Biology subjects

Tendler, B. C.

Publications and source records attributed to Tendler, B. C..

At least 19 recordsLinked to original sources

bioRxiv2026

An open-source stereotaxic container with an integrated cutting guide for human brain fixation during magnetic resonance imaging and sectioning for histology

IntroductionPostmortem imaging at ultrahigh field strengths, such as 7 Tesla (7T) magnetic resonance imaging (MRI), enables unprecedented visualization of fine brain structures and pathology. However, precise registration between MRI and histology is often compromised by tissue deformation and lack of standardized tools for preserving anatomical orientation. A reliable, high-resolution MRI-to-histology workflow is essential for MRI-guided sampling to investigate neurodegenerative diseases. MethodsWe developed a human postmortem brain container composed of stereotaxic enclosure and cutting guide system using iterative 3D printing. The final design is constructed from Victrex AM 200, a polyaryletherketone material engineered with MRI compatibility, high mechanical strength, and high resistance to fixatives. Human brains were embedded in an agar/sucrose mixture within the container and scanned at 7T using high-contrast and high-resolution imaging sequences. The cutting guide enables reproducible sectioning at defined tissue coronal slab thicknesses (9.2 {+/-} 0.6 mm). Block face photographs of each coronal slab were then co-registered with MRI for targeted tissue sampling. ResultsTo date, 215 human postmortem brains have been imaged ex vivo using this container. The container maintains consistent spatial orientation from imaging through sectioning, supporting correlation between MR-visible features and histological findings. Imaging-visible abnormalities, such as white matter hyperintensities and cerebral microbleeds, were localized and sampled with minimal deformation. The container enables single-scan workflows, avoiding custom cutting templates or repeat imaging. It supports deep learning-based lesion segmentation and MRI-guided histology registration, facilitating large-scale neuropathological investigations. ConclusionThe stereotaxic cutting guide system addresses a critical gap in postmortem imaging by integrating MRI-compatible materials, precision-guided sectioning, and high-throughput imaging. It has enabled multimodal studies of aging and neurodegeneration and is being adopted in neuropathological workflows. This platform provides a reproducible, scalable, and anatomically precise solution for aligning ultrahigh field MRI with histology, enhancing both clinical research and digital pathology efforts.

bioengineering↗

bioRxiv2025

10.5 Tesla High-Resolution Macaque Brain MRI for Connectivity Studies

Mapping brain connectivity in primates remains a major challenge due to difficulties in resolving microscopic white matter architecture, while maintaining whole-brain coverage. Increasing imaging spatial resolution is key for disambiguating fibre configurations within smaller anatomical volumes. Here, we present novel developments that allow high-resolution diffusion MRI of the macaque brain using one of the world's highest-field human MRI scanners operating at 10.5 Tesla, allowing both in vivo and ex vivo macaque brain imaging. Our approach achieves very high spatial resolution across both tissue states, (up to 580 m)3 in vivo and (300 m)3 ex vivo, with diffusion weighting up to b = 6000 s/mm2. We detail methodological advances in data acquisition, image reconstruction, processing and whole-brain tractography that overcome critical challenges associated with ultra-high-field imaging. This work establishes a new framework for high-resolution in vivo and ex vivo neuroimaging of the NHP brain at 10.5 T using a human bore scanner, paving the way for subsequent analyses of brain connectivity across species and tissue states at unprecedented detail. The dataset, along with all processing pipelines, containerised workflows, and reusable web services, is openly shared to support reproducibility and future integration with microscopy for studying white matter microstructure and connections at the mesoscale.

neuroscience↗

bioRxiv2025

Diffusion-weighted steady-state free precession imaging in the ex vivo macaque brain on a 10.5T human MRI scanner

