Biology subjects

Germuska, M.

Publications and source records attributed to Germuska, M..

7 recordsLinked to original sources

bioRxiv2026

Human brain cortical oxygen consumption is positively related to soma surface area density.

Evidence from in-silico, ex vivo and invasive animal studies suggested the function of neural tissue to be inextricably linked to its structural and microstructural organization. However, this link has never been assessed non-invasively in humans. Here, we established a simple quantitative framework linking cerebral oxygen metabolism to gray matter microstructural features in healthy humans using advanced non-invasive MRI methods. The cerebral metabolic rate of oxygen consumption (CMRO2) was quantified with calibrated fMRI, whereas microstructural properties were estimated from diffusion MRI data fitted to the Soma and Neurite Density Imaging (SANDI) model, yielding soma radius (R soma) and soma volume fraction (fsoma) metrics, from which we derived maps of soma surface area density (SAD) and soma numerical density (ND) under the assumption of a spherical soma. CMRO2 was positively associated with SAD (r = 0.29, p < 0.01), fsoma (r = 0.28, p < 0.05) and ND (r = 0.25, p < 0.05), and negatively associated with Rsoma (r = -0.23, p < 0.05) across cortical brain regions. These relationships are consistent with predictions from experimental and theoretical studies, providing the first quantitative evidence that cerebral metabolic demand is coupled to microstructure in humans. The positive association of energy consumption with SAD is consistent with the notion that both the number of synapses (energy-demanding structures), and the energy required to maintain a membrane potential, scale with soma surface area. Our findings establish a non-invasive MRI framework for investigating the microstructural determinants of brain energy metabolism in health and potentially in disease.

neuroscience↗

bioRxiv2024

Endocrine modulation of cortical and retinal blood flow across the menstrual cycle

The ovarian hormones, oestrogen and progesterone, have vaso- and neuroprotective effects, likely due to interactions with the cerebrovascular system. This study investigates their neuroendocrine influence on a range of cerebral and retinal vascular functions across a healthy menstrual cycle. Twenty-six healthy, menstruating females completed imaging sessions and assessment of circulating hormone levels during their early follicular, late follicular, and mid-luteal phase (1-4, 10-12 and 20-22 days after menses onset). Cerebral blood flow (CBF), arterial arrival time (AAT), global oxygen extraction fraction (OEF), cerebrovascular metabolic rate of oxygen (CMRO2), carotid artery radius and carotid pulsatility index (PI) were measured using 3T MRI. Retinal vessel density and blood flow resistance were assessed with optical coherence tomography angiography (OCT-A). Assessed with linear models, increased oestradiol was related to increased global CBF ({chi}2(1)=41.682; p=1.074x10-10). An independent progesterone increase was also associated with increased global CBF ({chi}2(1)=14.979; p=0.0001). In the retina, a relationship was found between oestradiol and decreased retinal blood flow resistance ({chi}2(1)=5.28; p=0.0215), which was primarily driven by centrally localised vessels. This study finds that circulating oestrogen increases blood flow in the eye and brain, while progesterone significantly impacts the brain alone. These effects suggest a potential pathway for neuroprotective mechanisms.

neuroscience↗

bioRxiv2024

Velocity-selective arterial spin labelling bolus duration measurements: Implications for consensus recommendations

Velocity-selective arterial spin labelling (VSASL) MRI is insensitive to arterial transit time. This is an advantage over other perfusion measurements, where long arterial transit times can lead to bias. Therefore, VSASL can be used to study perfusion in the presence of long arterial transit times, such as in the ageing brain, in vascular pathologies, and cancer, or where arterial transit time changes, such as during measurement of cerebrovascular reactivity (CVR). However, when calculating perfusion (cerebral blood flow, CBF, in the brain) from VSASL signal, it is assumed that images are acquired before the trailing edge of the labelled blood has arrived in the imaging slice. The arrival of the trailing edge of the labelled bolus of blood will cause an underestimation of perfusion. Here we measure bolus duration in young, healthy human brains, both at rest and during elevated CBF. Grey matter bolus duration was 1.61 {+/-} 0.31 s, but there was a large spatial heterogeneity, with bolus duration being lower in anterior brain regions, with some areas having bolus duration < 1.2 s. We place these results in context of recommendations from a recent consensus paper, which recommends imaging 1.4 s after the label, potentially underestimating CBF in anterior regions. Further, we observed a 0.23 {+/-} 0.12 s reduction in grey matter bolus duration with 5% CO2 inhalation. These results can be used to inform the experimental design of future VSASL studies, to avoid underestimating perfusion by imaging after the arrival of the trailing edge of the labelled bolus.

neuroscience↗

bioRxiv2024

Imaging brain vascular function in Cystic Fibrosis: an MRI study of cerebral blood flow and brain oxygenation

