Uniform distributions of glucose oxidation and oxygen extraction in gray matter of normal human brain: No evidence of regional differences of aerobic glycolysis

Evidence for biexponential glutamate T2 relaxation in human visual cortex at 3T: A functional MRS study

Functional magnetic resonance spectroscopy (fMRS) measures dynamic changes in metabolite concentration in response to neural stimulation. The biophysical basis of these changes remains unclear. One hypothesis suggests that an increase or decrease in the glutamate signal detected by fMRS could be due to neurotransmitter movements between cellular compartments with different T2 relaxation times. Previous studies reporting glutamate (Glu) T2 values have generally sampled at echo times (TEs) within the range of 30-450 ms, which is not adequate to observe a component with short T2 (<20 ms). Here, we acquire MRS measurements for Glu, (t) total creatine (tCr) and total N-acetylaspartate (tNAA) from the visual cortex in 14 healthy participants at a range of TE values between 9.3-280 ms during short blocks (64 s) of flickering checkerboards and rest to examine both the short- and long-T2 components of the curve. We fit monoexponential and biexponential Glu, tCr and tNAA T2 relaxation curves for rest and stimulation and use Akaike information criterion to assess best model fit. We also include power calculations for detection of a 2% shift of Glu between compartments for each TE. Using pooled data over all participants at rest, we observed a short Glu T2-component with T2 = 10 ms and volume fraction of 0.35, a short tCr T2-component with T2 = 26 ms and volume fraction of 0.25 and a short tNAA T2-component around 15 ms with volume fraction of 0.34. No statistically significant change in Glu, tCr and tNAA signal during stimulation was detected at any TE. The volume fractions of short-T2 component between rest and active conditions were not statistically different. This study provides evidence for a short T2-component for Glu, tCr and tNAA but no evidence to support the hypothesis of task-related changes in glutamate distribution between short and long T2 compartments.

Metabolic Reprogramming of Astrocytes in Pathological Conditions: Implications for Neurodegenerative Diseases

Astrocytes play a pivotal role in maintaining brain energy homeostasis, supporting neuronal function through glycolysis and lipid metabolism. This review explores the metabolic intricacies of astrocytes in both physiological and pathological conditions, highlighting their adaptive plasticity and diverse functions. Under normal conditions, astrocytes modulate synaptic activity, recycle neurotransmitters, and maintain the blood-brain barrier, ensuring a balanced energy supply and protection against oxidative stress. However, in response to central nervous system pathologies such as neurotrauma, stroke, infections, and neurodegenerative diseases like Alzheimer's and Huntington's disease, astrocytes undergo significant morphological, molecular, and metabolic changes. Reactive astrocytes upregulate glycolysis and fatty acid oxidation to meet increased energy demands, which can be protective in acute settings but may exacerbate chronic inflammation and disease progression. This review emphasizes the need for advanced molecular, genetic, and physiological tools to further understand astrocyte heterogeneity and their metabolic reprogramming in disease states.

In vivo neuropil density from anatomical MRI and machine learning

Brain energy budgets specify metabolic costs emerging from underlying mechanisms of cellular and synaptic activities. While current bottom-up energy budgets use prototypical values of cellular density and synaptic density, predicting metabolism from a person's individualized neuropil density would be ideal. We hypothesize that in vivo neuropil density can be derived from magnetic resonance imaging (MRI) data, consisting of longitudinal relaxation (T1) MRI for gray/white matter distinction and diffusion MRI for tissue cellularity (apparent diffusion coefficient, ADC) and axon directionality (fractional anisotropy, FA). We present a machine learning algorithm that predicts neuropil density from in vivo MRI scans, where ex vivo Merker staining and in vivo synaptic vesicle glycoprotein 2A Positron Emission Tomography (SV2A-PET) images were reference standards for cellular and synaptic density, respectively. We used Gaussian-smoothed T1/ADC/FA data from 10 healthy subjects to train an artificial neural network, subsequently used to predict cellular and synaptic density for 54 test subjects. While excellent histogram overlaps were observed both for synaptic density (0.93) and cellular density (0.85) maps across all subjects, the lower spatial correlations both for synaptic density (0.89) and cellular density (0.58) maps are suggestive of individualized predictions. This proof-of-concept artificial neural network may pave the way for individualized energy atlas prediction, enabling microscopic interpretations of functional neuroimaging data.

Lactate as a supplemental fuel for synaptic transmission and neuronal network oscillations: Potentials and limitations

Lactate shuttled from the blood circulation, astrocytes, oligodendrocytes or even activated microglia (resident macrophages) to neurons has been hypothesized to represent a major source of pyruvate compared to what is normally produced endogenously by neuronal glucose metabolism. However, the role of lactate oxidation in fueling neuronal signaling associated with complex cortex function, such as perception, motor activity, and memory formation, is widely unclear. This issue has been experimentally addressed using electrophysiology in hippocampal slice preparations (ex vivo) that permit the induction of different neural network activation states by electrical stimulation, optogenetic tools or receptor ligand application. Collectively, these studies suggest that lactate in the absence of glucose (lactate only) impairs gamma (30-70 Hz) and theta-gamma oscillations, which feature high energy demand revealed by the cerebral metabolic rate of oxygen (CMRO2, set to 100%). The impairment comprises oscillation attenuation or moderate neural bursts (excitation-inhibition imbalance). The bursting is suppressed by elevating the glucose fraction in energy substrate supply. By contrast, lactate can retain certain electric stimulus-induced neural population responses and intermittent sharp wave-ripple activity that features lower energy expenditure (CMRO2 of about 65%). Lactate utilization increases the oxygen consumption by about 9% during sharp wave-ripples reflecting enhanced adenosine-5'-triphosphate (ATP) synthesis by oxidative phosphorylation in mitochondria. Moreover, lactate attenuates neurotransmission in glutamatergic pyramidal cells and fast-spiking, γ-aminobutyric acid (GABA)ergic interneurons by reducing neurotransmitter release from presynaptic terminals. By contrast, the generation and propagation of action potentials in the axon is regular. In conclusion, lactate is less effective than glucose and potentially detrimental during neural network rhythms featuring high energetic costs, likely through the lack of some obligatory ATP synthesis by aerobic glycolysis at excitatory and inhibitory synapses. High lactate/glucose ratios might contribute to central fatigue, cognitive impairment, and epileptic seizures partially seen, for instance, during exhaustive physical exercise, hypoglycemia and neuroinflammation.