Diffusion MRI provides a non-invasive probe of local fibre bundles and long-range anatomical connections to characterise the structural connectome. One way to achieve very high spatial resolution diffusion MRI data for connectivity investigations is to scan ex-vivo brains over many hours or days, ideally at ultra-high field strength to boost signal levels. However, conventional diffusion MRI acquisition techniques do not generally deliver good data quality for the challenging conditions of ex-vivo tissue, characterised by reduced diffusivities and relaxation times when compared to in vivo. In this work, we investigate the potential of the diffusion-weighted steady-state free precession (DW-SSFP) sequence for ex vivo diffusion imaging of the macaque brain using a 10.5 T human MRI scanner with a conventional (Gmax = 70 mT/m) gradient set. SNR-efficiency optimisations incorporating experimental relaxation times demonstrate that the DW-SSFP sequence is predicted to achieve improved or similar SNR efficiency compared to a diffusion-weighted spin- and stimulated-echo sequence. Importantly, DW-SSFP can achieve this with the additional benefit of negligible geometric distortions, unlike conventional diffusion MRI using an echo-planar imaging readout. Using optimised DW-SSFP sequence parameters, we propose a protocol at 0.4 mm isotropic resolution using a two-shell multi-orientation protocol (effective b-values of 3200 s/mm2 and 5600 s/mm2). We fit the data using Tensor, Ball and 3-Sticks and Constrained Spherical Deconvolution signal representations. The results demonstrate high-quality diffusivity estimates across the entire brain with the ability to resolve multiple fibre populations in challenging crossing-fibre regions. The data will be made fully open source and multimodal as part of the Center for Mesoscale Connectomics, providing a resource for future connectivity investigations.

neuroscience↗

bioRxiv2025

An RF coil array system for in vivo & ex vivo non-human primate brain studies at 10.5 Tesla

PurposeWe aimed to develop an innovative RF coil toolset for high resolution in vivo and ex vivo non-human primate neuroimaging applications at 10.5T MRI. The main goal was to improve our multimodal neural connectivity pipeline through the improved SNR, CNR, and spatial resolution that result from utilizing high-density RF coil arrays in combination with ultra-high field MRI. MethodsTwo RF coil arrays, both comprising 8 transmit and 40 receive channels, were designed and built for in vivo and ex vivo NHP imaging at 10.5 T. Experimental data was collected on multiple in vivo and ex vivo specimens, showing the utility UHF MRI for NHP neuroscience. ResultsExperimental results demonstrate uniform whole-brain coverage within both in vivo--which included the cerebellar, and spinal cord regions--and ex vivo specimens. High spatial resolutions (in vivo: 0.1x0.1x0.5 mm, ex vivo: 120 micron isotropic) were achieved, revealing detailed anatomical structures throughout. High temporal stability allowed for EPI and dMRI applications. ConclusionAn RF coil toolset comprising two 8ch transmit/40ch receive arrays was successfully designed for both in vivo and ex vivo NHP brain applications at 10.5 T. Both high-density RF coil arrays coupled with the SNR and CNR benefits available at UHF supported unmatched anatomical, functional, and diffusion applications at some of the highest spatial resolutions to date. Additionally, the combined capability of both in vivo and ex vivo MRI with the same brain specimen allows for tighter control for experimental-paradigm multistage studies examining translation between in vivo and ex vivo methodologies.

