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Biondetti, E.

Publications and source records attributed to Biondetti, E..

4 recordsLinked to original sources

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↗

Three-dimensional T1 mapping demonstrates the transfer of oxygen into cerebrospinal fluid during hyperoxia

BackgroundThis study optimised a non-invasive magnetic resonance imaging technique to investigate the transfer of oxygen into cerebrospinal fluid (CSF) across the whole brain of healthy subjects. MethodsA shortening of the T1 (longitudinal relaxation time) of CSF was induced by 100% hyperoxia and measured using a 3D SPACE sequence at 3T in 29 subjects, thereby demonstrating the diffusion of oxygen from blood to CSF. T1 mapping was performed at high resolution (0.9-mm isotropic, taking approximately 16 minutes) to capture anatomical details of the CSF spaces and was also repeated more rapidly at a lower resolution (3-mm isotropic, taking approximately 3.5 minutes) to capture the temporal dynamics of T1 changes. ResultsSignificant region-dependent reductions in T1 were observed, indicating increased oxygen concentration in CSF. These occurred most prominently and rapidly in the cortical subarachnoid space and basilar cisterns, stabilising between 7 and 10 minutes after initiating hyperoxia, suggesting that oxygen diffusion primarily occurs via pial arteries and arteries at the base of the skull, both of which are in proximity to CSF-filled spaces. Over a timescale of 16 minutes, smaller T1 changes, only observed on the high-resolution T1 maps, occurred in the posterior lateral ventricles, where the choroid plexus is found, and the cisterna magna, possibly because of mixing effects with the adjacent basilar cisterns. ConclusionsThis study provides insights into the structure of CSF and dynamics of blood-CSF oxygen exchange, including their regional dependence. Moreover, the methodology presented here could, in the future, offer a valuable tool for characterising the passive diffusion of oxygen across cerebral blood vessel walls (i.e., their oxygen permeability), thereby providing a potential marker of cerebrovascular integrity.

physiology↗

Comparing the Accuracy and Precision of Multi-echo Combination Methods for Quantitative Susceptibility Mapping Using Laplacian-Based Methods at 3 T

PurposeTo compare different multi-echo combination methods for MRI quantitative susceptibility mapping (QSM). Given the current lack of consensus, we aimed to elucidate how to optimally combine multi-echo gradient-recalled echo (GRE) signal phase information, either before or after applying Laplacian-base methods (LBMs) for phase unwrapping or background field removal. MethodsMulti-echo GRE data were simulated in a numerical head phantom, and multiecho GRE images were acquired at 3 T in ten healthy volunteers. To enable image-based estimation of GRE signal noise, five volunteers were scanned twice in the same session without repositioning. Five QSM processing pipelines were designed: one applied nonlinear phase fitting over echo times (TEs) before LBMs; two applied LBMs to the TE-dependent phase and then combined multiple TEs via either TE-weighted or signal-to-noise ratio (SNR)-weighted averaging; two calculated TE-dependent susceptibility maps via either multi-step or single-step QSM and then combined multiple TEs via magnitude-weighted averaging. Results from different pipelines were compared using visual inspection; summary statistics of susceptibility in deep gray matter, white matter, and venous regions; phase noise maps (error propagation theory); and, in the healthy volunteers, regional fixed bias analysis (Bland-Altman) and regional differences between the means (nonparametric tests). ResultsNonlinearly fitting the multi-echo phase over TEs before applying LBMs provided the highest regional accuracy of{chi} and the lowest phase noise propagation compared to averaging the LBM-processed TE-dependent phase. This result was especially pertinent in high-susceptibility venous regions. ConclusionFor multi-echo QSM, we recommend combining the signal phase by nonlinear fitting before applying LBMs.

neuroscience↗

Investigating the Effect of Flow Compensation and Quantitative Susceptibility Mapping Method on the Accuracy of Venous Susceptibility Measurement

Quantitative susceptibility mapping (QSM) is a promising non-invasive method for obtaining information relating to the oxygen metabolism. However, the optimal acquisition sequence and QSM reconstruction method for reliable venous susceptibility measurements are unknown. Full flow compensation is generally recommended to correct for the influence of venous blood flow, although the effect of flow compensation on the accuracy of venous susceptibility values has not been systematically evaluated. In this study, we investigated the effect of different acquisition sequences, including different flow compensation schemes, and different QSM reconstruction methods on venous susceptibilities. Ten healthy subjects were scanned with five or six distinct QSM sequence designs implementing different flow compensation schemes. All data sets were processed using six different QSM pipelines and venous blood susceptibility was evaluated in whole-brain segmentations of the venous vasculature and single veins. The quality of vein segmentations and the accuracy of venous susceptibility values were analyzed and compared between all combinations of sequences and QSM methods. The influence of the QSM method on average venous susceptibility values was found to be 2.7 - 11.6 times greater than the influence of the acquisition sequence, including flow compensation. The majority of the investigated QSM reconstruction methods tended to underestimate venous susceptibility values in the vein segmentations that were obtained. Using multi-echo gradient-echo acquisitions with monopolar readout gradients, we found that sequences without full flow compensation yielded venous susceptibility values comparable to sequences with full flow compensation. However, the QSM method had a great influence on susceptibility values and thus needs to be considered carefully for accurate venous QSM.

neuroscience↗