Assessing the repeatability of absolute CMRO2, OEF and haemodynamic measurements from calibrated fMRI

Small animal PET with spontaneous inhalation of 15O-labelled oxygen gases: Longitudinal assessment of cerebral oxygen metabolism in a rat model of neonatal hypoxic-ischaemic encephalopathy

Perinatal hypoxic-ischaemic encephalopathy (HIE) is the leading cause of irreversible brain damage resulting in serious neurological dysfunction among neonates. We evaluated the feasibility of positron emission tomography (PET) methodology with 15O-labelled gases without intravenous or tracheal cannulation for assessing temporal changes in cerebral blood flow (CBF) and cerebral metabolic rate for oxygen (CMRO2) in a neonatal HIE rat model. Sequential PET scans with spontaneous inhalation of 15O-gases mixed with isoflurane were performed over 14 days after the hypoxic-ischaemic insult in HIE pups and age-matched controls. CBF and CMRO2 in the injured hemispheres of HIE pups remarkably decreased 2 days after the insult, gradually recovering over 14 days in line with their increase found in healthy controls according to their natural maturation process. The magnitude of hemispheric tissue loss histologically measured after the last PET scan was significantly correlated with the decreases in CBF and CMRO2.This fully non-invasive imaging strategy may be useful for monitoring damage progression in neonatal HIE and for evaluating potential therapeutic outcomes.

Cerebrovascular reactivity measurements using 3T BOLD MRI and a fixed inhaled CO2 gas challenge: Repeatability and impact of processing strategy

Introduction: Cerebrovascular reactivity (CVR) measurements using blood oxygen level dependent (BOLD) magnetic resonance imaging (MRI) are commonly used to assess the health of cerebral blood vessels, including in patients with cerebrovascular diseases; however, evidence and consensus regarding reliability and optimal processing are lacking. We aimed to assess the repeatability, accuracy and precision of voxel- and region-based CVR measurements at 3 T using a fixed inhaled (FI) CO₂ stimulus in a healthy cohort. Methods: We simulated the effect of noise, delay constraints and voxel- versus region-based analysis on CVR parameters. Results were verified in 15 healthy volunteers (28.1±5.5 years, female: 53%) with a test-retest MRI experiment consisting of two CVR scans. CVR magnitude and delay in grey matter (GM) and white matter were computed for both analyses assuming a linear relationship between the BOLD signal and time-shifted end-tidal CO₂ (EtCO₂) profile. Results: Test-retest repeatability was high [mean (95% CI) inter-scan difference: -0.01 (-0.03, -0.00) %/mmHg for GM CVR magnitude; -0.3 (-1.2,0.6) s for GM CVR delay], but we detected a small systematic reduction in CVR magnitude at scan 2 versus scan 1, accompanied by a greater EtCO2 change [±1.0 (0.4,1.5) mmHg] and lower heart rate [-5.5 (-8.6,-2.4] bpm]. CVR magnitude estimates were higher for voxel- versus region-based analysis [difference in GM: ±0.02 (0.01,0.03) %/mmHg]. Findings were supported by simulation results, predicting a positive bias for voxel-based CVR estimates dependent on temporal contrast-to-noise ratio and delay fitting constraints and an underestimation for region-based CVR estimates. Discussion: BOLD CVR measurements using FI stimulus have good within-day repeatability in healthy volunteers. However, measurements may be influenced by physiological effects and the analysis protocol. Voxel-based analyses should be undertaken with care due to potential for systematic bias; region-based analyses are more reliable in such cases.

Reduced brain oxygen metabolism in patients with multiple sclerosis: Evidence from dual-calibrated functional MRI

Cerebral energy deficiency is increasingly recognised as an important feature of multiple sclerosis (MS). Until now, we have lacked non-invasive imaging methods to quantify energy utilisation and mitochondrial function in the human brain. Here, we used novel dual-calibrated functional magnetic resonance imaging (dc-fMRI) to map grey-matter (GM) deoxy-haemoglobin sensitive cerebral blood volume (CBVdHb), cerebral blood flow (CBF), oxygen extraction fraction (OEF), and cerebral metabolic rate of oxygen consumption (CMRO2) in patients with MS (PwMS) and age/sex matched controls. By integrating a flow-diffusion model of oxygen transport, we evaluated the effective oxygen diffusivity of the capillary network (DC) and the partial pressure of oxygen at the mitochondria (PmO2). Significant between-group differences were observed as decreased CBF (p = 0.010), CMRO2 (p < 0.001) and DC (p = 0.002), and increased PmO2 (p = 0.043) in patients compared to controls. No significant differences were observed for CBVdHb (p = 0.389), OEF (p = 0.358), or GM volume (p = 0.302). Regional analysis showed widespread reductions in CMRO2 and DC for PwMS. Our findings may be indicative of reduced oxygen demand or utilisation in the MS brain and mitochondrial dysfunction. Our results suggest changes in brain physiology may precede MRI-detectable GM loss and may contribute to disease progression and neurodegeneration.