neuroscience↗

bioRxiv2025

Investigating motion-induced signal corruption in steady-state diffusion MRI

PurposeDiffusion-weighted steady-state free precession (DW-SSFP) is a diffusion imaging sequence achieving high SNR efficiency. A key challenge for in vivo DW-SSFP is the sequences severe motion sensitivity, currently limiting investigations to low or no motion regimes. Here we establish a framework to both (1) model and (2) correct for the impact of subject motion associated with the underlying magnetisation distribution of DW-SSFP. Theory and MethodsAn extended phase graphs (EPG) representation of the 1D DW-SSFP signal was established incorporating a motion operator describing rigid body and pulsatile motion. The representation was validated using Monte Carlo simulations, and subsequently integrated into a data fitting routine for motion estimation and correction. The fitting routine was evaluated using both simulations and a voxelwise correction applied to in vivo experimental 2D low-resolution single-shot timeseries DW-SSFP data acquired in the human brain in three healthy volunteers, with a tensor reconstructed from the motion-corrected experimental DW-SSFP data. ResultsThe proposed EPG-motion framework gives excellent agreement to complementary Monte Carlo simulations, demonstrating that diffusion coefficient estimation is robust over a range of motion and SNR regimes. Tensor estimates from the motion-corrected experimental DW-SSFP data give good visual agreement to complementary diffusion-weighted spin-echo (DW-SE) data acquired in the same subject, considerably reducing orientation-dependent motion-induced biases. ConclusionTemporal information capturing the evolution of the DW-SSFP signal can be used to retrospectively (1) estimate subject motion and (2) reconstruct motion-corrected DW-SSFP data. Open-source software is provided, facilitating future investigations into the impact of subject-motion on DW-SSFP acquisitions.

neuroscience↗

bioRxiv2025

Investigating the sensitivity of the diffusion MRI signal to magnetization transfer and permeability via Monte-Carlo simulations

PurposeMagnetization transfer (MT) and water exchange via permeability operate on a similar spatiotemporal scale to water diffusion. In this study, we use a simulation-based approach to characterise how MT and permeability impact (1) diffusion-weighted MRI (dMRI) measurements from cylindrical substrates and (2) parameter estimation using a two-compartment model of white matter. MethodsWe used Monte-Carlo simulations to model the dMRI signal inside and outside axons by simulating signals from parallel cylinders with different diameters and volume densities. We subsequently introduced membrane permeability and MT at the cylinder walls to investigate their impact on the dMRI signal. We fitted a two-compartment model to the simulated signal to produce estimates of the cylinder diameter and density. We evaluated the impact of MT and permeability by comparing the fitted diameter and density to the simulated ground truth. ResultsPermeability leads to underestimation (up to 100%) of cylinder diameter and density. Specifically, by enabling isochromats to escape from restrictions and diffuse more freely, permeability makes the overall displacement profile closer to the extra-axonal displacement profile. MT had limited effects on diameter estimation but caused substantial bias (20-50%) in volume density estimates depending on the ratio of the intra-axonal and extra-axonal volume fraction. This is due to the intra-axonal and extra-axonal space having different surface-to-volume ratios and therefore different surface relaxation rates. ConclusionPermeability and MT can considerably influence the dMRI signal. They increase the relative contribution from larger cylinders to the dMRI signal and bias microstructural parameter estimates derived from dMRI data.

neuroscience↗

bioRxiv2025

Integration of steady-state diffusion MRI with Neural Posterior Estimation (NPE) for post-mortem investigations

Post-mortem diffusion MRI plays a key role in investigative pipelines to characterise tissue microstructure, with long scan times facilitating the acquisition of datasets with improved spatial/angular resolution and reduced artefacts versus in vivo. Diffusion-weighted steady-state free precession (DW-SSFP) has emerged as a powerful technique for post-mortem imaging, achieving high SNR-efficiency and strong diffusion weighting in the challenging imaging environment of fixed tissue. However, the sophisticated signal forming mechanisms of DW-SSFP limit the characterisation of tissue properties with conventional parameter estimation routines. Here, I investigate the integration of DW-SSFP with neural posterior estimation (NPE), a parameter inference technique leveraging concepts from Bayesian statistics and machine learning to directly estimate P({theta} | S) (i.e. the posterior distribution of parameters {theta} given signal S). A key challenge is that diffusion attenuation in DW-SSFP is dependent on tissue relaxation properties (T1/T2) and transmit inhomogeneity (B1), which must be estimated experimentally and incorporated into the NPE network for accurate modelling. Using a Tensor representation and NPE to estimate P({theta} | S, T1, T2, B1) (i.e. conditioning on S and known T1/T2/B1), evaluations using synthetic DW-SSP data give excellent agreement to simulation ground truth even in the presence of non-Gaussian noise in low-SNR regimes. Evaluations using experimental DW-SSFP data (whole human post-mortem brain) give excellent agreement to non-linear least-squares estimates, with NPE providing 1000s of posterior samples in a matched evaluation time. Taken together, findings provide a framework to perform rapid parameter estimation with DW-SSFP, and an intuitive approach to incorporate conditional dependencies with NPE.

