Gas-free calibrated fMRI with a correction for vessel-size sensitivity

Predicting the macrovascular contribution to resting-state fMRI functional connectivity at 3 Tesla: A model-informed approach

Macrovascular biases have been a long-standing challenge for fMRI, limiting its ability to detect spatially specific neural activity. Recent experimental studies, including our own (Huck et al., 2023; Zhong et al., 2023), found substantial resting-state macrovascular BOLD fMRI contributions from large veins and arteries, extending into the perivascular tissue at 3 T and 7 T. The objective of this study is to demonstrate the feasibility of predicting, using a biophysical model, the experimental resting-state BOLD fluctuation amplitude (RSFA) and associated functional connectivity (FC) values at 3 Tesla. We investigated the feasibility of both 2D and 3D infinite-cylinder models as well as macrovascular anatomical networks (mVANs) derived from angiograms. Our results demonstrate that: 1) with the availability of mVANs, it is feasible to model macrovascular BOLD FC using both the mVAN-based model and 3D infinite-cylinder models, though the former performed better; 2) biophysical modelling can accurately predict the BOLD pairwise correlation near to large veins (with R 2 ranging from 0.53 to 0.93 across different subjects), but not near to large arteries; 3) compared with FC, biophysical modelling provided less accurate predictions for RSFA; 4) modelling of perivascular BOLD connectivity was feasible at close distances from veins (with R 2 ranging from 0.08 to 0.57), but not arteries, with performance deteriorating with increasing distance. While our current study demonstrates the feasibility of simulating macrovascular BOLD in the resting state, our methodology may also apply to understanding task-based BOLD. Furthermore, these results suggest the possibility of correcting for macrovascular bias in resting-state fMRI and other types of fMRI using biophysical modelling based on vascular anatomy.

MRI-Based Assessment of Brain Tumor Hypoxia: Correlation with Histology

Cerebral hypoxia significantly impacts the progression of brain tumors and their resistance to radiotherapy. This study employed streamlined quantitative blood-oxygen-level-dependent (sqBOLD) MRI to assess the oxygen extraction fraction (OEF)-a measure of how much oxygen is being extracted from vessels, with higher OEF values indicating hypoxia. Simultaneously, we utilized vessel size imaging (VSI) to evaluate microvascular dimensions and blood volume. A cohort of ten patients, divided between those with glioma and those with brain metastases, underwent a 3 Tesla MRI scan. We generated OEF, cerebral blood volume (CBV), and vessel size maps, which guided 3-4 targeted biopsies per patient. Subsequent histological analyses of these biopsies used hypoxia-inducible factor 1-alpha (HIF-1α) for hypoxia and CD31 for microvasculature assessment, followed by a correlation analysis between MRI and histological data. The results showed that while the sqBOLD model was generally applicable to brain tumors, it demonstrated discrepancies in some metastatic tumors, highlighting the need for model adjustments in these cases. The OEF, CBV, and vessel size maps provided insights into the tumor's hypoxic condition, showing intertumoral and intratumoral heterogeneity. A significant relationship between MRI-derived measurements and histological data was only evident in the vessel size measurements (r = 0.68, p < 0.001).

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Spatiotemporal features of neurovascular (un)coupling with stimulus-induced activity and hypercapnia challenge in cerebral cortex and olfactory bulb

Carbon dioxide (CO2) is traditionally considered as metabolic waste, yet its regulation is critical for brain function. It is well accepted that hypercapnia initiates vasodilation, but its effect on neuronal activity is less clear. Distinguishing how stimulus- and CO2-induced vasodilatory responses are (dis)associated with neuronal activity has profound clinical and experimental relevance. We used an optical method in mice to simultaneously image fluorescent calcium (Ca2+) transients from neurons and reflectometric hemodynamic signals during brief sensory stimuli (i.e., hindpaw, odor) and CO2 exposure (i.e., 5%). Stimuli-induced neuronal and hemodynamic responses swiftly increased within locally activated regions exhibiting robust neurovascular coupling. However, hypercapnia produced slower global vasodilation which was temporally uncoupled to neuronal deactivation. With trends consistent across cerebral cortex and olfactory bulb as well as data from GCaMP6f/jRGECO1a mice (i.e., green/red Ca2+ fluorescence), these results unequivocally reveal that stimuli and CO2 generate comparable vasodilatory responses but contrasting neuronal responses. In summary, observations of stimuli-induced regional neurovascular coupling and CO2-induced global neurovascular uncoupling call for careful appraisal when using CO2 in gas mixtures to affect vascular tone and/or neuronal excitability, because CO2 is both a potent vasomodulator and a neuromodulator.

