Biology subjects

Tomassini, V.

Publications and source records attributed to Tomassini, V..

4 recordsLinked to original sources

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↗

bioRxiv2019

Tractography in the presence of white matter lesions in multiple sclerosis

Accurate anatomical localisation of specific white matter tracts and the quantification of their tractspecific microstructural damage in multiple sclerosis (MS) can contribute to a better understanding of symptomatology, disease progression and intervention effects. Diffusion MRI-based tractography is being used increasingly to segment white matter tracts as regions-of-interest for subsequent quantitative analysis. Since MS lesions can interrupt the tractography algorithms tract reconstruction, clinical studies frequently resort to atlas-based approaches, which are convenient but ignorant to individual variability in tract size and shape. Here, we revisit the problem of individual tractography in MS, comparing tractography algorithms using: (i) The diffusion tensor framework; (ii) constrained spherical deconvoution (CSD); and (iii) damped Richardson-Lucy (dRL) deconvolution. Firstly, using simulated and in vivo data from 29 MS patients and 19 healthy controls, we show that the three tracking algorithms respond differentially to MS pathology. While the tensor-based approach is unable to deal with crossing fibres, CSD produces spurious stream-lines, in particular in tissue with high fibre loss and low diffusion anisotropy. With dRL, streamlines are increasingly interrupted in pathological tissue. Secondly, we demonstrate that despite the effects of lesion on the fibre orientation reconstruction algorithms, fibre tracking algorithms are still able to segment tracts that pass areas with high prevalence of lesions. Combining dRL-based tractography with an automated tract segmentation tool on data from 131 MS patients, the corticospinal tracts and arcuate fasciculi were successfully reconstructed in more than 90% of individuals. Comparing tractspecific microstructural parameters (fractional anisotropy, radial diffusivity and magnetisation transfer ratio) in individually segmented tracts to those from a tract probability map, we showed that there is no systematic disease-related bias in the individually reconstructed tracts, suggesting that lesions and otherwise damaged parts are not systematically omitted during tractography. Thirdly, we demonstrate modest anatomical correspondence between the individual and tract probability-based approach, with a spatial overlap between 35 and 55%. Correlations between tract-averaged microstructural parameters in individually segmented tracts and the probability-map approach ranged between r = .52 (p < .001) for radial diffusivity in the right cortico-spinal tract and r = .97 (p < .001) for magnetization transfer ratio in the arcuate fasciculi. Our results show that MS white matter lesions impact fibre orientation reconstructions but this does not appear to hinder the ability to anatomically localise white matter tracts in MS. Individual tract segmentation in MS is feasible on a large scale and could prove a powerful tool for investigating diagnostic and prognostic markers.

neuroscience↗

bioRxiv2019

Assessment of the effects of aerobic fitness on cerebrovascular function in young adults using multiple inversion time arterial spin labelling MRI

The cross-sectional study investigated the effects of aerobic fitness on cerebrovascular function in the healthy brain. We quantified grey matter (GM) cerebral blood flow (CBF) and cerebrovascular reactivity (CVR), in a sample of young adults within a normal fitness range. Based on existing TCD and fMRI evidence, we predicted a positive relationship between fitness and resting GM CBF, and CVR. Exploratory hypotheses that higher [Formula] peak would be associated with higher GM volume and cognitive performance were also investigated. 20 adults underwent a [Formula] peak test and a battery of cognitive tests. All subjects underwent an MRI scan where multiple inversion time (MTI) pulsed arterial spin labelling (PASL) was used to quantify resting CBF and CVR to 5% CO2. ROI analysis showed a non-significant negative correlation between whole-brain GM CBF and [Formula] peak; r=-0.4, p=0.08, corrected p (p) =0.16 and a significant positive correlation between [Formula] peak and voxelwise whole-brain GM CVR; r=0.62, p=0.003, p =0.006. Voxelwise analysis revealed a significant inverse association between [Formula] peak and resting CBF in the left and right thalamus, brainstem, right lateral occipital cortex, left intracalcarine cortex and cerebellum. The results of this study suggest that aerobic fitness is associated with lower CBF and greater CVR in young adults.

neuroscience↗

bioRxiv2019

Cerebral Metabolic Changes during Visuomotor Adaptation Assessed using Quantitative FMRI

The neural energetics underlying functional brain plasticity have not been thoroughly investigated in the healthy human brain. A better understanding of the blood flow and metabolism changes underlying plasticity will help us to address pathologies in which plasticity is compromised and, with interventions, could be enhanced for patient benefit. Calibrated fMRI was conducted in 20 healthy participants during performance of a serial reaction time task which induces rapid motor adaptation. Regions of interest (ROIs) were defined from areas showing linearly decreasing task-induced BOLD and CBF responses. BOLD, CBF and relative CMRO2 responses were calculated for each block of the task. The flow-metabolism coupling ratio, n, was also calculated for each ROI. Increases from baseline in BOLD, CBF and CMRO2 were observed in multiple brain regions including the motor and sensorimotor cortices, cerebellum and hippocampus during SRT task performance, as well as changes in the response amplitude from early to late task blocks reflecting task adaptation. CMRO2 responses on average decreased faster than BOLD or CBF responses, potentially due to rapid neural adaptation. However, the mean flow-metabolism coupling ratio was not significantly different between ROIs or across blocks. Calibrated fMRI can be used to study energetic changes during learning in the healthy brain and could be used to investigate the vascular and metabolic changes underlying reductions in plasticity in ageing and disease.

neuroscience↗