neuroscience↗

bioRxiv2025

Multi-modal Monte Carlo MRI simulator of tissue microstructure

Monte Carlo simulation of MRI signals is a powerful tool for modelling and quantifying tissue microstructure. While these methods have been used in MRI for decades, they typically focus on one aspect of microstructure and one type of MRI contrast at a time. In this paper, we present a new Monte Carlo MRI (MCMR) simulator for investigating the impact of tissue microstructure on arbitrary MRI sequences. A key feature of the proposed simulator is that substrates can incorporate multiple microstructural features (diffusion, T1/T2 relaxation, membrane permeability, local off-resonance fields, surface relaxation and magnetisation transfer) simultaneously. This provides a single forward model from tissue microstructure to MRI signals that captures a broad range of contrasts typically considered to be of different MRI "modalities". We validate the results of the simulator by reproducing previous findings in well-established sequences, namely diffusion-weighted MRI, magnetisation transfer imaging, and gradient and spin echo sequences. The simulator is fully open source and packaged along with detailed documentation and tutorials.

neuroscience↗

bioRxiv2024

Comparative neuroimaging of the carnivoran brain: Neocortical sulcal anatomy

Carnivorans are an important study object for comparative neuroscience, as they exhibit a wide range of behaviours, ecological adaptations, and social structures. Previous studies have mainly examined relative brain size, but a comprehensive understanding of brain diversity requires the investigation of other aspects of their neuroanatomy. Here, we obtained primarily post-mortem brain scans from twenty-six species of the order Carnivora, spanning across eight families with diverse representatives and including additional individuals for selected species, to create the largest Carnivoran brain collection to date. We then reconstructed their cortical surfaces, and examined neocortical sulcal anatomy to establish a framework for systematic inter-species comparisons. We observed distinct regional variations in sulcal anatomy, potentially related to the species behaviour and ecology. Arctoidea species with pronounced forepaw dexterity exhibited complex sulcal configurations in the presumed somatosensory cortex but low sulcal complexity in the presumed visual and auditory occipitotemporal cortex. Canidae had the largest number of unique major sulci with a unique sulcus in the occipital cortex and highly social canids featuring an additional frontal cortex sulcus. We also observed differentially complex occipito-temporal sulcal patterns in Felidae and Canidae, indicative of changes in auditory and visual areas that may be related to foraging strategies and social behaviour. In conclusion, this study presents an inventory of the sulcal anatomy of a number of rarely studied carnivoran brains including detailed digital atlases and establishes a framework and novel avenues for further investigations employing a variety of neuroimaging modalities to reveal more about carnivoran brain diversity.

neuroscience↗

bioRxiv2024

Investigating tissue microstructure using steady-state diffusion MRI

Diffusion MRI is a leading method to non-invasively characterise brain tissue microstructure across multiple domains and scales. Diffusion-weighted steady-state free precession (DW-SSFP) is an established imaging sequence for post-mortem MRI, addressing the challenging imaging environment of fixed tissue with short T2 and low diffusivities. However, a current limitation of DW-SSFP is signal interpretation: it is not clear what diffusion regime the sequence probes and therefore its potential to characterise tissue microstructure. Building on a model of Extended Phase Graphs (EPG), I establish two alternative representations of the DW-SSFP signal in terms of (1) conventional b-values (time-independent diffusion) and (2) encoding power-spectra (time-dependent diffusion). The proposed representations provide insights into how different parameter regimes and gradient waveforms impact the diffusion properties of DW-SSFP. Using these representations, I introduce an approach to incorporate existing diffusion models into DW-SSFP without the requirement of extensive derivations. Investigations incorporating free-diffusion and tissue-relevant microscopic restrictions (cylinder of varying radius) give excellent agreement to complementary analytical models and Monte Carlo simulations. Experimentally, the time-independent representation is used to derive Tensor and proof of principle NODDI estimates in a whole human post-mortem brain. A final SNR-efficiency investigation demonstrates the theoretical potential of DW-SSFP for ultra-high field microstructural imaging.