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

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

High-resolution relaxometry-based calibrated fMRI in murine brain: Metabolic differences between awake and anesthetized states

Functional magnetic resonance imaging (fMRI) techniques using the blood-oxygen level-dependent (BOLD) signal have shown great potential as clinical biomarkers of disease. Thus, using these techniques in preclinical rodent models is an urgent need. Calibrated fMRI is a promising technique that can provide high-resolution mapping of cerebral oxygen metabolism (CMR_O2). However, calibrated fMRI is difficult to use in rodent models for several reasons: rodents are anesthetized, stimulation-induced changes are small, and gas challenges induce noisy CMR_O2 predictions. We used, in mice, a relaxometry-based calibrated fMRI method which uses cerebral blood flow (CBF) and the BOLD-sensitive magnetic relaxation component, R₂', the same parameter derived in the deoxyhemoglobin-dilution model of calibrated fMRI. This method does not use any gas challenges, which we tested on mice in both awake and anesthetized states. As anesthesia induces a whole-brain change, our protocol allowed us to overcome the former limitations of rodent studies using calibrated fMRI. We revealed 1.5-2 times higher CMR_O2, dependent upon brain region, in the awake state versus the anesthetized state. Our results agree with alternative measurements of whole-brain CMR_O2 in the same mice and previous human anesthesia studies. The use of calibrated fMRI in rodents has much potential for preclinical fMRI.

Cerebrovascular Reactivity Across the Entire Brain in Cerebral Amyloid Angiopathy

Background and Objectives

Reduced cerebrovascular reactivity is proposed to be a feature of cerebral amyloid angiopathy (CAA) but has not been measured directly. Employing a global vasodilatory stimulus (hypercapnia), this study assessed the relationships between cerebrovascular reactivity and MRI markers of CAA and cognitive function.

Methods

In a cross-sectional study, individuals with probable CAA, mild cognitive impairment, or dementia due to Alzheimer disease and healthy controls underwent neuropsychological testing and an MRI that included a 5% carbon dioxide challenge. Cerebrovascular reactivity was compared across groups controlling for age, sex, and the presence of hypertension, and its associations with MRI markers of CAA in participants with CAA and with cognition across all participants were determined using multivariable linear regression adjusting for group, age, sex, education, and the presence of hypertension.

Results

Cerebrovascular reactivity data (mean ± SD) were available for 26 participants with CAA (9 female; 74.4 ± 7.7 years), 19 participants with mild cognitive impairment (5 female; 72.1 ± 8.5 years), 12 participants with dementia due to Alzheimer disease (4 female; 69.4 ± 6.6 years), and 39 healthy controls (30 female; 68.8 ± 5.4 years). Gray and whiter matter reactivity averaged across the entire brain was lower in participants with CAA and Alzheimer disease dementia compared to healthy controls, with a predominantly posterior distribution of lower reactivity in both groups. Higher white matter hyperintensity volume was associated with lower white matter reactivity (standardized coefficient [β], 95% CI −0.48, −0.90 to −0.01). Higher gray matter reactivity was associated with better global cognitive function (β 0.19, 0.03–0.36), memory (β 0.21, 0.07–0.36), executive function (β 0.20, 0.02–0.39), and processing speed (β 0.27, 0.10–0.45) and higher white matter reactivity was associated with higher memory (β 0.22, 0.08–0.36) and processing speed (β 0.23, 0.06–0.40).

Conclusions

Reduced cerebrovascular reactivity is a core feature of CAA and its assessment may provide an additional biomarker for disease severity and cognitive impairment.