A flow-diffusion model of oxygen transport for quantitative mapping of cerebral metabolic rate of oxygen (CMRO2) with single gas calibrated fMRI

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, P_mO₂, 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 P_mO₂), 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.

Cerebral oxygen extraction fraction MRI: Techniques and applications

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

A non-invasive reference-based method for imaging the cerebral metabolic rate of oxygen by PET/MR: theory and error analysis

Positron emission tomography (PET) remains the gold standard for quantitative imaging of the cerebral metabolic rate of oxygen (CMRO₂); however, it is an invasive and complex procedure that requires accounting for recirculating [¹⁵O]H₂O (RW) and the cerebral blood volume (CBV). This study presents a non-invasive reference-based technique for imaging CMRO₂ that was developed for PET/magnetic resonance imaging (MRI) with the goal of simplifying the PET procedure while maintaining its ability to quantify metabolism. The approach is to use whole-brain (WB) measurements of oxygen extraction fraction (OEF) and cerebral blood flow (CBF) to calibrate [¹⁵O]O₂-PET data, thereby avoiding the need for invasive arterial sampling. Here we present the theoretical framework, along with error analyses, sensitivity to PET noise and inaccuracies in input parameters, and initial assessment on PET data acquired from healthy participants. Simulations showed that neglecting RW and CBV corrections caused errors in CMRO₂ of less than ±10% for changes in regional OEF of ±25%. These predictions were supported by applying the reference-based approach to PET data, which resulted in remarkably similar CMRO₂ images to those generated by analyzing the same data using a modeling approach that incorporated the arterial input functions and corrected for CBV contributions. Significant correlations were observed between regional CMRO₂ values from the two techniques (slope = 1.00 ± 0.04, R ² > 0.98) with no significant differences found for integration times of 3 and 5 min. In summary, results demonstrate the feasibility of producing quantitative CMRO₂ images by PET/MRI without the need for invasive blood sampling.

Cerebrovascular Reactivity Measurement Using Magnetic Resonance Imaging: A Systematic Review

Cerebrovascular reactivity (CVR) magnetic resonance imaging (MRI) probes cerebral haemodynamic changes in response to a vasodilatory stimulus. CVR closely relates to the health of the vasculature and is therefore a key parameter for studying cerebrovascular diseases such as stroke, small vessel disease and dementias. MRI allows in vivo measurement of CVR but several different methods have been presented in the literature, differing in pulse sequence, hardware requirements, stimulus and image processing technique. We systematically reviewed publications measuring CVR using MRI up to June 2020, identifying 235 relevant papers. We summarised the acquisition methods, experimental parameters, hardware and CVR quantification approaches used, clinical populations investigated, and corresponding summary CVR measures. CVR was investigated in many pathologies such as steno-occlusive diseases, dementia and small vessel disease and is generally lower in patients than in healthy controls. Blood oxygen level dependent (BOLD) acquisitions with fixed inspired CO₂ gas or end-tidal CO₂ forcing stimulus are the most commonly used methods. General linear modelling of the MRI signal with end-tidal CO₂ as the regressor is the most frequently used method to compute CVR. Our survey of CVR measurement approaches and applications will help researchers to identify good practice and provide objective information to inform the development of future consensus recommendations.

Cardiorespiratory fitness is associated with increased middle cerebral arterial compliance and decreased cerebral blood flow in young healthy adults: A pulsed ASL MRI study

Cardiorespiratory fitness is thought to have beneficial effects on systemic vascular health, in part, by decreasing arterial stiffness. However, in the absence of non-invasive methods, it remains unknown whether this effect extends to the cerebrovasculature. The present study uses a novel pulsed arterial spin labelling (pASL) technique to explore the relationship between cardiorespiratory fitness and arterial compliance of the middle cerebral arteries (MCAC). Other markers of cerebrovascular health, including resting cerebral blood flow (CBF) and cerebrovascular reactivity to CO2 (CVRCO2) were also investigated. Eleven healthy males aged 21 ± 2 years with varying levels of cardiorespiratory fitness (maximal oxygen uptake (V · O2MAX) 38-76 ml/min/kg) underwent MRI scanning at 3 Tesla. Higher V · O2MAX was associated with greater MCAC (R2 = 0.64, p < 0.01) and lower resting grey matter CBF (R2 = 0.75, p < 0.01). However, V · O2MAX was not predictive of global grey matter BOLD-based CVR (R2 = 0.47, p = 0.17) or CBF-based CVR (R2 = 0.19, p = 0.21). The current experiment builds upon the established benefits of exercise on arterial compliance in the systemic vasculature, by showing that increased cardiorespiratory fitness is associated with greater cerebral arterial compliance in early adulthood.

