Biology subjects

Pizzolato, M.

Publications and source records attributed to Pizzolato, M..

10 recordsLinked to original sources

bioRxiv2026

Quantitative MRI-based assessment of the ultrastructural compactness of myelin lamellae

Efficient neuronal communication relying on rapid saltatory conduction depends not only on the amount of myelin wrapping axons but also on myelin compact organisation. Yet, current quantitative MRI myelin imaging methods, such as Myelin Water Imaging (MWI) and quantitative Magnetization Transfer (qMT), are designed to estimate myelin content and are often treated as interchangeable, overlooking myelin organisation. We introduce Structural Myelin Integrity (SMI), a quantitative MRI metric designed to distinguish myelin compact organisation from content. SMI combines the distinct biophysical sensitivities of MWI and qMT to separate the water confined between myelin layers from the total myelin membrane mass. We evaluated SMI in two rodent models of myelin decompaction and one remyelination model, validating our findings with synchrotron small-angle X-ray scattering and electron microscopy. SMI detected myelin layers decompaction despite largely preserved myelin membranes, revealing structural abnormalities that were not explained by myelin content alone. During remyelination, SMI returned closer to healthy values at early timepoints than myelin-content metrics, consistent with the formation of thin-but-compact sheaths. These findings indicate that myelin content and organisation can dissociate and establish SMI as a non-invasive marker of myelin organisation, compatible with existing clinical MRI approaches for studying white matter changes not detected today.

neuroscience↗

bioRxiv2026

Mapping 3D tissue orientation with tensor-augmented light-sheet microscopy

Mapping the three-dimensional directional organization of biological tissues is essential for understanding their structure and function. However, existing methods cannot resolve micrometer-scale orientation in volumetric samples. We introduce tensor light-sheet scattering microscopy (tLSSM), a label-free method that reconstructs 3D fiber orientations at micrometer resolution in optically cleared tissues, enabling whole-organ imaging. We discovered that even in transparent samples, organized structures such as neural fibers scatter light in directional patterns, consistent with models of light scattering by cylinders. We compared tLSSM against diffusion MRI in the mouse brain, demonstrating strong agreement and orders of magnitude superior spatial resolution. Furthermore, we showcase tLSSMs versatility across diverse contexts, including whole-brain label-free tracing, pathological demyelination lesions, heart tissue, peripheral nerves, and human white matter. By enabling whole-organ fiber orientation mapping compatible with standard light-sheet microscopes, tLSSM establishes a new standard for mesoscopic connectivity studies by mapping tissue architecture beyond the limits of traditional sectioning.

neuroscience↗

bioRxiv2026

Encoder-based Curvature-Aware Regularization for estimating asymmetric fiber orientation distribution functions in diffusion MRI

Diffusion-weighted magnetic resonance imaging (dMRI) is used to study white matter microstructure and to delineate pathways by estimating fiber orientation distributions (FODs). Symmetric FODs represent the conventional model assuming antipodal symmetry in water diffusion. However, in complex regions with bending, branching or fanning fibers, this assumption is not guaranteed. To better capture such underlying fibers geometries, asymmetric FODs (A-FODs), derived from neighboring FODs, have been introduced. Here, we propose an Encoder-based Curvature-Aware Regularization (EnCAR) method for estimating A-FODs. Incorporating curvature features into the regularization weight applied to neighboring voxels improves reconstruction of A-FODs. A self-supervised Transformer network, combined with a Spherical Harmonics Semantic Encoder, learns region-specific regularization parameters from this local neighborhood to capture the diversity of fiber geometries across the brain. The EnCAR method was verified on the DiSCo challenge phantom, and applied to in vivo multi-shell Human data. The model estimated sharp, high-angular-resolution A-FODs that were well aligned with local fiber pathway. Compared with established FOD and A-FOD methods, it performed on par in regions dominated by symmetric FODs and outperformed them in complex asymmetric regions. Quantitative evaluation using the Asymmetry Index (ASI) and Model Discrepancy Index (MDI) confirmed improved consistency with the underlying diffusion signals. By ensuring smooth directional transitions, this work enhances the visibility of continuous fiber segments.

neuroscience↗

bioRxiv2023

Mapping axon diameters and conduction velocity in the rat brain - different methods tell different stories of the structure-function relationship