Imaging faster neural dynamics with fast fMRI: A need for updated models of the hemodynamic response

Fast fMRI enables the detection of neural dynamics over timescales of hundreds of milliseconds, suggesting it may provide a new avenue for studying subsecond neural processes in the human brain. The magnitudes of these fast fMRI dynamics are far greater than predicted by canonical models of the hemodynamic response. Several studies have established nonlinear properties of the hemodynamic response that have significant implications for fast fMRI. We first review nonlinear properties of the hemodynamic response function that may underlie fast fMRI signals. We then illustrate the breakdown of canonical hemodynamic response models in the context of fast neural dynamics. We will then argue that the canonical hemodynamic response function is not likely to reflect the BOLD response to neuronal activity driven by sparse or naturalistic stimuli or perhaps to spontaneous neuronal fluctuations in the resting state. These properties suggest that fast fMRI is capable of tracking surprisingly fast neuronal dynamics, and we discuss the neuroscientific questions that could be addressed using this approach.

Age-related differences in cerebral blood flow and cortical thickness with an application to age prediction

Cerebral cortex thinning and cerebral blood flow (CBF) reduction are typically observed during normal healthy aging. However, imaging-based age prediction models have primarily used morphological features of the brain. Complementary physiological CBF information might result in an improvement in age estimation. In this study, T1-weighted structural magnetic resonance imaging and arterial spin labeling CBF images were acquired in 146 healthy participants across the adult life span. Sixty-eight cerebral cortex regions were segmented, and the cortical thickness and mean CBF were computed for each region. Linear regression with age was computed for each region and data type, and laterality and correlation matrices were computed. Sixteen predictive models were trained with the cortical thickness and CBF data alone as well as a combination of both data types. The age explained more variance in the cortical thickness data (average R² of 0.21) than in the CBF data (average R² of 0.09). All 16 models performed significantly better when combining both measurement types and using feature selection, and thus, we conclude that the inclusion of CBF data marginally improves age estimation.

Calibrated fMRI for dynamic mapping of CMRO2 responses using MR-based measurements of whole-brain venous oxygen saturation

Functional MRI (fMRI) can identify active foci in response to stimuli through BOLD signal fluctuations, which represent a complex interplay between blood flow and cerebral metabolic rate of oxygen (CMRO₂) changes. Calibrated fMRI can disentangle the underlying contributions, allowing quantification of the CMRO₂ response. Here, whole-brain venous oxygen saturation (Y_v) was computed alongside ASL-measured CBF and BOLD-weighted data to derive the calibration constant, M, using the proposed Y_v-based calibration. Data were collected from 10 subjects at 3T with a three-part interleaved sequence comprising background-suppressed 3D-pCASL, 2D BOLD-weighted, and single-slice dual-echo GRE (to measure Y_v via susceptometry-based oximetry) acquisitions while subjects breathed normocapnic/normoxic, hyperoxic, and hypercapnic gases, and during a motor task. M was computed via Y_v-based calibration from both hypercapnia and hyperoxia stimulus data, and results were compared to conventional hypercapnia or hyperoxia calibration methods. Mean M in gray matter did not significantly differ between calibration methods, ranging from 8.5 ± 2.8% (conventional hyperoxia calibration) to 11.7 ± 4.5% (Y_v-based calibration in response to hyperoxia), with hypercapnia-based M values between (p = 0.56). Relative CMRO₂ changes from finger tapping were computed from each M map. CMRO₂ increased by ∼20% in the motor cortex, and good agreement was observed between the conventional and proposed calibration methods.

Oxygen extraction fraction mapping with multi-parametric quantitative BOLD MRI: Reduced transverse relaxation bias using 3D-GraSE imaging

Magnetic resonance imaging (MRI)-based quantification of the blood-oxygenation-level-dependent (BOLD) effect allows oxygen extraction fraction (OEF) mapping. The multi-parametric quantitative BOLD (mq-BOLD) technique facilitates relative OEF (rOEF) measurements with whole brain coverage in clinically applicable scan times. Mq-BOLD requires three separate scans of cerebral blood volume and transverse relaxation rates measured by gradient-echo (1/T₂*) and spin-echo (1/T₂). Although the current method is of clinical merit in patients with stroke, glioma and internal carotid artery stenosis (ICAS), there are relaxation measurement artefacts that impede the sensitivity of mq-BOLD and artificially elevate reported rOEF values.