Neurovascular coupling is optimized to compensate for the increase in proton production from nonoxidative glycolysis and glycogenolysis during brain activation and maintain homeostasis of pH, pCO2, and pO2

During transient brain activation cerebral blood flow (CBF) increases substantially more than cerebral metabolic rate of oxygen consumption (CMRO2) resulting in blood hyperoxygenation, the basis of BOLD-fMRI contrast. Explanations for the high CBF versus CMRO2 slope, termed neurovascular coupling (NVC) constant, focused on maintenance of tissue oxygenation to support mitochondrial ATP production. However, paradoxically the brain has a 3-fold lower oxygen extraction fraction (OEF) than other organs with high energy requirements, like heart and muscle during exercise. Here, we hypothesize that the NVC constant and the capillary oxygen mass transfer coefficient (which in combination determine OEF) are co-regulated during activation to maintain simultaneous homeostasis of pH and partial pressure of CO2 and O2 (pCO2 and pO2). To test our hypothesis, we developed an arteriovenous flux balance model for calculating blood and brain pH, pCO2, and pO2 as a function of baseline OEF (OEF0), CBF, CMRO2, and proton production by nonoxidative metabolism coupled to ATP hydrolysis. Our model was validated against published brain arteriovenous difference studies and then used to calculate pH, pCO2, and pO2 in activated human cortex from published calibrated fMRI and PET measurements. In agreement with our hypothesis, calculated pH, pCO2, and pO2 remained close to constant independently of CMRO2 in correspondence to experimental measurements of NVC and OEF0. We also found that the optimum values of the NVC constant and OEF0 that ensure simultaneous homeostasis of pH, pCO2, and pO2 were remarkably similar to their experimental values. Thus, the high NVC constant is overall determined by proton removal by CBF due to increases in nonoxidative glycolysis and glycogenolysis. These findings resolve the paradox of the brain's high CBF yet low OEF during activation, and may contribute to explaining the vulnerability of brain function to reductions in blood flow and capillary density with aging and neurovascular disease.

Metabolic dynamics in astrocytes and microglia during post-natal development and their implications for autism spectrum disorders

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by elusive underlying mechanisms. Recent attention has focused on the involvement of astrocytes and microglia in ASD pathology. These glial cells play pivotal roles in maintaining neuronal homeostasis, including the regulation of metabolism. Emerging evidence suggests a potential association between ASD and inborn errors of metabolism. Therefore, gaining a comprehensive understanding of the functions of microglia and astrocytes in ASD is crucial for the development of effective therapeutic interventions. This review aims to provide a summary of the metabolism of astrocytes and microglia during post-natal development and the evidence of disrupted metabolic pathways in ASD, with particular emphasis on those potentially important for the regulation of neuronal post-natal maturation by astrocytes and microglia.

Brain Frontal-Lobe Misery Perfusion in COVID-19 ICU Survivors: An MRI Pilot Study

Post-acute COVID-19 syndrome (PCS) is highly prevalent. Critically ill patients requiring intensive care unit (ICU) admission are at a higher risk of developing PCS. The mechanisms underlying PCS are still under investigation and may involve microvascular damage in the brain. Cerebral misery perfusion, characterized by reduced cerebral blood flow (CBF) and elevated oxygen extraction fraction (OEF) in affected brain areas, has been demonstrated in cerebrovascular diseases such as carotid occlusion and stroke. This pilot study aimed to examine whether COVID-19 ICU survivors exhibited regional misery perfusion, indicating cerebral microvascular damage. In total, 7 COVID-19 ICU survivors (4 female, 20-77 years old) and 19 age- and sex-matched healthy controls (12 female, 22-77 years old) were studied. The average interval between ICU admission and the MRI scan was 118.6 ± 30.3 days. The regional OEF was measured using a recently developed technique, accelerated T2-relaxation-under-phase-contrast MRI, while the regional CBF was assessed using pseudo-continuous arterial spin labeling. COVID-19 ICU survivors exhibited elevated OEF (β = 5.21 ± 2.48%, p = 0.047) and reduced relative CBF (β = -0.083 ± 0.025, p = 0.003) in the frontal lobe compared to healthy controls. In conclusion, misery perfusion was observed in the frontal lobe of COVID-19 ICU survivors, suggesting microvascular damage in this critical brain area for high-level cognitive functions that are known to manifest deficits in PCS. Physiological biomarkers such as OEF and CBF may provide new tools to improve the understanding and treatment of PCS.

Evaluation of whole-brain oxygen metabolism in Alzheimer's disease using QSM and quantitative BOLD

OBJECTIVE

The objective of this study was to evaluate the whole-brain pattern of oxygen extraction fraction (OEF), cerebral blood flow (CBF), and cerebral metabolic rate of oxygen consumption (CMRO2) perturbation in Alzheimer's disease (AD) and investigate the relationship between regional cerebral oxygen metabolism and global cognition.

METHODS

Twenty-six AD patients and 25 age-matched healthy controls (HC) were prospectively recruited in this study. Mini-Mental State Examination (MMSE) was used to evaluate cognitive status. We applied the QQ-CCTV algorithm which combines quantitative susceptibility mapping and quantitative blood oxygen level-dependent models (QQ) for OEF calculation. CBF map was computed from arterial spin labeling and CMRO2 was generated based on Fick's principle. Whole-brain and regional OEF, CBF, and CMRO2 analyses were performed. The associations between these measures in substructures of deep brain gray matter and MMSE scores were assessed.

RESULTS

Whole brain voxel-wise analysis showed that CBF and CMRO2 values significantly decreased in AD predominantly in the bilateral angular gyrus, precuneus gyrus and parieto-temporal regions. Regional analysis showed that CBF value decreased in the bilateral caudal hippocampus and left rostral hippocampus and CMRO2 value decreased in left caudal and rostral hippocampus in AD patients. Considering all subjects in the AD and HC groups combined, the mean CBF and CMRO2 values in the bilateral hippocampus positively correlated with the MMSE score.

CONCLUSION

CMRO2 mapping with the QQ-CCTV method - which is readily available in MR systems for clinical practice - can be a potential biomarker for AD. In addition, CMRO2 in the hippocampus may be a useful tool for monitoring cognitive impairment.

A new framework for metabolic connectivity mapping using bolus [18F]FDG PET and kinetic modeling

Metabolic connectivity (MC) has been previously proposed as the covariation of static [18F]FDG PET images across participants, i.e., across-individual MC (ai-MC). In few cases, MC has been inferred from dynamic [18F]FDG signals, i.e., within-individual MC (wi-MC), as for resting-state fMRI functional connectivity (FC). The validity and interpretability of both approaches is an important open issue. Here we reassess this topic, aiming to 1) develop a novel wi-MC methodology; 2) compare ai-MC maps from standardized uptake value ratio (SUVR) vs. [18F]FDG kinetic parameters fully describing the tracer behavior (i.e., Ki, K1, k3); 3) assess MC interpretability in comparison to structural connectivity and FC. We developed a new approach based on Euclidean distance to calculate wi-MC from PET time-activity curves. The across-individual correlation of SUVR, Ki, K1, k3 produced different networks depending on the chosen [18F]FDG parameter (k3 MC vs. SUVR MC, r = 0.44). We found that wi-MC and ai-MC matrices are dissimilar (maximum r = 0.37), and that the match with FC is higher for wi-MC (Dice similarity: 0.47-0.63) than for ai-MC (0.24-0.39). Our analyses demonstrate that calculating individual-level MC from dynamic PET is feasible and yields interpretable matrices that bear similarity to fMRI FC measures.