Cystic fibrosis (CF) is a progressive inherited disorder that primarily affects the lungs. With recent breakthroughs in effective treatments for CF that increase life-expectancy, a higher prevalence of age-related comorbidities have been reported including cardiovascular disease, stroke and cognitive decline. Despite the known relationship between cardiovascular health and cerebrovascular function, very little is known about brain blood flow and oxygen metabolism in patients with CF (PwCF). In 14 PwCF and 56 healthy age / sex matched controls, we used pseudo-continuous arterial spin labelling (pCASL) to quantify cerebral perfusion in grey-matter and T2-Relaxation-Under-Spin-Tagging (TRUST) to estimate global oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen consumption (CMRO2). Compared to healthy controls, PwCF showed elevated CMRO2 (p = 0.015). There were no significant between-group differences in grey-matter CBF (p = 0.342), or whole brain OEF (p = 0.091). However, regional analysis showed certain areas with higher CBF in PwCF (p < .05, FDR). This is the first study to characterise cerebrovascular function and brain oxygen metabolism in PwCF. Our findings highlight the need for early cardiovascular monitoring procedures to help maintain cerebrovascular function and combat accelerated aging effects in the brains of PwCF.

neuroscience↗

bioRxiv2021

Quantitative mapping of cerebral oxygen metabolism using breath-hold calibrated fMRI

Magnetic resonance imaging (MRI) offers the possibility to non-invasively map the rate of cerebral metabolic oxygen consumption (CMRO2), which is essential for understanding and monitoring neural function in both health and disease. Existing methods of mapping CMRO2, based on respiratory modulation of arterial spin labelling (ASL) and blood oxygen level dependent (BOLD) signals, require lengthy acquisitions and independent modulation of both arterial oxygen and carbon dioxide levels. Here, we present a new simplified method for mapping the rate of cerebral oxygen metabolism that can be performed using a simple breath-holding paradigm. The method incorporates flow-diffusion modelling of oxygen transport and physiological constraints to create a non-linear mapping between the maximum BOLD signal, M, baseline blood flow (CBF0), and CMRO2. A gradient boosted decision tree is used to learn this mapping directly from simulated MRI data. Modelling studies demonstrate that the proposed method is robust to variation in cerebral physiology and metabolism. This new gas-free methodology offers a rapid and pragmatic alternative to existing dual-calibrated methods, removing the need for specialist respiratory equipment and long acquisition times. In-vivo testing of the method, using an 8-minute 45 second protocol of repeated breath-holding, was performed on 15 healthy volunteers, producing quantitative maps of cerebral blood flow (CBF), oxygen extraction fraction (OEF), and CMRO2.

neuroscience↗

bioRxiv2021

Using dual-calibrated functional MRI to map brain oxygen supply and consumption in multiple sclerosis

Evidence suggests that cerebrovascular function and oxygen consumption are altered in multiple sclerosis (MS). Here, we quantified the vascular and oxygen metabolic MRI burden in patients with MS (PwMS) and assessed the relationship between these MRI measures of and metrics of damage and disability. In PwMS and in matched healthy volunteers, we applied a newly developed dual-calibrated fMRI method of acquisition and analysis to map grey matter (GM) cerebral blood flow (CBF), oxygen extraction fraction (OEF), cerebral metabolic rate of oxygen consumption (CMRO2) and effective oxygen diffusivity of the capillary network (DC). We also quantified physical and cognitive function in PwMS and controls. There was no significant difference in GM volume between 22 PwMS and 20 healthy controls (p=0.302). Significant differences in CBF (PwMS vs. controls: 44.91 {+/-} 6.10 vs. 48.90 {+/-} 5.87 ml/100g/min, p=0.010), CMRO2 (117.69 {+/-} 17.31 vs. 136.49 {+/-} 14.48 mol/100g/min p<0.001) and DC (2.70 {+/-} 0.51 vs. 3.18 {+/-} 0.41 mol/100g/mmHg/min, p=0.002) were observed in the PwMS. No significant between-group differences were observed for OEF (PwMS vs. controls: 0.38 {+/-} 0.09 vs. 0.39 {+/-} 0.02, p=0.358). Regional analysis showed widespread reductions in CMRO2 and DC for PwMS compared to healthy volunteers. There was a significant correlation between physiological measures and T2 lesion volume, but no association with current clinical disability. Our findings demonstrate concurrent reductions in oxygen supply and consumption in the absence of an alteration in oxygen extraction that may be indicative of a reduced demand for oxygen (O2), an impaired transfer of O2 from capillaries to mitochondria, and/or a reduced ability to utilise O2 that is available at the mitochondria. With no between-group differences in GM volume, our results suggest that changes in brain physiology may precede MRI-detectable GM loss and thus may be one of the pathological drivers of neurodegeneration and disease progression.

neuroscience↗

bioRxiv2019

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 brains 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.

neuroscience↗