI signal

Magnetic resonance imaging (MRI) and functional MRI (fMRI) continue to advance because creative physicists, engineers, neuroscientists, clinicians, and physiologists find new ways for extracting more information from the signal. Innovations in pulse sequence design, paradigm design, and processing methods have advanced the field and firmly established fMRI as a cornerstone for understanding the human brain. In this article, the field of fMRI is described through consideration of the central problem of separating hemodynamic from neuronal information. Discussed here are examples of how pulse sequences, activation paradigms, and processing methods are integrated such that novel, high-quality information can be obtained. Examples include the extraction of information such as activation onset latency, metabolic rate, neuronal adaptation, vascular patency, vessel diameter, vigilance, and subvoxel activation. Experimental measures include time series latency, hemodynamic shape, MR phase, multivoxel patterns, ratios of activation-related R2* to R2, metabolic rate changes, fluctuation correlations and frequencies, changes in fluctuation correlations and frequencies over time, resting correlation states, echo time dependence, and more.

Does functional MRI detect activation in white matter? A review of emerging evidence, issues, and future directions

Functional magnetic resonance imaging (fMRI) is a non-invasive technique that allows for visualization of activated brain regions. Until recently, fMRI studies have focused on gray matter. There are two main reasons white matter fMRI remains controversial: (1) the blood oxygen level dependent (BOLD) fMRI signal depends on cerebral blood flow and volume, which are lower in white matter than gray matter and (2) fMRI signal has been associated with post-synaptic potentials (mainly localized in gray matter) as opposed to action potentials (the primary type of neural activity in white matter). Despite these observations, there is no direct evidence against measuring fMRI activation in white matter and reports of fMRI activation in white matter continue to increase. The questions underlying white matter fMRI activation are important. White matter fMRI activation has the potential to greatly expand the breadth of brain connectivity research, as well as improve the assessment and diagnosis of white matter and connectivity disorders. The current review provides an overview of the motivation to investigate white matter fMRI activation, as well as the published evidence of this phenomenon. We speculate on possible neurophysiologic bases of white matter fMRI signals, and discuss potential explanations for why reports of white matter fMRI activation are relatively scarce. We end with a discussion of future basic and clinical research directions in the study of white matter fMRI.

Multiple sclerosis: improved identification of disease-relevant changes in gray and white matter by using susceptibility-based MR imaging

PURPOSE

To evaluate the potential of quantitative susceptibility (QS) and R2* mapping as surrogate biomarkers of clinically relevant, age-adjusted demyelination and iron deposition in multiple sclerosis (MS).

MATERIALS AND METHODS

All study participants gave written informed consent, and the study was approved by the institutional review board. Quantitative maps of the magnetic resonance imaging susceptibility parameters (R2* and QS) were computed for 25 patients with either clinically isolated syndrome (CIS) or relapsing-remitting MS, as well as for 15 age- and sex-matched control subjects imaged at 7 T. The candidate MR imaging biomarkers were correlated with Extended Disability Status Scale (EDSS), time since CIS diagnosis, time since MS diagnosis, and age.

RESULTS

QS maps aided identification of significant, voxel-level increases in iron deposition in subcortical gray matter (GM) of patients with MS compared with control subjects. These voxel-level increases were not observed on R2* maps. Region-of-interest analysis of mean R2* and QS in subcortical GM demonstrated that R2* (R ≥ 0.39, P < .01) and QS (R ≥ 0.44, P < .01) were strongly correlated with EDSS. In white matter (WM), the volume of total WM damage (defined by a z score of less than -2.0 criterion, indicating demyelination) on QS maps correlated significantly with EDSS (R = 0.46, P = .02). Voxelwise QS also supported a significant contribution of age to demyelination in patients with MS, suggesting that age-adjusted clinical scores may provide more robust measures of MS disease severity compared with non-age-adjusted scores.

CONCLUSION

Using QS and R2* mapping, evidence of both significant increases in iron deposition in subcortical GM and myelin degeneration along the WM skeleton of patients with MS was identified. Both effects correlated strongly with EDSS.

Regional variations in vascular density correlate with resting-state and task-evoked blood oxygen level-dependent signal amplitude

Functional magnetic resonance imaging (fMRI) has become one of the primary tools used for noninvasively measuring brain activity in humans. For the most part, the blood oxygen level-dependent (BOLD) contrast is used, which reflects the changes in hemodynamics associated with active brain tissue. The main advantage of the BOLD signal is that it is relatively easy to measure and thus is often used as a proxy for comparing brain function across population groups (i.e., control vs. patient). However, it is particularly weighted toward veins whose structural architecture is known to vary considerably across the brain. This makes it difficult to interpret whether differences in BOLD between cortical areas reflect true differences in neural activity or vascular structure. We therefore investigated how regional variations of vascular density (VAD) relate to the amplitude of resting-state and task-evoked BOLD signals. To address this issue, we first developed an automated method for segmenting veins in images acquired with susceptibility-weighted imaging, allowing us to visualize the venous vascular tree across the brain. In 19 healthy subjects, we then applied voxel-based morphometry (VBM) to T1-weighted images and computed regional measures of gray matter density (GMD). We found that, independent of spatial scale, regional variations in resting-state and task-evoked fMRI amplitudes were better correlated to VAD compared to GMD. Using a general linear model (GLM), it was observed that the bulk of regional variance in resting-state activity could be modeled by VAD. Cortical areas whose resting-state activity was most suppressed by VAD correction included Cuneus, Precuneus, Culmen, and BA 9, 10, and 47. Taken together, our results suggest that resting-state BOLD signals are significantly related to the underlying structure of the brain vascular system. Calibrating resting BOLD activity by venous structure may result in a more accurate interpretation of differences observed between cortical areas and/or individuals.