A functional account of stimulation-based aerobic glycolysis and its role in interpreting BOLD signal intensity increases in neuroimaging experiments

In aerobic glycolysis, oxygen is abundant, and yet cells metabolize glucose without using it, decreasing their ATP per glucose yield by 15-fold. During task-based stimulation, aerobic glycolysis occurs in localized brain regions, presenting a puzzle: why produce ATP inefficiently when, all else being equal, evolution should favor the efficient use of metabolic resources? The answer is that all else is not equal. We propose that a tradeoff exists between efficient ATP production and the efficiency with which ATP is spent to transmit information. Aerobic glycolysis, despite yielding little ATP per glucose, may support neuronal signaling in thin (< 0.5 µm), information-efficient axons. We call this the efficiency tradeoff hypothesis. This tradeoff has potential implications for interpretations of task-related BOLD "activation" observed in fMRI. We hypothesize that BOLD "activation" may index local increases in aerobic glycolysis, which support signaling in thin axons carrying "bottom-up" information, or "prediction error"-i.e., the BIAPEM (BOLD increases approximate prediction error metabolism) hypothesis. Finally, we explore implications of our hypotheses for human brain evolution, social behavior, and mental disorders.

Reproducibility of cerebral blood flow, oxygen metabolism, and lactate and N-acetyl-aspartate concentrations measured using magnetic resonance imaging and spectroscopy

In humans, resting cerebral perfusion, oxygen consumption and energy metabolism demonstrate large intersubject variation regardless of methodology. Whether a similar large variation is also present longitudinally in individual subjects is much less studied, but knowing the time variance in reproducibility is important when designing and interpreting longitudinal follow-up studies examining brain physiology. Therefore, we examined the reproducibility of cerebral blood flow (CBF), global cerebral metabolic rate of oxygen (CMRO2), global arteriovenous oxygen saturation difference (A-V.O2), and cerebral lactate and N-acetyl-aspartate (NAA) concentrations measured using magnetic resonance imaging (MRI) and spectroscopy (MRS) techniques through repeated measurements at 6 h, 24 h, 7 days and several weeks after initial baseline measurements in young healthy adults (N = 26, 13 females, age range 18-35 years). Using this setup, we calculated the correlation, limit of agreement (LoA) and within-subject coefficient of variation (CoVWS) between baseline values and the subsequent repeated measurements to examine the longitudinal variation in individual cerebral physiology. CBF and CMRO2 correlated significantly between baseline and all subsequent measurements. The strength of the correlations (R2) and reproducibility metrics (LoA and CoVWS) demonstrated the best reproducibility for the within-day measurements and generally declined with longer time between measurements. Cerebral lactate and NAA concentrations also correlated significantly for all measurements, except between baseline and the 7-day measurement for lactate. Similar to CBF and CMRO2, lactate and NAA demonstrated the best reproducibility for within-day repeated measurements. The gradual decline in reproducibility over time should be considered when designing and interpreting studies on brain physiology, for example, in the evaluation of treatment efficacy.

Evaluating Physiological MRI Parameters in Patients with Brain Metastases Undergoing Stereotactic Radiosurgery-A Preliminary Analysis and Case Report

Brain metastases occur in ten to thirty percent of the adult cancer population. Treatment consists of different (palliative) options, including stereotactic radiosurgery (SRS). Sensitive MRI biomarkers are needed to better understand radiotherapy-related effects on cerebral physiology and the subsequent effects on neurocognitive functioning. In the current study, we used physiological imaging techniques to assess cerebral blood flow (CBF), oxygen extraction fraction (OEF), cerebral metabolic rate of oxygen (CMRO2) and cerebrovascular reactivity (CVR) before and three months after SRS in nine patients with brain metastases. The results showed improvement in OEF, CBF and CMRO2 within brain tissue that recovered from edema (all p ≤ 0.04), while CVR remained impacted. We observed a global post-radiotherapy increase in CBF in healthy-appearing brain tissue (p = 0.02). A repeated measures correlation analysis showed larger reductions within regions exposed to higher radiotherapy doses in CBF (rrm = -0.286, p < 0.001), CMRO2 (rrm = -0.254, p < 0.001), and CVR (rrm = -0.346, p < 0.001), but not in OEF (rrm = -0.004, p = 0.954). Case analyses illustrated the impact of brain metastases progression on the post-radiotherapy changes in both physiological MRI measures and cognitive performance. Our preliminary findings suggest no radiotherapy effects on physiological parameters occurred in healthy-appearing brain tissue within 3-months post-radiotherapy. Nevertheless, as radiotherapy can have late side effects, larger patient samples allowing meaningful grouping of patients and longer follow-ups are needed.

A 3D atlas of functional human brain energetic connectome based on neuropil distribution

The human brain is energetically expensive, yet the key factors governing its heterogeneous energy distributions across cortical regions to support its diversity of functions remain unexplored. Here, we built up a 3D digital cortical energy atlas based on the energetic costs of all neuropil activities into a high-resolution stereological map of the human cortex with cellular and synaptic densities derived, respectively, from ex vivo histological staining and in vivo PET imaging. The atlas was validated with PET-measured glucose oxidation at the voxel level. A 3D cortical activity map was calculated to predict the heterogeneous activity rates across all cortical regions, which revealed that resting brain is indeed active with heterogeneous neuronal activity rates averaging around 1.2 Hz, comprising around 70% of the glucose oxidation of the cortex. Additionally, synaptic density dominates spatial patterns of energetics, suggesting that the cortical energetics rely heavily on the distribution of synaptic connections. Recent evidence from functional imaging studies suggests that some cortical areas act as hubs (i.e., interconnecting distinct and functionally active regions). An inverse allometric relationship was observed between hub metabolic rates versus hub volumes. Hubs with smaller volumes have higher synapse density, metabolic rate, and activity rates compared to nonhubs. The open-source BrainEnergyAtlas provides a granular framework for exploring revealing design principles in energy-constrained human cortical circuits across multiple spatial scales.

Ketamine Effects on Energy Metabolism, Functional Connectivity and Working Memory in Healthy Humans

Working memory (WM) is a crucial resource for temporary memory storage and the guiding of ongoing behavior. N-methyl-D-aspartate glutamate receptors (NMDARs) are thought to support the neural underpinnings of WM. Ketamine is an NMDAR antagonist that has cognitive and behavioral effects at subanesthetic doses. To shed light on subanesthetic ketamine effects on brain function, we employed a multimodal imaging design, combining gas-free calibrated functional magnetic resonance imaging (fMRI) measurement of oxidative metabolism (CMRO ₂ ), resting-state cortical functional connectivity assessed with fMRI, and WM-related fMRI. Healthy subjects participated in two scan sessions in a randomized, double-blind, placebo-controlled design. Ketamine increased CMRO ₂ and cerebral blood flow (CBF) in prefrontal cortex (PFC) and other cortical regions. However, resting-state cortical functional connectivity was not affected. Ketamine did not alter CBF-CMRO ₂ coupling brain-wide. Higher levels of basal CMRO ₂ were associated with lower task-related PFC activation and WM accuracy impairment under both saline and ketamine conditions. These observations suggest that CMRO ₂ and resting-state functional connectivity index distinct dimensions of neural activity. Ketamine’s impairment of WM-related neural activity and performance appears to be related to its ability to produce cortical metabolic activation. This work illustrates the utility of direct measurement of CMRO ₂ via calibrated fMRI in studies of drugs that potentially affect neurovascular and neurometabolic coupling.

