Biology subjects

Mito, R.

Publications and source records attributed to Mito, R..

4 recordsLinked to original sources

bioRxiv2026

Longitudinal quantitative streamline tractography: robust estimation of white matter connectivity differences

Longitudinal probing of structural connectivity via diffusion magnetic resonance imaging (dMRI) is experiencing uptake. However, the detection of biological effects is significantly hampered by the limitations of cross-sectional streamline tractography, where even small changes in the dMRI signal can produce drastically different trajectories and therefore quantitative parameterisation; if not properly dealt with, such effects will manifest as spurious longitudinal change, which can obscure subtle biological differences. To overcome this challenge, we here introduce a novel quantitative streamline tractography framework tailored for longitudinal analysis, wherein an individuals streamline trajectories remain fixed throughout the analysis, allowing only their ascribed density weights to vary between sessions. We present two strategies by which these quantitative streamline weights can be determined, both extensions of the widely adopted SIFT2 method. The performance of this framework is benchmarked against cross-sectional reconstruction with and without SIFT2 optimisation, in both in silico dMRI phantoms with known ground truths and three distinct human in vivo cohorts with clear a priori expectations of biological effects. We demonstrate that the proposed framework drastically reduces methodological imprecisions in synthetic dMRI phantoms and enhances statistical sensitivity and specificity to biological effects in human cohorts, enabling robust longitudinal quantification of structural connectivity.

neuroscience↗

bioRxiv2025

TRAMFIX: TRavelling Across Melbourne for FIXel-based analysis (a reproducibility study)

Fixel-based analysis (FBA) has gained substantial interest for its ability to probe fibre-specific changes in the brains white matter from diffusion-weighted imaging data. However, the reproducibility and reliability of fixel-based measures across different scanners remains largely unknown. In this work, we present TRAMFIX: a multisite dataset of travelling participants (n=10 healthy adults) scanned across four 3T MRI scanners using a harmonised multi-shell DWI protocol. DWI data were processed using two pipelines that can adopted when performing multi-site FBA studies (site-specific versus pooled processing). We extracted fixel-based measures of fibre density (FD), fibre cross-section (FC), and fibre density and cross-section (FDC), as well as diffusion tensor imaging (DTI)-based fractional anisotropy (FA) and mean diffusivity (MD) from the harmonised protocol. Within-subject coefficients of variation (CVws) and intraclass correlation coefficients (ICC) of FBA and DTI measures were computed at multiple resolutions of computation and analysis: (i) the whole-brain averaged level, (ii) tract-level, and (iii) fixel- or voxel-level. Fixel-based metrics demonstrated high reproducibility and reliability at the whole-brain level (CVws ranging between 0.51% to 1.57% and ICC between 0.93 and 0.996). While reproducibility and reliability remained high for tract-averaged FBA measures (particularly the FC and FDC metrics), some tracts exhibited lower ICC values < 0.8 for the FD measure. When examining fixel-level reliability and reproducibility clear spatial patterns emerged, with lower ICC across subcortical and cerebellar regions, and higher CVws at the cortical boundaries. Across all levels, tensor-based metrics demonstrated slightly lower reproducibility and reliability metrics than FBA measures, suggesting that FBA metrics are just as, if not more, reproducible than DTI metrics across scanners when using identical protocols. Our findings provide support for the reproducibility and reliability of fixel-based measures, highlighting their potential for use in multi-site FBA studies. Future work examining protocol-related differences, as well as appropriate harmonisation strategies when pooling data across sites and scanners, will be valuable.

neuroscience↗

bioRxiv2025

Beyond the Resection: Surgical White Matter Disruption alters Non-Resected Brain Anatomy