neuroscience↗

bioRxiv2022

Tensor Image Registration Library: Automated Deformable Registration of Stand-Alone Histology Images to Whole-Brain Post-Mortem MRI Data

BackgroundAccurate registration between microscopy and MRI data is necessary for validating imaging biomarkers against neuropathology, and to disentangle complex signal dependencies in microstructural MRI. Existing registration methods often rely on serial histological sampling or significant manual input, providing limited scope to work with a large number of stand-alone histology sections. Here we present a customisable pipeline to automate the registration of stand-alone histology sections to whole-brain MRI data. MethodsOur pipeline registers stained histology sections to whole-brain post-mortem MRI in 4 stages, with the help of two photographic intermediaries: a block face image (to undistort histology sections) and coronal brain slice photographs (to insert them into MRI space). Each registration stage is implemented as a configurable stand-alone Python script using our novel platform, Tensor Image Registration Library (TIRL), which provides flexibility for wider adaptation. We report our experience of registering 87 PLP-stained histology sections from 14 subjects and perform various experiments to assess the accuracy and robustness of each stage of the pipeline. ResultsAll 87 histology sections were successfully registered to MRI. Histology-to-block registration (Stage 1) achieved 0.2-0.4 mm accuracy, better than commonly used existing methods. Block-to-slice matching (Stage 2) showed great robustness in automatically identifying and inserting small tissue blocks into whole brain slices with 0.2 mm accuracy. Simulations demonstrated sub-voxel level accuracy (0.13 mm) of the slice-to-volume registration (Stage 3) algorithm, which was observed in over 200 actual brain slice registrations, compensating 3D slice deformations up to 6.5 mm. Stage 4 combined the previous stages and generated refined pixelwise aligned multi-modal histology-MRI stacks. ConclusionsOur open-source pipeline provides robust automation tools for registering stand-alone histology sections to MRI data with sub-voxel level precision, and the underlying framework makes it readily adaptable to a diverse range of microscopy-MRI studies. HighlightsO_LINew software framework for prototyping bespoke image registration pipelines C_LIO_LIAutomated pipeline to register stand-alone histology sections to whole-brain MRI C_LIO_LINovel deformable slice-to-volume registration algorithm C_LIO_LINo strict necessity for serial histological sectioning for MRI-histology registration C_LI

neuroscience↗

bioRxiv2022

An automated pipeline for extracting quantitative histological metrics for voxelwise MRI-histology comparisons

The acquisition of MRI and histology in the same post-mortem tissue sample enables direct correlation between MRI and histologically-derived parameters. However, there still lacks a standardised automated pipeline to process histology data, with most studies relying on heavy manual intervention. Here, we introduce an automated pipeline to extract a quantitative histological measure for staining density (stain area fraction) from multiple immunohistochemical (IHC) stains. The pipeline is designed to directly address key IHC artefacts related to tissue staining and slide digitisation. Here, the pipeline was applied to post-mortem human brain data from multiple subjects, relating MRI parameters (FA, MD, R2*, R1) to IHC slides stained for myelin, neurofilaments, microglia and activated microglia. Utilising high-quality MRI-histology coregistrations, we then performed whole-slide voxelwise comparisons (simple correlations, partial correlations and multiple regression analyses) between multimodal MRI- and IHC-derived parameters. The pipeline was found to be reproducible, robust to artefacts and generalisable across multiple IHC stains. Our partial correlation results suggest that some simple MRI-SAF correlations should be interpreted with caution, due to the co-localisation of certain tissue features (e.g. myelin and neurofilaments). Further, we find activated microglia to consistently be the strongest predictor of DTI FA, which may suggest sensitivity of diffusion MRI to neuroinflammation. Taken together, these results show the utility of this approach in carefully curating IHC data and performing multimodal analyses to better understand microstructural relationships with MRI.