A mean-field model of glutamate and GABA synaptic dynamics for functional MRS

Advances in functional magnetic resonance spectroscopy (fMRS) have enabled the quantification of activity-dependent changes in neurotransmitter concentrations in vivo. However, the physiological basis of the large changes in GABA and glutamate observed by fMRS (>10%) over short time scales of less than a minute remain unclear as such changes cannot be accounted for by known synthesis or degradation metabolic pathways. Instead, it has been hypothesized that fMRS detects shifts in neurotransmitter concentrations as they cycle from presynaptic vesicles, where they are largely invisible, to extracellular and cytosolic pools, where they are detectable. The present paper uses a computational modelling approach to demonstrate the viability of this hypothesis. A new mean-field model of the neural mechanisms generating the fMRS signal in a cortical voxel is derived. The proposed macroscopic mean-field model is based on a microscopic description of the neurotransmitter dynamics at the level of the synapse. Specifically, GABA and glutamate are assumed to cycle between three metabolic pools: packaged in the vesicles; active in the synaptic cleft; and undergoing recycling and repackaging in the astrocytic or neuronal cytosol. Computational simulations from the model are used to generate predicted changes in GABA and glutamate concentrations in response to different types of stimuli including pain, vision, and electric current stimulation. The predicted changes in the extracellular and cytosolic pools corresponded to those reported in empirical fMRS data. Furthermore, the model predicts a selective control mechanism of the GABA/glutamate relationship, whereby inhibitory stimulation reduces both neurotransmitters, whereas excitatory stimulation increases glutamate and decreases GABA. The proposed model bridges between neural dynamics and fMRS and provides a mechanistic account for the activity-dependent changes in the glutamate and GABA fMRS signals. Lastly, these results indicate that echo-time may be an important timing parameter that can be leveraged to maximise fMRS experimental outcomes.

Expression of actin- and oxidative phosphorylation-related transcripts across the cortical visuospatial working memory network in unaffected comparison and schizophrenia subjects

Visuospatial working memory (vsWM), which is impaired in schizophrenia (SZ), is mediated by a distributed cortical network. In one node of this network, the dorsolateral prefrontal cortex (DLPFC), altered expression of transcripts for actin assembly and mitochondrial oxidative phosphorylation (OXPHOS) have been reported in SZ. To understand the relationship between these processes, and the extent to which similar alterations are present in other regions of vsWM network in SZ, a subset of actin- (CDC42, BAIAP2, ARPC3, and ARPC4) and OXPHOS-related (ATP5H, COX4I1, COX7B, and NDUFB3) transcripts were quantified in DLPFC by RNA sequencing in 139 SZ and unaffected comparison (UC) subjects, and in DLPFC and three other regions of the cortical vsWM network by qPCR in 20 pairs of SZ and UC subjects. By RNA sequencing, levels of actin- and OXPHOS-related transcripts were significantly altered in SZ, and robustly correlated in both UC and SZ subject groups. By qPCR, cross-regional expression patterns of these transcripts in UC subjects were consistent with greater actin assembly in DLPFC and higher OXPHOS activity in primary visual cortex (V1). In SZ, CDC42 and ARPC4 levels were lower in all regions, BAIAP2 levels higher only in V1, and ARPC3 levels unaltered across regions. All OXPHOS-related transcript levels were lower in SZ, with the disease effect decreasing from posterior to anterior regions. The differential alterations in markers of actin assembly and energy production across regions of the cortical vsWM network in SZ suggest that each region may make specific contributions to vsWM impairments in the illness.

Increased white matter glycolysis in humans with cerebral small vessel disease

White matter lesions in cerebral small vessel disease are related to ischemic injury and increase the risk of stroke and cognitive decline. Pathological changes due to cerebral small vessel disease are increasingly recognized outside of discrete lesions, but the metabolic alterations in nonlesional tissue has not been described. Aerobic glycolysis is critical to white matter myelin homeostasis and repair. In this study, we examined cerebral metabolism of glucose and oxygen as well as blood flow in individuals with and without cerebral small vessel disease using multitracer positron emission tomography. We show that glycolysis is relatively elevated in nonlesional white matter in individuals with small vessel disease relative to healthy, age-matched controls. On the other hand, in young healthy individuals, glycolysis is relatively low in areas of white matter susceptible to lesion formation. These results suggest that increased white matter glycolysis is a marker of pathology associated with small vessel disease.

Oxygen extraction fraction (OEF) assesses cerebral oxygen metabolism of deep gray matter in patients with pre-eclampsia

OBJECTIVES

The objective of this study was to compare oxygen extraction fraction (OEF) values in the deep gray matter (GM) of pre-eclampsia (PE) patients, pregnant healthy controls (PHCs), and non-pregnant healthy controls (NPHCs) to explore their brain oxygen metabolism differences in GM.

METHODS

Forty-seven PE patients, forty NPHCs, and twenty-one PHCs were included. Brain OEF values were computed from quantitative susceptibility mapping (QSM) plus quantitative blood oxygen level-dependent magnitude (QSM + qBOLD = QQ)-based mapping. One-way ANOVA was used to compare mean OEF values in the three groups. The area under the curve of the mean OEF value in each region of interest was estimated using a receiver operating characteristic curve analysis.

RESULTS

We found that the mean OEF values in the thalamus, putamen, caudate nucleus, pallidum, and substantia nigra were significantly different in these three groups (F = 5.867, p = 0.004; F = 5.142, p = 0007; F = 6.158, p = 0.003; F = 6.319, p = 0.003; F = 5.491, p = 0.005). The mean OEF values for these 5 regions were higher in PE patients than in NPHCs and in PHCs (p < 0.05). The AUC of these ROIs ranged from 0.673 to 0.692 (p < 0.01) and cutoff values varied from 35.1 to 36.6%, indicating that the OEF values could discriminate patients with and without PE. Stepwise multivariate analysis revealed that the OEF values correlated with hematocrit in pregnant women (r = 0.353, p = 0.003).

CONCLUSION

OEF values in the brains of pregnant women can be measured in clinical practice using QQ-based OEF mapping for noninvasive assessment of hypertensive disorders.

KEY POINTS

• Pre-eclampsia is a hypertensive disorder associated with abnormalities in brain oxygen extraction. • Oxygen extraction fraction (OEF) is an indicator of brain tissue viability and function. QQ-based mapping of OEF is a new MRI technique that can noninvasively quantify brain oxygen metabolism. • OEF values in the brains of pregnant women can be measured for noninvasive assessment of hypertensive disorders in clinical practice.

Non-Invasive measurement of the cerebral metabolic rate of oxygen using MRI in rodents

Malfunctions of oxygen metabolism are suspected to play a key role in a number of neurological and psychiatric disorders, but this hypothesis cannot be properly investigated without an in-vivo non-invasive measurement of brain oxygen consumption. We present a new way to measure the Cerebral Metabolic Rate of Oxygen (CMRO2) by combining two existing magnetic resonance imaging techniques, namely arterial spin-labelling and oxygen extraction fraction mapping. This method was validated by imaging rats under different anaesthetic regimes and was strongly correlated to glucose consumption measured by autoradiography.