We posited that T₂-related biases caused by slice refocusing imperfections during rapid 2D-GraSE (Gradient and Spin Echo) imaging can be reduced by applying 3D-GraSE imaging sequences, because the latter requires no slice selective pulses. The removal of T₂-related biases would decrease overestimated rOEF values measured by mq-BOLD. We characterized effects of T₂-related bias in mq-BOLD by comparing the initially employed 2D-GraSE and two proposed 3D-GraSE sequences to multiple single spin-echo reference measurements, both in vitro and in vivo. A phantom and 25 participants, including young and elderly healthy controls as well as ICAS-patients, were scanned. We additionally proposed a procedure to reliably identify and exclude artefact affected voxels. In the phantom, 3D-GraSE derived T₂ values had 57% lower deviation from the reference. For in vivo scans, the formerly overestimated rOEF was reduced by −27% (p < 0.001). We obtained rOEF = 0.51, which is much closer to literature values from positron emission tomography (PET) measurements. Furthermore, increased sensitivity to a focal rOEF elevation in an ICAS-patient was demonstrated.

In summary, the application of 3D-GraSE improves the mq-BOLD-based rOEF quantification while maintaining clinically feasible scan times. Thus, mq-BOLD with non-slice selective T₂ imaging is highly promising to improve clinical diagnostics of cerebrovascular diseases such as ICAS.

Model-based Bayesian inference of brain oxygenation using quantitative BOLD

Streamlined Quantitative BOLD (sqBOLD) is an MR technique that can non-invasively measure physiological parameters including Oxygen Extraction Fraction (OEF) and deoxygenated blood volume (DBV) in the brain. Current sqBOLD methodology rely on fitting a linear model to log-transformed data acquired using an Asymmetric Spin Echo (ASE) pulse sequence. In this paper, a non-linear model implemented in a Bayesian framework was used to fit physiological parameters to ASE data. This model makes use of the full range of available ASE data, and incorporates the signal contribution from venous blood, which was ignored in previous analyses. Simulated data are used to demonstrate the intrinsic difficulty in estimating OEF and DBV simultaneously, and the benefits of the proposed non-linear model are shown. In vivo data are used to show that this model improves parameter estimation when compared with literature values. The model and analysis framework can be extended in a number of ways, and can incorporate prior information from external sources, so it has the potential to further improve OEF estimation using sqBOLD.

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

Quantitative BOLD (qBOLD) is a technique for mapping oxygen extraction fraction (OEF) and deoxygenated blood volume (DBV) in the human brain. Recent measurements using an asymmetric spin echo (ASE) based qBOLD approach produced estimates of DBV which were systematically higher than measurements from other techniques. In this study, we investigate two hypotheses for the origin of this DBV overestimation using simulations and consider the implications for experimental measurements. Investigations were performed by combining Monte Carlo simulations of extravascular signal with an analytical model of the intravascular signal. HYPOTHESIS 1: DBV overestimation is due to the presence of intravascular signal which is not accounted for in the analysis model. Intravascular signal was found to have a weak effect on qBOLD parameter estimates. HYPOTHESIS 2: DBV overestimation is due to the effects of diffusion which are not accounted for in the analysis model. The effect of diffusion on the extravascular signal was found to result in a vessel radius dependent variation in qBOLD parameter estimates. In particular, DBV overestimation peaks for vessels with radii from 20 to 30 μm and is OEF dependent. This results in the systematic underestimation of OEF. IMPLICATIONS: The impact on experimental qBOLD measurements was investigated by simulating a more physiologically realistic distribution of vessel sizes with a small number of discrete radii. Overestimation of DBV consistent with previous experiments was observed, which was also found to be OEF dependent. This results in the progressive underestimation of the measured OEF. Furthermore, the relationship between the measured OEF and the true OEF was found to be dependent on echo time and spin echo displacement time. The results of this study demonstrate the limitations of current ASE based qBOLD measurements and provide a foundation for the optimisation of future acquisition approaches.