Changes in volumetric and metabolic parameters relate to differences in exposure to sub-concussive head impacts

Structural and calibrated magnetic resonance imaging data were acquired on 44 collegiate football players prior to the season (PRE), following the first four weeks in-season (PTC) and one month after the last game (POST). Exposure data collected from g-Force accelerometers mounted to the helmet of each player were used to split participants into HIGH (N = 22) and LOW (N = 22) exposure groups, based on the frequency of impacts sustained by each athlete. Significant decreases in grey-matter volume specific to the HIGH group were documented at POST (P = 0.009), compared to baseline. Changes in resting cerebral blood flow (CBF0), corrected for partial volume effects, were observed within the HIGH group, throughout the season (P < 0.0001), suggesting that alterations in perfusion may follow exposure to sub-concussive collisions. Co-localized significant increases in cerebral metabolic rate of oxygen consumption (CMRO2|0) mid-season were also documented in the HIGH group, with respect to both PRE- and POST values. No physiological changes were observed in the LOW group. Therefore, cerebral metabolic demand may be elevated in players with greater exposure to head impacts. These results provide novel insight into the effects of sub-concussive collisions on brain structure and cerebrovascular physiology and emphasize the importance of multi-modal imaging for a complete characterization of cerebral health.

Cerebral oxygen metabolism in adults with sickle cell disease

In sickle cell disease (SCD), oxygen delivery is impaired due to anemia, especially during times of increased metabolic demand, and cerebral blood flow (CBF) must increase to meet changing physiologic needs. But hyperemia limits cerebrovascular reserve (CVR) and ischemic risk prevails despite elevated CBF. The cerebral metabolic rate of oxygen (CMRO₂ ) directly reflects oxygen supply and consumption and may therefore be more insightful than flow-based CVR measures for ischemic risk in SCD. We hypothesized that adults with SCD have impaired CMRO₂ at rest and that a vasodilatory challenge with acetazolamide would improve CMRO₂ . CMRO₂ was calculated from CBF and oxygen extraction fraction (OEF), measured with arterial spin labeling and T₂ -prepared tissue relaxation with inversion recovery (T₂ -TRIR) MRI. We studied 36 adults with SCD without a clinical history of overt stroke, and nine healthy controls. As expected, CBF was higher in patients with SCD versus controls (mean ± SD: 74 ± 16 versus 46 ± 5 mL/100 g/min, P < .001), resulting in similar oxygen delivery (SCD: 377 ± 67 versus controls: 368 ± 42 μmol O₂ /100g/min, P = .69). OEF was lower in patients versus controls (27 ± 4 versus 35 ± 4%, P < .001), resulting in lower CMRO₂ in patients versus controls (102 ± 24 versus 127 ± 20 μmol O₂ /100g/min, P = .002). After acetazolamide, CMRO₂ declined further in patients (P < .01) and did not decline significantly in controls (P = .78), indicating that forcing higher CBF worsened oxygen utilization in SCD patients. This lower CMRO₂ could reflect variation between healthy and unhealthy vascular beds in terms of dilatory capacity and resistance whereby dysfunctional vessels become more oxygen-deprived, hence increasing the risk of localized ischemia.

A frequency-domain machine learning method for dual-calibrated fMRI mapping of oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen consumption (CMRO2)

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.

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

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

Detecting resting-state brain activity using OEF-weighted imaging

Traditional resting-state functional magnetic resonance imaging (fMRI) is mainly based on the blood oxygenation level-dependent (BOLD) contrast. The oxygen extraction fraction (OEF) represents an important parameter of brain metabolism and is a key biomarker of tissue viability, detecting the ratio of oxygen utilization to oxygen delivery. Investigating spontaneous fluctuations in the OEF-weighted signal is crucial for understanding the underlying mechanism of brain activity because of the immense energy budget during the resting state. However, due to the poor temporal resolution of OEF mapping, no studies have reported using OEF contrast to assess resting-state brain activity. In this fMRI study, we recorded brain OEF-weighted fluctuations for 10 min in healthy volunteers across two scanning visits, using our recently developed pulse sequence that can acquire whole-brain voxel-wise OEF-weighted signals with a temporal resolution of 3 s. Using both group-independent component analysis and seed-based functional connectivity analysis, we robustly identified intrinsic brain networks, including the medial visual, lateral visual, auditory, default mode and bilateral executive control networks, using OEF contrast. Furthermore, we investigated the resting-state local characteristics of brain activity based on OEF-weighted signals using regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFF). We demonstrated that the gray matter regions of the brain, especially those in the default mode network, showed higher ReHo and fALFF values with the OEF contrast. Moreover, voxel-wise test-retest reliability comparisons across the whole brain demonstrated that the reliability of resting-state brain activity based on the OEF contrast was moderate for the network indices and high for the local activity indices, especially for ReHo. Although the reliabilities of the OEF-based indices were generally lower than those based on BOLD, the reliability of OEF-ReHo was slightly higher than that of BOLD-ReHo, with a small effect size, which indicated that OEF-ReHo could be used as a reliable index for characterizing resting-state local brain activity as a complement to BOLD. In conclusion, OEF can be used as an effective contrast to study resting-state brain activity with a medium to high test-retest reliability.