Biology subjects

Fasano, F.

Publications and source records attributed to Fasano, F..

10 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↗

bioRxiv2026

Open-Source Framework for Measurement of the Gradient Impulse Response Function

The Gradient Impulse Response Function (GIRF) is widely used to model and correct gradient system imperfections in MRI, but scanner-specific GIRF measurement remains inaccessible to many research groups because existing approaches rely on specialised field monitoring hardware or fragmented and non-reproducible software workflows. To address this limitation, an open-source, end-to-end framework for phantom-based GIRF measurement is presented, providing a reproducible workflow requiring only standard MRI hardware and a spherical water phantom. The framework integrates vendor-independent pulse sequence generation, phantom-based data acquisition, automated data processing, and GIRF estimation. The framework was validated by comparing GIRF-predicted non-Cartesian k-space trajectories with independent measurements acquired using NMR field probes, which served as the gold-standard for trajectory characterization. Accurate prediction of rosette and spiral trajectories was demonstrated across multiple imaging orientations, with substantially lower trajectory error than the corresponding nominal trajectories. By providing the first openly available end-to-end implementation for phantom-based GIRF measurement, the barrier to routine scanner-specific GIRF characterisation is reduced, facilitating broader adoption of GIRF-based methods across the MRI community.

bioengineering↗

bioRxiv2025

Cardiac diffusion kurtosis imaging in the human heart in vivo using 300mT/m gradients

PurposeDiffusion tensor imaging (DTI) is commonly used in cardiac diffusion magnetic resonance imaging (dMRI). However, the tissues microstructure (cells, membranes, etc.) restricts the movement of the water molecules, making the spin displacements deviate from Gaussian behaviour. This effect may be observed with diffusion kurtosis imaging (DKI) using sufficiently high b-values (b > 450 s/mm2), which are presently outside the realm of routine cardiac dMRI due to the limited gradient strength of clinical scanners. The Connectom scanner with Gmax = 300 mT/m enables high b-values at echo times (TE) similar to DTI on standard clinical scanners, therefore facilitating cardiac DKI in humans. MethodsCardiac-gated, second-order motion-compensated dMRI was performed with bmax = 1350 s/mm2 in 10 healthy volunteers on a 3T MRI scanner with Gmax = 300 mT/m. The signal was fitted to a cumulant expansion up to and including the kurtosis term and diffusion metrics such as fractional anisotropy (FA), mean diffusivity (MD), mean kurtosis (MK), axial kurtosis (AK), and radial kurtosis (RK) were calculated. ResultsWe demonstrate deviation of the signal from monoexponential decay for b-values > 450 s/mm2 (MK = 0.32 {+/-} 0.03). Radial kurtosis (RK = 0.35 {+/-} 0.04) was observed slightly larger than axial kurtosis (AK = 0.27 {+/-} 0.02), and the difference is statistically significant (RK - AK = 0.08 {+/-} 0.04, p = 2e - 4). ConclusionThis work demonstrates the feasibility of quantifying kurtosis effect in the human heart in vivo (at an echo time shorter than typical TEs reported for cardiac DTI), using high-performance gradient systems (which are 4-8 times stronger than on standard clinical scanners). Our work lays the foundation for exploring new biomarkers in cardiac dMRI beyond DTI.

biophysics↗

bioRxiv2021

Multi-compartment analysis of the complex gradient-echo signal quantifies myelin breakdown in premanifest Huntington's disease