MR vascular fingerprinting: A new approach to compute cerebral blood volume, mean vessel radius, and oxygenation maps in the human brain

In the present study, we describe a fingerprinting approach to analyze the time evolution of the MR signal and retrieve quantitative information about the microvascular network. We used a Gradient Echo Sampling of the Free Induction Decay and Spin Echo (GESFIDE) sequence and defined a fingerprint as the ratio of signals acquired pre- and post-injection of an iron-based contrast agent. We then simulated the same experiment with an advanced numerical tool that takes a virtual voxel containing blood vessels as input, then computes microscopic magnetic fields and water diffusion effects, and eventually derives the expected MR signal evolution. The parameter inputs of the simulations (cerebral blood volume [CBV], mean vessel radius [R], and blood oxygen saturation [SO2]) were varied to obtain a dictionary of all possible signal evolutions. The best fit between the observed fingerprint and the dictionary was then determined by using least square minimization. This approach was evaluated in 5 normal subjects and the results were compared to those obtained by using more conventional MR methods, steady-state contrast imaging for CBV and R and a global measure of oxygenation obtained from the superior sagittal sinus for SO2. The fingerprinting method enabled the creation of high-resolution parametric maps of the microvascular network showing expected contrast and fine details. Numerical values in gray matter (CBV=3.1±0.7%, R=12.6±2.4μm, SO2=59.5±4.7%) are consistent with literature reports and correlated with conventional MR approaches. SO2 values in white matter (53.0±4.0%) were slightly lower than expected. Numerous improvements can easily be made and the method should be useful to study brain pathologies.

The influence of noise on BOLD-mediated vessel size imaging analysis methods

Vessel size imaging (VSI) is a magnetic resonance imaging (MRI) technique that aims to provide quantitative measurements of tissue microvasculature. An emerging variation of this technique uses the blood oxygenation level-dependent (BOLD) effect as the source of the imaging contrast. Gas challenges have the advantage over contrast injection techniques in that they are noninvasive and easily repeatable because of the fast washout of the contrast. However, initial results from BOLD-VSI studies are somewhat contradictory, with substantially different estimates of the mean vessel radius. Owing to BOLD-VSI being an emerging technique, there is not yet a standard processing methodology, and different techniques have been used to calculate the mean vessel radius and reject uncertain estimates. In addition, the acquisition methodology and signal modeling vary from group to group. Owing to these differences, it is difficult to determine the source of this variation. Here we use computer modeling to assess the impact of noise on the accuracy and precision of different BOLD-VSI calculations. Our results show both potential overestimates and underestimates of the mean vessel radius, which is confirmed with a validation study at 3T.

High-resolution structural and functional assessments of cerebral microvasculature using 3D Gas ΔR2*-mMRA

The ability to evaluate the cerebral microvascular structure and function is crucial for investigating pathological processes in brain disorders. Previous angiographic methods based on blood oxygen level-dependent (BOLD) contrast offer appropriate visualization of the cerebral vasculature, but these methods remain to be optimized in order to extract more comprehensive information. This study aimed to integrate the advantages of BOLD MRI in both structural and functional vascular assessments. The BOLD contrast was manipulated by a carbogen challenge, and signal changes in gradient-echo images were computed to generate ΔR2* maps. Simultaneously, a functional index representing the regional cerebral blood volume was derived by normalizing the ΔR2* values of a given region to those of vein-filled voxels of the sinus. This method is named 3D gas ΔR2*-mMRA (microscopic MRA). The advantages of using 3D gas ΔR2*-mMRA to observe the microvasculature include the ability to distinguish air-tissue interfaces, a high vessel-to-tissue contrast, and not being affected by damage to the blood-brain barrier. A stroke model was used to demonstrate the ability of 3D gas ΔR2*-mMRA to provide information about poststroke revascularization at 3 days after reperfusion. However, this technique has some limitations that cannot be overcome and hence should be considered when it is applied, such as magnifying vessel sizes and predominantly revealing venous vessels.