Non-Invasive measurement of the cerebral metabolic rate of oxygen using MRI in rodents

Malfunctions of oxygen metabolism are suspected to play a key role in a number of neurological and psychiatric disorders, but this hypothesis cannot be properly investigated without an in-vivo non-invasive measurement of brain oxygen consumption. We present a new way to measure the Cerebral Metabolic Rate of Oxygen (CMRO 2) by combining two existing magnetic resonance imaging techniques, namely arterial spin-labelling and oxygen extraction fraction mapping. This method was validated by imaging rats under different anaesthetic regimes and was strongly correlated to glucose consumption measured by autoradiography.

Non-Invasive measurement of the cerebral metabolic rate of oxygen using MRI in rodents

Malfunctions of oxygen metabolism are suspected to play a key role in a number of neurological and psychiatric disorders, but this hypothesis cannot be properly investigated without an in-vivo non-invasive measurement of brain oxygen consumption. We present a new way to measure the Cerebral Metabolic Rate of Oxygen (CMRO2) by combining two existing magnetic resonance imaging techniques, namely arterial spin-labelling and oxygen extraction fraction mapping. This method was validated by imaging rats under different anaesthetic regimes and was strongly correlated to glucose consumption measured by autoradiography.

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.

Human brain functional MRS reveals interplay of metabolites implicated in neurotransmission and neuroenergetics

While functional MRI (fMRI) localizes brain activation and deactivation, functional MRS (fMRS) provides insights into the underlying metabolic conditions. There is much interest in measuring task-induced and resting levels of metabolites implicated in neuroenergetics (e.g., lactate, glucose, or β-hydroxybutyrate (BHB)) and neurotransmission (e.g., γ-aminobutyric acid (GABA) or pooled glutamate and glutamine (Glx)). Ultra-high magnetic field (e.g., 7T) has boosted the fMRS quantification precision, reliability, and stability of spectroscopic observations using short echo-time (TE) 1H-MRS techniques. While short TE 1H-MRS lacks sensitivity and specificity for fMRS at lower magnetic fields (e.g., 3T or 4T), most of these metabolites can also be detected by J-difference editing (JDE) 1H-MRS with longer TE to filter overlapping resonances. The 1H-MRS studies show that JDE can detect GABA, Glx, lactate, and BHB at 3T, 4T and 7T. Most recently, it has also been demonstrated that JDE 1H-MRS is capable of reliable detection of metabolic changes in different brain areas at various magnetic fields. Combining fMRS measurements with fMRI is important for understanding normal brain function, but also clinically relevant for mechanisms and/or biomarkers of neurological and neuropsychiatric disorders. We provide an up-to-date overview of fMRS research in the last three decades, both in terms of applications and technological advances. Overall the emerging fMRS techniques can be expected to contribute substantially to our understanding of metabolism for brain function and dysfunction.

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.

Aerobic glycolysis imaging of epileptic foci during the inter-ictal period

BACKGROUND

In drug-resistant epilepsy, surgical resection of the epileptic focus can end seizures. However, success is dependent on the ability to identify foci locations and, unfortunately, current methods like electrophysiology and positron emission tomography can give contradictory results. During seizures, glucose is metabolized at epileptic foci through aerobic glycolysis, which can be imaged through the oxygen-glucose index (OGI) biomarker. However, inter-ictal (between seizures) OGI changes have not been studied, which has limited its application.

METHODS

18 healthy controls and 24 inter-ictal, temporal lobe epilepsy patients underwent simultaneous positron emission tomography (PET) and magnetic resonance imaging (MRI) scans. We used [18F]fluorodeoxyglucose-PET (FDG-PET) to detect cerebral glucose metabolism, and calibrated functional MRI to acquire relative oxygen consumption. With these data, we calculated relative OGI maps.

FINDINGS

While bilaterally symmetrical in healthy controls, we observed, in patients during the inter-ictal period, higher OGI ipsilateral to the epileptic focus than contralateral. While traditional FDG-PET results and temporal lobe OGI results usually both agreed with invasive electrophysiology, in cases where FDG-PET disagreed with electrophysiology, temporal lobe OGI agreed with electrophysiology, and vice-versa.

INTERPRETATION

As either our novel epilepsy biomarker or traditional approaches located foci in every case, our work provides promising insights into metabolic changes in epilepsy. Our method allows single-session OGI measurement which can be useful in other diseases.

FUNDING

This work was supported by ShanghaiTech University, the Shanghai Municipal Government, the National Natural Science Foundation of China Grant (No. 81950410637) and Shanghai Municipal Key Clinical Specialty (No. shslczdzk03403). F. H. and P. H. were supported by USA National Institute of Health grants (R01 NS-100106, R01 MH-067528).Z. W. was supported by the Key-Area Research and Development Program of Guangdong Province (2019B030335001), National Natural Science Foundation of China (No. 82151303), and National Key R&D Program of China (No. 2021ZD0204002).

Hemodynamic and metabolic correspondence of resting-state voxel-based physiological metrics in healthy adults

Voxel-based physiological (VBP) variables derived from blood oxygen level dependent (BOLD) fMRI time-course variations include: amplitude of low frequency fluctuations (ALFF), fractional amplitude of low frequency fluctuations (fALFF) and regional homogeneity (ReHo). Although these BOLD-derived variables can detect between-group (e.g. disease vs control) spatial pattern differences, physiological interpretations are not well established. The primary objective of this study was to quantify spatial correspondences between BOLD VBP variables and PET measurements of cerebral metabolic rate and hemodynamics, being well-validated physiological standards. To this end, quantitative, whole-brain PET images of metabolic rate of glucose (MRGlu; 18FDG) and oxygen (MRO2; 15OO), blood flow (BF; H215O) and blood volume (BV; C15O) were obtained in 16 healthy controls. In the same subjects, BOLD time-courses were obtained for computation of ALFF, fALFF and ReHo images. PET variables were compared pair-wise with BOLD variables. In group-averaged, across-region analyses, ALFF corresponded significantly only with BV (R = 0.64; p < 0.0001). fALFF corresponded most strongly with MRGlu (R = 0.79; p < 0.0001), but also significantly (p < 0.0001) with MRO2 (R = 0.68), BF (R = 0.68) and BV (R=0.68). ReHo performed similarly to fALFF, with significant strong correspondence (p < 0.0001) with MRGlu (R = 0.78), MRO2 (R = 0.54), and, but less strongly with BF (R = 0.50) and BV (R=0.50). Mutual information analyses further clarified these physiological interpretations. When conditioned by BV, ALFF retained no significant MRGlu, MRO2 or BF information. When conditioned by MRGlu, fALFF and ReHo retained no significant MRO2, BF or BV information. Of concern, however, the strength of PET-BOLD correspondences varied markedly by brain region, which calls for future investigation on physiological interpretations at a regional and per-subject basis.