White matter (WM) alterations have been identified as a relevant pathological feature of Huntingtons disease (HD). Increasing evidence suggests that WM changes in this disorder are due to alterations in myelin-associated biological processes. Multi-compartmental analysis of the complex gradient-echo MRI signal evolution in WM has been shown to quantify myelin in vivo, therefore pointing to the potential of this technique for the study of WM myelin changes in health and disease. This study first characterized the reproducibility of metrics derived from the complex multi-echo gradient-recalled echo (mGRE) signal across the corpus callosum in healthy participants, finding highest reproducibility in the posterior callosal segment. Subsequently, the same analysis pipeline was applied in this callosal region in a sample of premanifest HD patients (n = 19) and age, sex and education matched healthy controls (n = 21). In particular, we focused on two myelin-associated derivatives: i. the myelin water signal fraction (fm), a parameter dependent on myelin content; and ii. the difference in frequency between myelin and intra-axonal water pools ({Delta}{omega}), a parameter dependent on the ratio between the inner and the outer axonal radii. fm was found to be lower in HD patients ({beta} = -0.13, p = 0.03), while {Delta}{omega} did not show a group effect. Performance in tests of working memory, executive function, social cognition and movement was also assessed, and a greater age-related decline in executive function was detected in HD patients ({beta} = -0.06, p = 0.006), replicating previous evidence of executive dysfunction in HD. Finally, the correlation between fm, executive function, and proximity to disease onset was explored in patients, and a positive correlation between executive function and fm was detected (r = 0.542; p = 0.02). This study emphasises the potential of complex mGRE signal analysis for aiding understanding of HD pathogenesis and progression. Moreover, expanding on evidence from pathology and animal studies, it provides novel in vivo evidence supporting myelin breakdown as an early feature of HD.

neuroscience↗

bioRxiv2021

Measuring arterial pulsatility with Dynamic Inflow MAgnitude Contrast (DIMAC)

The pulsatility of blood flow through cerebral arteries is clinically important, as it is intrinsically associated with cerebrovascular health. In this study we outline a new MRI approach to measuring the real-time pulsatile flow in cerebral arteries, which is based on the inflow phenomenon associated with fast gradient-recalled-echo acquisitions. Unlike traditional phase-contrast techniques, this new method, which we dub Dynamic Inflow Magnitude Contrast (DIMAC), does not require velocity-encoding gradients as sensitivity to flow velocity is derived purely from the inflow effect. We achieved this using a highly accelerated single slice EPI acquisition with a very short TR (15 ms) and a 90{degrees} flip angle, thus maximizing inflow contrast. We simulate the spoiled GRE signal in the presence of large arteries and perform a sensitivity analysis to demonstrate that in the regime of high inflow contrast it shows much greater sensitivity to flow velocity over blood volume changes. We support this theoretical prediction with in-vivo data collected in two separate experiments designed to demonstrate the utility of the DIMAC signal contrast. We perform a hypercapnia challenge experiment in order to experimentally modulate arterial tone within subjects, and thus modulate the arterial pulsatile flow waveform. We also perform a thigh-cuff release challenge, designed to induce a transient drop in blood pressure, and demonstrate that the continuous DIMAC signal captures the complex transient change in the pulsatile and non-pulsatile components of flow. In summary, this study proposes a new role for a well-established source of MR image contrast and demonstrates its potential for measuring both steady-state and dynamic changes in arterial tone. HighlightsO_LIWe present a novel method for measuring pulsatility of cerebral arteries. C_LIO_LIThe inflow effect on fast GRE imaging can be exploited to yield a flow velocity dependent signal. C_LIO_LIWe measure pulsatile flow through cerebral arteries dynamically on a beat-to-beat basis. C_LIO_LIWe use physiological challenges to demonstrate sensitivity to dynamic and steady-state changes in vascular tone. C_LI

bioengineering↗

bioRxiv2020

Most small cerebral cortical veins demonstrate significant flow pulsatility: a human phase contrast MRI study at 7T

Phase contrast MRI has been used to investigate flow pulsatility in cerebral arteries, larger cerebral veins and the cerebrospinal fluid. Such measurements of intracranial pulsatility and compliance are beginning to inform understanding of the pathophysiology of conditions including normal pressure hydrocephalus, multiple sclerosis and dementias. We demonstrate the presence of flow pulsatility in small cerebral cortical veins, for the first time using phase contrast MRI at 7 Tesla, with the aim of improving our understanding of the haemodynamics of this little-studied vascular compartment. An automated method for establishing where venous flow is pulsatile is introduced, revealing significant pulsatility in 116 out of 146 veins, across 8 healthy participants, assessed in parietal and frontal regions. Distributions of pulsatility index and pulse waveform delay were characterized, indicating a small, but statistically significant (p<0.05), delay of 59{+/-}41 ms in cortical veins with respect to the superior sagittal sinus, but no differences between veins draining different arterial supply territories. Measurements of pulsatility in smaller cortical veins, a hitherto unstudied compartment closer to the capillary bed, could lead to a better understanding of intracranial compliance and cerebrovascular (patho)physiology.

neuroscience↗

bioRxiv2019

Genetic risk of dementia modifies the impact of obesity on limbic white matter and spatial navigation behavior in cognitively healthy adults.