Resective neurosurgery is a cornerstone treatment for many neurological conditions. Although traditionally viewed as localised procedure, increasing evidence from advanced magnetic resonance imaging (MRI) shows that also non-resected anatomy can degenerate following surgery. The relationship between local tissue removal and these postoperative changes remains thus far speculative. Here, we investigate the hypothesis that degenerative changes to surgically preserved grey and white matter are mediated by transneuronal degeneration, a deterioration of intact neuronal populations due to lost axonal input. Using a robust structural and diffusion MRI framework, we first identify widespread postoperative atrophy: pronounced cortical thickness decreases near the resection, and extensive white matter impairments across the ipsilateral hemisphere. Importantly, we then link these alterations to surgical white matter disruption, revealing a sequential network atrophy following neurosurgery. Beyond degenerative effects, we also demonstrate often reported structural network reorganisations as an artefact of image processing, indicating limited capacity for macroscale plasticity post-resection. Key PointsO_LIResective neurosurgery can lead to postoperative atrophy of non-resected grey and white matter. Utilising a robust longitudinal neuroimaging framework, we evaluate these changes as consequences of transneuronal degeneration, demonstrating a sequential atrophy of brain anatomy following the loss of surgically disrupted white matter. C_LIO_LIThe majority of severed connections projected to atrophic cortices near the resection, indicating them to be short association fibers. Consecutive white matter atrophy however affected extensive ipsilateral pathways, highlighting a cascading network effect of resective brain surgery. C_LIO_LIWe did not find evidence to support often reported structural reorganisations of large-scale brain networks post-resection. Yet, we demonstrate that evidence typically interpreted as such can be replicated when using non-robust reconstruction methods. C_LI

neuroscience↗

bioRxiv2019

In vivo microstructural heterogeneity of white matter lesions in Alzheimer’s disease using tissue compositional analysis of diffusion MRI data

White matter hyperintensities (WMH) are commonly observed in elderly individuals, and are typically more prevalent in Alzheimers disease subjects than in healthy subjects. These lesions can be identified on fluid attenuated inversion recovery (FLAIR) MRI, on which they are hyperintense compared to their surroundings. These MRI-visible lesions appear homogeneously hyperintense despite known heterogeneity in their pathological underpinnings, and are commonly regarded as surrogate markers of small vessel disease in in vivo studies. Consequently, the extent to which these lesions contribute to Alzheimers disease remains unclear, likely due to the somewhat limited way in which these lesions are assessed in vivo. Diffusion MRI is sensitive to white matter microstructure, and might thus be used to investigate microstructural changes within WMH. In this study, we applied a method called single-shell 3-tissue constrained spherical deconvolution, which models white matter microstructure while also accounting for other tissue compartments, to investigate WMH in vivo. Diffusion MRI data and FLAIR images were obtained from Alzheimers disease (n = 48) and healthy elderly control (n = 94) subjects from the Australian Imaging, Biomarkers and Lifestyle study of ageing. WMH were automatically segmented and classified as periventricular or deep lesions from FLAIR images based on their continuity with the lateral ventricles, and the 3-tissue profile of different classes of WMH was characterised by three metrics, which together characterised the relative tissue profile in terms of the white matter-, grey matter-, and fluid-like characteristics of the diffusion signal. Our findings revealed that periventricular and deep lesion classes could be distinguished from one another, and from normal-appearing white matter based on their 3-tissue profile, with substantially higher free water content in periventricular lesions than deep. Given the higher lesion load of periventricular lesions in Alzheimers disease patients, the 3-tissue profile of these WMH could be interpreted as reflecting the more deleterious pathological underpinnings that are associated with disease. However, when alternatively classifying lesion sub-regions in terms of distance contours from the ventricles to account for potential heterogeneity within confluent lesions, we found that the highest fluid content was present in lesion areas most proximal to the ventricles, which were common to both Alzheimers disease subjects and healthy controls. We argue that whatever classification scheme is used when investigating WMH, failure to account for heterogeneity within lesions may result in classification-scheme dependent conclusions. Future studies of WMH in Alzheimers Disease would benefit from inclusion of microstructural information when characterising lesions.

neuroscience↗