From a Demand-Based to a Supply-Limited Framework of Brain Metabolism

What defines the rate of energy use by the brain, as well as per neurons of different sizes in different structures and animals, is one fundamental aspect of neuroscience for which much has been theorized, but very little data are available. The prevalent theories and models consider that energy supply from the vascular system to different brain regions is adjusted both dynamically and in the course of development and evolution to meet the demands of neuronal activity. In this perspective, we offer an alternative view: that regional rates of energy use might be mostly constrained by supply, given the properties of the brain capillary network, the highly stable rate of oxygen delivery to the whole brain under physiological conditions, and homeostatic constraints. We present evidence that these constraints, based on capillary density and tissue oxygen homeostasis, are similar between brain regions and mammalian species, suggesting they derive from fundamental biophysical limitations. The same constraints also determine the relationship between regional rates of brain oxygen supply and usage over the full physiological range of brain activity, from deep sleep to intense sensory stimulation, during which the apparent uncoupling of blood flow and oxygen use is still a predicted consequence of supply limitation. By carefully separating "energy cost" into energy supply and energy use, and doing away with the problematic concept of energetic "demands," our new framework should help shine a new light on the neurovascular bases of metabolic support of brain function and brain functional imaging. We speculate that the trade-offs between functional systems and even the limitation to a single attentional spot at a time might be consequences of a strongly supply-limited brain economy. We propose that a deeper understanding of brain energy supply constraints will provide a new evolutionary understanding of constraints on brain function due to energetics; offer new diagnostic insight to disturbances of brain metabolism; lead to clear, testable predictions on the scaling of brain metabolic cost and the evolution of brains of different sizes; and open new lines of investigation into the microvascular bases of progressive cognitive loss in normal aging as well as metabolic diseases.

Microglial metabolic flexibility: emerging roles for lactate

Microglia, the resident macrophages of the central nervous system (CNS), play important functions in the healthy and diseased brain. In the emerging field of immunometabolism, progress has been made in understanding how cellular metabolism can orchestrate the key responses of tissue macrophages, such as phagocytosis and inflammation. However, very little is known about the metabolic control of microglia. Lactate, now recognized as a crucial metabolite and a central substrate in metabolic flexibility, is emerging not only as a novel bioenergetic fuel for microglial metabolism but also as a potential modulator of cellular function. Parallels with macrophages will help in understanding how microglial lactate metabolism is implicated in brain physiology and pathology, and how it could be targeted for therapeutic purposes.

Imaging effective oxygen diffusivity in the human brain with multiparametric magnetic resonance imaging

Cerebrovascular diseases can impair blood circulation and oxygen extraction from the blood. The effective oxygen diffusivity (EOD) of the capillary bed is a potential biomarker of microvascular function that has gained increasing interest, both for clinical diagnosis and for elucidating oxygen transport mechanisms. Models of capillary oxygen transport link EOD to measurable oxygen extraction fraction (OEF) and cerebral blood flow (CBF). In this work, we confirm that two well established mathematical models of oxygen transport yield nearly equivalent EOD maps. Furthermore, we propose an easy-to-implement and clinically applicable multiparametric magnetic resonance imaging (MRI) protocol for quantitative EOD mapping. Our approach is based on imaging OEF and CBF with multiparametric quantitative blood oxygenation level dependent (mq-BOLD) MRI and pseudo-continuous arterial spin labeling (pCASL), respectively. We evaluated the imaging protocol by comparing MRI-EOD maps of 12 young healthy volunteers to PET data from a published study in different individuals. Our results show comparably good correlation between MRI- and PET-derived cortical EOD, OEF and CBF. Importantly, absolute values of MRI and PET showed high accordance for all three parameters. In conclusion, our data indicates feasibility of the proposed MRI protocol for EOD mapping, rendering the method promising for future clinical evaluation of patients with cerebrovascular diseases.

Rescuing mitochondria in traumatic brain injury and intracerebral hemorrhages - A potential therapeutic approach

Mitochondria are dynamic organelles responsible for cellular energy production. Besides, regulating energy homeostasis, mitochondria are responsible for calcium homeostasis, signal transmission, and the fate of cellular survival in case of injury and pathologies. Accumulating reports have suggested multiple roles of mitochondria in neuropathologies, neurodegeneration, and immune activation under physiological and pathological conditions. Mitochondrial dysfunction, which occurs at the initial phase of brain injury, involves oxidative stress, inflammation, deficits in mitochondrial bioenergetics, biogenesis, transport, and autophagy. Thus, development of targeted therapeutics to protect mitochondria may improve functional outcomes following traumatic brain injury (TBI) and intracerebral hemorrhages (ICH). In this review, we summarize mitochondrial dysfunction related to TBI and ICH, including the mechanisms involved, and discuss therapeutic approaches with special emphasis on past and current clinical trials.

Astrocyte-neuron metabolic cooperation shapes brain activity

The brain has almost no energy reserve, but its activity coordinates organismal function, a burden that requires precise coupling between neurotransmission and energy metabolism. Deciphering how the brain accomplishes this complex task is crucial to understand central facets of human physiology and disease mechanisms. Each type of neural cell displays a peculiar metabolic signature, forcing the intercellular exchange of metabolites that serve as both energy precursors and paracrine signals. The paradigm of this biological feature is the astrocyte-neuron couple, in which the glycolytic metabolism of astrocytes contrasts with the mitochondrial oxidative activity of neurons. Astrocytes generate abundant mitochondrial reactive oxygen species and shuttle to neurons glycolytically derived metabolites, such as L-lactate and L-serine, which sustain energy needs, conserve redox status, and modulate neurotransmitter-receptor activity. Conversely, early disruption of this metabolic cooperation may contribute to the initiation or progression of several neurological diseases, thus requiring innovative therapies to preserve brain energetics.

Energy metabolism in childhood neurodevelopmental disorders

Whereas energy function in the aging brain and their related neurodegenerative diseases has been explored in some detail, there is limited knowledge about molecular mechanisms and brain networks of energy metabolism during infancy and childhood. In this review we describe current insights on physiological brain energetics at prenatal and neonatal stages, and in childhood. We then describe the main groups of inborn errors of energy metabolism affecting the brain. Of note, scarce basic neuroscience research in this field limits the opportunity for these disorders to provide paradigms of energy utilization during neurodevelopment. Finally, we report energy metabolism disturbances in well-known non-metabolic neurodevelopmental disorders. As energy metabolism is a fundamental biological function, brain energy utilization is likely altered in most neuropediatric diseases. Precise knowledge on mechanisms of brain energy disturbance will open the possibility of metabolic modulation therapies regardless of disease etiology.

Metabolic underpinnings of activated and deactivated cortical areas in human brain

Neuroimaging with functional MRI (fMRI) identifies activated and deactivated brain regions in task-based paradigms. These patterns of (de)activation are altered in diseases, motivating research to understand their underlying biochemical/biophysical mechanisms. Essentially, it remains unknown how aerobic metabolism of glucose to lactate (aerobic glycolysis) and excitatory-inhibitory balance of glutamatergic and GABAergic neuronal activities vary in these areas. In healthy volunteers, we investigated metabolic distinctions of activating visual cortex (VC, a task-positive area) using a visual task and deactivating posterior cingulate cortex (PCC, a task-negative area) using a cognitive task. We used fMRI-guided J-edited functional MRS (fMRS) to measure lactate, glutamate plus glutamine (Glx) and γ-aminobutyric acid (GABA), as indicators of aerobic glycolysis and excitatory-inhibitory balance, respectively. Both lactate and Glx increased upon activating VC, but did not change upon deactivating PCC. Basal GABA was negatively correlated with BOLD responses in both brain areas, but during functional tasks GABA decreased in VC upon activation and GABA increased in PCC upon deactivation, suggesting BOLD responses in relation to baseline are impacted oppositely by task-induced inhibition. In summary, opposite relations between BOLD response and GABAergic inhibition, and increases in aerobic glycolysis and glutamatergic activity distinguish the BOLD response in (de)activated areas.