The structure-function relationship of nerve fibers describes an empirically determined linear relationship between axon diameter, myelin thickness (i.e., g-ratio), and conduction velocity. We investigated the structure-function relationship with different modalities in axons projecting through the corpus callosum of the rodent brain. We measured transcallosal conduction times using optogenetically evoked local field potentials (LFP) and estimated conduction velocity after measuring the callosal length with diffusion magnetic resonance imaging (dMRI) based tractography. Tractography followed the same projection as the fluorescently labeled axons in the corpus callosum. In the same animal, axon diameters were quantified using transmission electron microscopy (TEM) and dMRI. Axon distributions of TEM indicated a bimodal population, where the larger axons shrink more than the smaller ones, when comparing the modes with cryo-TEM. When applying shrinkage-correction to axon diameters from TEM of dehydrated tissue, they were better aligned with estimates from dMRI obtained in the same animal. Measured LFPs predicted axon diameters that agree with the primary mode of the axon distribution, whereas the large axons estimated by dMRI predicted latencies too short to be measured by LFPs. Different modalities show different degrees of variations, being low between animals, suggesting that the variation is methodologically dominated - not anatomically. Our results show that modalities have different sensitivity profiles to the whole axon diameter distribution. Therefore, caution must be taken when interpreting a methods prediction of a metric, as it may not represent the full but only a sub-part of the structure-function relationship of an axonal projection. Significance StatementWe acquire both functional and structural metrics, namely conduction velocity, pathway length, axon diameter, and g-ratio in the same cohort of animals. The transcallosal conduction time was obtained from electrophysiological measurements after contralateral optogenetic stimulation in the rat motor cortex. Cryo-fixation of the tissue reveals different shrinkages for different sub-populations in the diameter distribution. Measured latencies correspond to the small axonal subpopulation with diameters extending up to the mode of the distribution obtained with electron microscopy. Diffusion-MRI primarily appears sensitive to the larger axons, obtained with histology, after correcting for diameter weighting and shrinkage. Different modalities can have very different sensitivities to the structure-function relationship of an axonal projection which must be accounted for in the interpretation.

neuroscience↗

bioRxiv2023

Bridging the 3D geometrical organisation of white matter pathways across anatomical length scales and species

We used diffusion MRI and x-ray synchrotron imaging on monkey and mice brains to examine the organisation of fibre pathways in white matter across anatomical scales. We compared the structure in the corpus callosum and crossing fibre regions and investigated the differences in cuprizone-induced demyelination mouse brains versus healthy controls. Our findings revealed common principles of fibre organisation that apply despite the varying patterns observed across species; small axonal fasciculi and major bundles formed laminar structures with varying angles, according to the characteristics of major pathways. Fasciculi exhibited non-straight paths around obstacles like blood vessels, comparable across the samples of varying fibre complexity and demyelination. Quantifications of fibre orientation distributions were consistent across anatomical length scales and modalities, whereas tissue anisotropy had a more complex relationship, both dependent on the field-of-view. Our study emphasises the need to balance field-of-view and voxel size when characterising white matter features across length scales.

neuroscience↗

bioRxiv2021

Insights from the IronTract challenge: optimal methods for mapping brain pathways from multi-shell diffusion MRI

Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI data quality, it remains unclear how these data should be analyzed to maximize tractography accuracy. Over a period of two years, we have engaged the dMRI community in the IronTract Challenge, which aims to answer this question by leveraging a unique dataset. Macaque brains that have received both tracer injections and ex vivo dMRI at high spatial and angular resolution allow a comprehensive, quantitative assessment of tractography accuracy on state-of-the-art dMRI acquisition schemes. We find that, when analysis methods are carefully optimized, the HCP scheme can achieve similar accuracy as a more time-consuming, Cartesian-grid scheme. Importantly, we show that simple pre- and post-processing strategies can improve the accuracy and robustness of many tractography methods. Finally, we find that fiber configurations that go beyond crossing (e.g., fanning, branching) are the most challenging for tractography. The IronTract Challenge remains open and we hope that it can serve as a valuable validation tool for both users and developers of dMRI analysis methods.

neuroscience↗

bioRxiv2021

Axonal T2 estimation using the spherical variance of the strongly diffusion-weighted MRI signal