A family history (FH) of dementia, APOE-{varepsilon}4 genotype, and obesity are major risk factors for developing Alzheimers disease but their combined effects on the brain and cognition remain elusive. We tested the hypothesis that these risk factors affect apparent white matter (WM) myelin and cognition including spatial navigation and processing speed in 166 asymptomatic individuals (38-71 years). Microstructure in temporal [fornix, parahippocampal cingulum, uncinate fasciculus], motor and whole-brain WM was assessed with myelin-sensitive indices from quantitative magnetization transfer [macromolecular proton fraction (MPF)] and axon density from diffusion imaging. Individuals with the highest genetic risk (FH+ and APOE-{varepsilon}4) compared to those with FH+ alone showed obesity-related reductions in MPF and axon density in the right parahippocampal cingulum. No effects were present for those without FH. Furthermore, FH modulated obesity-related effects on spatial navigation behaviour. In summary, an individuals genetic dementia risk influenced the impact of obesity on WM myelin and cognition.

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↗

bioRxiv2018

The causal structure of age-dependent limbic decline: fornix white matter glia damage causes hippocampal grey matter damage, not vice versa.

Aging leads to gray and white matter decline but their causation remains unclear. We explored two broad classes of models of age and dementia risk related brain changes. The first class of models emphasises the importance of gray matter: age and risk-related processes cause neurodegeneration and this causes damage in associated white matter tracts. The second class of models reverses the direction of causation: aging and risk factors cause white matter damage and this leads to gray matter damage. We compared these models with linear mediation analysis and quantitative multi-modal MRI indices (from diffusion, quantitative magnetization transfer and relaxometry imaging) of tissue properties in two limbic structures implicated in age-related memory decline: the hippocampus and the fornix in 166 asymptomatic individuals (aged 38 - 71 years). Aging was associated with apparent glia but not axon density damage in the fornix. Mediation analysis unambiguously supported white matter damage causing gray matter decline; controlling for fornix glia damage, the correlation between age and hippocampal damage disappears, but not vice versa. Fornix and hippocampal tissue loss were both associated with reductions in episodic memory performance. The implications of these findings for neuroglia and neurodegenerative models of aging and late onset dementia are discussed.

neuroscience↗

bioRxiv2018

Adipokines contribute to central-obesity related reductions in myelin-sensitive MRI indices in the fornix.

Midlife obesity is a risk factor of late onset Alzheimers disease (LOAD) but why this is the case remains unknown. As systemic inflammation is involved in both conditions, one possibility is that obesity-related neuroinflammation may contribute to the development of LOAD. Neuroinflammation is closely linked to white matter myelin loss, and this can be measured in vivo with quantitative magnetization transfer (qMT) imaging. Here, we investigated whether differences in obesity measures, i.e., in Waist Hip Ratio (WHR), abdominal visceral and subcutaneous fat volume fractions and Body Mass Index (BMI), were associated with reductions in qMT indices of apparent myelin in temporal white matter pathways involved in LOAD (i.e., the fornix, the parahippocampal cingulum and the uncinate fasciculus compared with whole brain and cortico-spinal white matter) in 166 cognitively healthy individuals (38-71 years of age). Obesity-related effects on myelin-sensitive markers were contrasted with differences in apparent axon density from dual-shell diffusion Neurite Orientation Dispersion and Density Imaging (NODDI). Differences in WHR and in visceral fat volume fractions were negatively correlated with differences in qMT estimates of apparent myelin and tissue metabolism in the fornix but not with any other microstructural components. These correlations were not explained by demographic (age, sex, education), health (hypertension, alcohol consumption, sedentary lifestyle) or genetic (APOE genotype, family history of dementia) risk factors of LOAD. Furthermore, differences in the ratio of plasma concentrations of leptin and adiponectin were also positively correlated with differences in C-Reactive Protein concentrations, and contributed significantly to the correlations between central obesity and myelin-sensitive metrics in the fornix. These results are consistent with the view that visceral fat-related chronic inflammation may damage white matter myelin in limbic regions, known to be vulnerable to LOAD pathology.

neuroscience↗