Zero Echo Time 17O-MRI Reveals Decreased Cerebral Metabolic Rate of Oxygen Consumption in a Murine Model of Amyloidosis

The cerebral metabolic rate of oxygen consumption (CMRO₂) is a key metric to investigate the mechanisms involved in neurodegeneration in animal models and evaluate potential new therapies. CMRO₂ can be measured by direct ¹⁷O magnetic resonance imaging (¹⁷O-MRI) of H₂¹⁷O signal changes during inhalation of ¹⁷O-labeled oxygen gas. In this study, we built a simple gas distribution system and used 3D zero echo time (ZTE-)MRI at 11.7 T to measure CMRO₂ in the APP_swe/PS1_dE9 mouse model of amyloidosis. We found that CMRO₂ was significantly lower in the APP_swe/PS1_dE9 brain than in wild-type at 12-14 months. We also estimated cerebral blood flow (CBF) from the post-inhalation washout curve and found no difference between groups. These results suggest that the lower CMRO₂ observed in APP_swe/PS1_dE9 is likely due to metabolism impairment rather than to reduced blood flow. Analysis of the ¹⁷O-MRI data using different quantification models (linear and 3-phase model) showed that the choice of the model does not affect group comparison results. However, the simplified linear model significantly underestimated the absolute CMRO₂ values compared to a 3-phase model. This may become of importance when combining several metabolic fluxes measurements to study neuro-metabolic coupling.

Regional and interindividual relationships between cerebral perfusion and oxygen metabolism

Quantitative measurements of resting cerebral blood flow (CBF) and metabolic rate of oxygen (CMRO₂) show large between-subject and regional variability, but the relationships between CBF and CMRO₂ measurements regionally and globally are not fully established. Here, we investigated the between-subject and regional associations between CBF and CMRO₂ measures with independent and quantitative PET techniques. We included resting CBF and CMRO₂ measurements from 50 healthy volunteers (aged 22-81 yr), and calculated the regional and global values of oxygen delivery (Do₂) and oxygen extraction fraction (OEF). Linear mixed-model analysis showed that CBF and CMRO₂ measurements were closely associated regionally, but no significant between-subject association could be demonstrated, even when adjusting for arterial Pco₂ and hemoglobin concentration. The analysis also showed regional differences of OEF, reflecting variable relationship between Do₂ and CMRO₂, resulting in lower estimates of OEF in thalami, brainstem, and mesial temporal cortices and higher estimates of OEF in occipital cortex. In the present study, we demonstrated no between-subject association of quantitative measurements of CBF and CMRO₂ in healthy subjects. Thus, quantitative measurements of CBF did not reflect the underlying between-subject variability of oxygen metabolism measures, mainly because of large interindividual OEF variability not accounted for by Pco₂ and hemoglobin concentration.NEW & NOTEWORTHY Using quantitative PET-measurements in healthy human subjects, we confirmed a regional association of CBF and CMRO₂, but did not find an association of these values across subjects. This suggests that subjects have an individual coupling between perfusion and metabolism and shows that absolute perfusion measurements does not serve as a surrogate measure of individual measures of oxygen metabolism. The analysis further showed smaller, but significant regional differences of oxygen extraction fraction at rest.

Resting cerebral oxygen metabolism exhibits archetypal network features

Standard magnetic resonance imaging approaches offer high‐resolution but indirect measures of neural activity, limiting understanding of the physiological processes associated with imaging findings. Here, we used calibrated functional magnetic resonance imaging during the resting state to recover low‐frequency fluctuations of the cerebral metabolic rate of oxygen (CMRO₂). We tested whether functional connections derived from these fluctuations exhibited organization properties similar to those established by previous standard functional and anatomical connectivity studies. Seventeen participants underwent 20 min of resting imaging during dual‐echo, pseudocontinuous arterial spin labeling, and blood‐oxygen‐level dependent (BOLD) signal acquisition. Participants also underwent a 10 min normocapnic and hypercapnic procedure. Brain‐wide, CMRO₂ low‐frequency fluctuations were subjected to graph‐based and voxel‐wise functional connectivity analyses. Results demonstrated that connections derived from resting CMRO₂ fluctuations exhibited complex, small‐world topological properties (i.e., high integration and segregation, cost efficiency) consistent with those observed in previous studies using functional and anatomical connectivity approaches. Voxel‐wise CMRO₂ connectivity also exhibited spatial patterns consistent with four targeted resting‐state subnetworks: two association (i.e., frontoparietal and default mode) and two perceptual (i.e., auditory and occipital‐visual). These are the first findings to support the use of calibration‐derived CMRO₂ low‐frequency fluctuations for detecting brain‐wide organizational properties typical of healthy participants. We discuss interpretations, advantages, and challenges in using calibration‐derived oxygen metabolism signals for examining the intrinsic organization of the human brain.

Validation of T2 -based oxygen extraction fraction measurement with 15 O positron emission tomography

PURPOSE

To evaluate the accuracy of T₂ -based whole-brain oxygen extraction fraction (OEF) estimation by comparing it with gold standard ¹⁵ O-PET measurements.

METHODS

Sixteen healthy adult subjects underwent MRI and ¹⁵ O-PET OEF measurements on the same day. On MRI, whole-brain OEF was quantified by T₂ -relaxation-under-spin-tagging (TRUST) MRI, based on subject-specific hematocrit. The TRUST OEF was compared to the whole-brain averaged OEF produced by ¹⁵ O-PET. Agreement between TRUST and ¹⁵ O-PET whole-brain OEF measurements was examined in terms of intraclass correlation coefficient (ICC) and in absolute OEF values. In a subset of 10 subjects, test-retest reproducibility of whole-brain OEF was also evaluated and compared between the two modalities.

RESULTS

Across the 16 subjects, the mean whole-brain OEF of TRUST and ¹⁵ O-PET were 36.44 ± 4.07% and 36.45 ± 3.65%, respectively, showing no difference between the two modalities (P = .99). TRUST whole-brain OEF strongly correlated with that of ¹⁵ O-PET (N = 16, ICC = 0.90, P = 4 × 10^-7 ). The coefficient-of-variation of TRUST and ¹⁵ O-PET whole-brain OEF measurements were 1.79 ± 0.67% and 2.06 ± 1.55%, respectively, showing no difference between the two modalities (N = 10, P = .64). Further analyses on the effect of hematocrit revealed that correlation between PET OEF and TRUST OEF with assumed hematocrit remained significant (ICC = 0.8, P < 2 × 10^-5 ).

CONCLUSION

Whole-brain OEF measured by TRUST was in excellent agreement with gold standard ¹⁵ O-PET, with highly comparable accuracy and reproducibility. These findings suggest that TRUST MRI can provide accurate quantification of whole-brain OEF noninvasively.