In magnetic resonance imaging, the application of a strong diffusion weighting suppresses the signal contributions from the less diffusion-restricted constituents of the brains white matter, thus enabling the estimation of the transverse relaxation time T2 that arises from the more diffusion-restricted constituents such as the axons. However, the presence of cell nuclei and vacuoles can confound the estimation of the axonal T2, as diffusion within those structures is also restricted, causing the corresponding signal to survive the strong diffusion weighting. We devise an estimator of the axonal T2 based on the directional spherical variance of the strongly diffusion-weighted signal. The spherical variance T2 estimates are insensitive to the presence of isotropic contributions to the signal like those provided by cell nuclei and vacuoles. We show that with a strong diffusion weighting these estimates differ from those obtained using the directional spherical mean of the signal which contains both axonal and isotropically-restricted contributions. Our findings hint at the presence of an MRI-visible isotropically-restricted contribution to the signal in the white matter ex vivo fixed tissue (monkey) at 7T, and do not allow us to discard such a possibility also for in vivo human data collected with a clinical 3T system.

biophysics↗

bioRxiv2021

Does powder averaging remove dispersion bias in diffusion MRI diameter estimates within real 3D axonal architectures?

Noninvasive estimation of axon diameter with diffusion MRI holds potential to investigate the dynamic properties of the brain network and pathology of neurodegenerative diseases. Recent methods use powder averaging to account for complex white matter architectures, such as fibre crossing regions, but these have not been validated for real axonal geometries. Here, we present 120 - 313 m long segmented axons from X-ray nano-holotomography volumes of a splenium and crossing fibre region of a vervet monkey brain. We show that the axons in the complex crossing fibre region, which contains callosal, association, and corticospinal connections, are larger and exhibit a wider distribution than those of the splenium region. To accurately estimate the axon diameter in these regions, therefore, sensitivity to a wide range of diameters is required. We demonstrate how the q-value, b-value, signal-to-noise ratio and the assumed intra-axonal parallel diffusivity influence the range of measurable diameters with powder average approaches. Furthermore, we show how Gaussian distributed noise results in a wider range of measurable diameter at high b-values than Rician distributed noise, even at high signal-to-noise ratios of 100. The number of gradient directions is also shown to impose a lower bound on measurable diameter. Our results indicate that axon diameter estimation can be performed with only few b-shells, and that additional shells do not improve the accuracy of the estimate. Through Monte Carlo simulations of diffusion, we show that powder averaging techniques succeed in providing accurate estimates of axon diameter across a range of sequence parameters and diffusion times, even in complex white matter architectures. At sufficiently low b-values, the acquisition becomes sensitive to axonal microdispersion and the intra-axonal parallel diffusivity shows time dependency at both in vivo and ex vivo intrinsic diffusivities.

neuroscience↗

bioRxiv2020

Tractography dissection variability: what happens when 42 groups dissect 14 white matter bundles on the same dataset?

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.

neuroscience↗

bioRxiv2018

Limits to anatomical accuracy of diffusion tractography using modern approaches

Diffusion MRI fiber tractography is widely used to probe the structural connectivity of thebrain, with a range of applications in both clinical and basic neuroscience. Despite widespread use, tractography has well-known pitfalls that limits the anatomical accuracy of this technique. Numerous modern methods have been developed to address these shortcomings through advances in acquisition, modeling, and computation. To test whether these advances improve tractography accuracy, we organized the ISBI 2018 3D Validation of Tractography with Experimental MRI (3D-VoTEM) challenge. We made available three unique independent tractography validation datasets - a physical phantom and two ex vivo brain specimens - resulting in 176 distinct submissions from 9 research groups. By comparing results over a wide range of fiber complexities and algorithmic strategies, this challenge provides a more comprehensive assessment of tractographys inherent limitations than has been reported previously. The central results were consistent across all sub-challenges in that, despite advances in tractography methods, the anatomical accuracy of tractography has not dramatically improved in recent years. Taken together, our results independently confirm findings from decades of tractography validation studies, demonstrate inherent limitations in reconstructing white matter pathways using diffusion MRI data alone, and highlight the need for alternative or combinatorial strategies to accurately map the fiber pathways of the brain.

neuroscience↗