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

SUMMARY

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

Dynamic hysteresis between gradient echo and spin echo attenuations in dynamic susceptibility contrast imaging

Perfusion measurements using dynamic susceptibility contrast imaging provide additional information about the mean vessel size of microvasculature when supplemented with a dual gradient echo (GE) - spin echo (SE) contrast. Dynamic increase in the corresponding transverse relaxation rate constant changes, ΔR2GE and ΔR2SE , forms a loop on the (Δ R2SE3/2, ΔR2GE ) plane, rather than a reversible line. The shape of the loop and the direction of its passage differentiate between healthy brain and pathological tissue, such as tumour and ischemic tissue. By considering a tree model of microvasculature, the direction of the loop is found to be influenced mainly by the relative arterial and venous blood volume, as well as the tracer bolus dispersion. A parameter Λ is proposed to characterize the direction and shape of the loop, which might be considered as a novel imaging marker for describing the pathology of cerebrovascular network.

Vascular component analysis of hyperoxic and hypercapnic BOLD contrast

Hyperoxia or hypercapnia provides a useful experimental tool to systematically alter the blood oxygenation level dependent (BOLD) contrast. Typical applications include calibrated functional magnetic resonance imaging (fMRI), BOLD sensitivity mapping, vessel size imaging or cerebrovascular reactivity mapping. This article describes a novel biophysical model of hyperoxic and hypercapnic BOLD contrast, which accounts for the magnetic susceptibility effects of molecular oxygen that is dissolved in blood and tissue, in addition to the well-established effects caused by the paramagnetic properties of deoxyhaemoglobin. Furthermore, the concept of vascular component analysis (VCA) is introduced and is shown to provide a computationally efficient tool for investigating the vascular specificity of hyperoxic and hypercapnic BOLD contrast. A theoretical investigation of gradient and spin echo BOLD contrast based on computer simulations was performed to compare three different conditions (hypercapnia induced by breathing 6% CO2, hyperoxia induced by breathing 100% O2, and simultaneous hypercapnia and hyperoxia induced by breathing carbogen, i.e. 5% CO2 in 95% CO2) with baseline (breathing air). Simulations were carried out for different levels of metabolic oxygen extraction fraction (OEF) ranging from 0 to 0.5. The key findings can be summarised as follows: (i) for hyperoxia the susceptibility of dissolved O2 may lead to a significant arterial BOLD contrast; (ii) under normoxic conditions the susceptibility of dissolved O2 is negligible; (iii) an almost complete loss of BOLD sensitivity may occur at lower OEF values in all parts of the vascular tree, whereas hyperoxic BOLD sensitivity is largely maintained; (iv) under hyperoxic conditions, a transition from positive to negative BOLD contrast occurs with decreasing OEF values. These findings have important implications for experimental applications of hyperoxic and hypercapnic BOLD contrast and may enable new clinical applications in ischemic stroke and other forms of acquired brain injury.

Vessel size imaging reveals pathological changes of microvessel density and size in acute ischemia

The aim of this study was to test the feasibility of vessel size imaging with precise evaluation of apparent diffusion coefficient and cerebral blood volume and to apply this novel technique in acute stroke patients within a pilot group to observe the microvascular responses in acute ischemic tissue. Microvessel density-related quantity Q and mean vessel size index (VSI) were assessed in 9 healthy volunteers and 13 acute stroke patients with vessel occlusion within 6 hours after symptom onset. Our results in healthy volunteers matched with general anatomical observations. Given the limitation of a small patient cohort, the median VSI in the ischemic area was higher than that in the mirrored region in the contralateral hemisphere (P<0.05). Decreased Q was observed in the ischemic region in 2 patients, whereas no obvious changes of Q were found in the remaining 11 patients. In a patient without recanalization, the VSI hyperintensity in the subcortical area matched well with the final infarct. These data reveal that different observations of microvascular response in the acute ischemic tissue seem to emerge and vessel size imaging may provide useful information for the definition of ischemic penumbra and have an impact on future therapeutic approaches.

Magnetic resonance imaging of the mean venous vessel size in the human brain using transient hyperoxia

Vessel size imaging is an emerging magnetic resonance imaging (MRI) technique which has been demonstrated to provide clinically relevant information about microvascular morphology. While previous studies of vessel size in humans relied on MRI contrast agents or hypercapnia-induced changes in blood oxygenation, the technique described here uses transient hyperoxia to alter the venous blood oxygenation. The experimental paradigm consisted of two 3-minute intervals of breathing 100% O(2) interleaved with three 2-minute intervals of breathing room air. Parametric maps of the mean venous vessel radius were calculated from changes in the blood oxygenation level dependent (BOLD) contrast which were measured using a combined spin-echo (SE) and gradient echo (GE) echo-planar imaging (EPI) sequence. The corresponding mean values in grey and white matter were r=6.5±0.3 μm and r=6.2±0.3 μm (n=6). While the hypercapnia technique requires a specialised gas mixture containing a low concentration of CO(2) (typically 5-6%), the hyperoxia technique presented here uses the inhalation of medical oxygen (100% O(2)) which is routinely available in a clinical environment. Furthermore, 100% O(2) is generally better tolerated than low doses of CO(2) which makes this technique particularly suitable for applications in critically ill patients.