Brain energy rescue: an emerging therapeutic concept for neurodegenerative disorders of ageing

The brain requires a continuous supply of energy in the form of ATP, most of which is produced from glucose by oxidative phosphorylation in mitochondria, complemented by aerobic glycolysis in the cytoplasm. When glucose levels are limited, ketone bodies generated in the liver and lactate derived from exercising skeletal muscle can also become important energy substrates for the brain. In neurodegenerative disorders of ageing, brain glucose metabolism deteriorates in a progressive, region-specific and disease-specific manner - a problem that is best characterized in Alzheimer disease, where it begins presymptomatically. This Review discusses the status and prospects of therapeutic strategies for countering neurodegenerative disorders of ageing by improving, preserving or rescuing brain energetics. The approaches described include restoring oxidative phosphorylation and glycolysis, increasing insulin sensitivity, correcting mitochondrial dysfunction, ketone-based interventions, acting via hormones that modulate cerebral energetics, RNA therapeutics and complementary multimodal lifestyle changes.

Brain Fuel Utilization in the Developing Brain

During pregnancy and infancy, the human brain is growing extremely fast; the brain volume increases significantly, reaching 36, 72, and 83% of the volume of adults at 2-4 weeks, 1 year, and 2 years of age, respectively, which is essential to establish the neuronal networks and capacity for the development of cognitive, motor, social, and emotional skills that will be continually refined throughout childhood and adulthood. Such dramatic changes in brain structure and function are associated with very large energetic demands exceeding by far those of other organs of the body. It has been estimated that during childhood the brain may account for up to 60% of the body basal energetic requirements. While the main source of energy for the adult brain is glucose, it appears that it is not sufficient to sustain the dramatic metabolic demands of the brain during its development. Recently, it has been proposed that this energetic challenge is solved by the ability of the brain to use ketone bodies (KBs), produced from fatty acid oxidation, as a complement source of energy. Here, we first describe the main cellular and physiological processes that drive brain development along time and how different brain metabolic pathways are engaged to support them. It has been assumed that the majority of energetic substrates are used to support neuronal activity and signal transmission. We discuss how glucose and KBs are metabolized to provide the carbon backbones used to synthesize lipids, nucleic acid, and cholesterol, which are indispensable building blocks of neuronal cell proliferation and are also used to establish and refine brain connectivity through synapse formation/elimination and myelination. We conclude that glucose and KBs are not only important to support the energy needs of the brain under development, but they are also essential substrates for the biosynthesis of macromolecules underlying structural brain growth and reorganization. We emphasize that glucose and fatty acids supporting the production of KBs are provided in complex food matrices, such as breast milk, and understanding how their availability impacts the brain will be key to promote adequate nutrition to support brain metabolism and, therefore, optimal brain development.

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.

Flow-metabolism uncoupling in patients with asymptomatic unilateral carotid artery stenosis assessed by multi-modal magnetic resonance imaging

Oxygen extraction (OEF), oxidative metabolism (CMRO₂), and blood flow (CBF) in the brain, as well as the coupling between CMRO₂ and CBF due to cerebral autoregulation are fundamental to brain's health. We used a clinically feasible MRI protocol to assess impairments of these parameters in the perfusion territories of stenosed carotid arteries. Twenty-nine patients with unilateral high-grade carotid stenosis and thirty age-matched healthy controls underwent multi-modal MRI scans. Pseudo-continuous arterial spin labeling (pCASL) yielded absolute CBF, whereas multi-parametric quantitative blood oxygenation level dependent (mqBOLD) modeling allowed imaging of relative OEF and CMRO₂. Both CBF and CMRO₂ were significantly reduced in the stenosed territory compared to the contralateral side, while OEF was evenly distributed across both hemispheres similarly in patients and controls. The CMRO₂-CBF coupling was significantly different between both hemispheres in patients, i.e. significant interhemispheric flow-metabolism uncoupling was observed in patients compared to controls. Given that CBF and CMRO₂ are intimately linked to brain function in health and disease, the proposed easily applicable MRI protocol of pCASL and mqBOLD imaging might serve as a valuable tool for early diagnosis of potentially harmful cerebral hemodynamic and metabolic states with the final aim to select clinically asymptomatic patients who would benefit from carotid revascularization therapy.

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.

Quantitative positron emission tomography reveals regional differences in aerobic glycolysis within the human brain

Glucose and oxygen metabolism are tightly coupled in the human brain, with the preponderance of the brain's glucose supply used to generate ATP via oxidative phosphorylation. A fraction of glucose is consumed outside of oxidative phosphorylation despite the presence of sufficient oxygen to do so. We refer to this process as aerobic glycolysis. A recent positron emission tomography study reported that aerobic glycolysis is uniform within gray matter. Here, we analyze the same data and demonstrate robust regional differences in aerobic glycolysis within gray matter, a finding consistent with previously published data.

Vascular Instability and Neurological Morbidity in Sickle Cell Disease: An Integrative Framework

It is well-established that patients with sickle cell disease (SCD) are at substantial risk of neurological complications, including overt and silent stroke, microstructural injury, and cognitive difficulties. Yet the underlying mechanisms remain poorly understood, partly because findings have largely been considered in isolation. Here, we review mechanistic pathways for which there is accumulating evidence and propose an integrative systems-biology framework for understanding neurological risk. Drawing upon work from other vascular beds in SCD, as well as the wider stroke literature, we propose that macro-circulatory hyper-perfusion, regions of relative micro-circulatory hypo-perfusion, and an exhaustion of cerebral reserve mechanisms, together lead to a state of cerebral vascular instability. We suggest that in this state, tissue oxygen supply is fragile and easily perturbed by changes in clinical condition, with the potential for stroke and/or microstructural injury if metabolic demand exceeds tissue oxygenation. This framework brings together recent developments in the field, highlights outstanding questions, and offers a first step toward a linking pathophysiological explanation of neurological risk that may help inform future screening and treatment strategies.

Brain Glucose Metabolism: Integration of Energetics with Function

Glucose is the long-established, obligatory fuel for brain that fulfills many critical functions, including ATP production, oxidative stress management, and synthesis of neurotransmitters, neuromodulators, and structural components. Neuronal glucose oxidation exceeds that in astrocytes, but both rates increase in direct proportion to excitatory neurotransmission; signaling and metabolism are closely coupled at the local level. Exact details of neuron-astrocyte glutamate-glutamine cycling remain to be established, and the specific roles of glucose and lactate in the cellular energetics of these processes are debated. Glycolysis is preferentially upregulated during brain activation even though oxygen availability is sufficient (aerobic glycolysis). Three major pathways, glycolysis, pentose phosphate shunt, and glycogen turnover, contribute to utilization of glucose in excess of oxygen, and adrenergic regulation of aerobic glycolysis draws attention to astrocytic metabolism, particularly glycogen turnover, which has a high impact on the oxygen-carbohydrate mismatch. Aerobic glycolysis is proposed to be predominant in young children and specific brain regions, but re-evaluation of data is necessary. Shuttling of glucose- and glycogen-derived lactate from astrocytes to neurons during activation, neurotransmission, and memory consolidation are controversial topics for which alternative mechanisms are proposed. Nutritional therapy and vagus nerve stimulation are translational bridges from metabolism to clinical treatment of diverse brain disorders.