neuroscience↗

bioRxiv2021

Phenotypic and genetic associations of quantitative magnetic susceptibility in UK Biobank brain imaging

A key aim in epidemiological neuroscience is identification of markers to assess brain health and monitor therapeutic interventions. Quantitative susceptibility mapping (QSM) is an emerging MRI technique that measures tissue magnetic susceptibility and has been shown to detect pathological changes in tissue iron, myelin and calcification. We developed a QSM processing pipeline to estimate magnetic susceptibility of multiple brain structures in 35,885 subjects from the UK Biobank prospective epidemiological study. We identified phenotypic associations of magnetic susceptibility that include body iron, disease, diet, and alcohol consumption. Genome-wide associations related magnetic susceptibility to genetic variants with biological functions involving iron, calcium, myelin, and extracellular matrix. These patterns of associations include relationships that are unique to QSM, in particular being complementary to T2* measures. These new imaging phenotypes are being integrated into the core UK Biobank measures provided to researchers world-wide, creating potential to discover novel, non-invasive markers of brain health.

neuroscience↗

bioRxiv2021

The Digital Brain Bank: an open access platform for post-mortem datasets

Post-mortem MRI provides the opportunity to acquire high-resolution datasets to investigate neuroanatomy, and validate the origins of image contrast through microscopy comparisons. We introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), a data release platform providing open access to curated, multimodal post-mortem neuroimaging datasets. Datasets span three themes - Digital Neuroanatomist: datasets for detailed neuroanatomical investigations; Digital Brain Zoo: datasets for comparative neuroanatomy; Digital Pathologist: datasets for neuropathology investigations. The first Digital Brain Bank release includes twenty one distinctive whole-brain diffusion MRI datasets for structural connectivity investigations, alongside microscopy and complementary MRI modalities. This includes one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired, whole-brain diffusion MRI in fourteen non-human primate species, and one of the largest post-mortem whole-brain cohort imaging studies in neurodegeneration. The Digital Brain Bank is the culmination of our labs investment into post-mortem MRI methodology and MRI-microscopy analysis techniques. This manuscript provides a detailed overview of our work with post-mortem imaging to date, including the development of diffusion MRI methods to image large post-mortem samples, including whole, human brains. Taken together, the Digital Brain Bank provides crossscale, cross-species datasets facilitating the incorporation of post-mortem data into neuroimaging studies.

neuroscience↗

bioRxiv2020

Distributional changes in myelin-specific MRI markers uncover dynamics in the fornix following spatial navigation training

Increasing evidence implicates white matter (WM) dynamics supporting learning in the mature brain. Recent MRI studies, mostly using diffusion tensor MRI (DT-MRI), have demonstrated learning-induced WM changes at the microstructural level. However, while DT-MRI-derived measures have sensitivity to general WM microstructural changes, they lack compartmental specificity, making them difficult to relate to underlying cellular mechanisms, stymying deeper understanding of mechanisms supporting training-induced gains in performance. Gaining a deeper understanding demands a more detailed characterization of changes in specific WM sub-components. To this end, four microstructural MRI techniques were employed to study alterations in rat brains after 5-days of water maze training: DT-MRI; Composite Hindered and Restricted Model of Diffusion (CHARMED); magnetization transfer (MT) imaging; quantitative susceptibility mapping and R2*. The hypothesis tested here was that microstructural changes would be: (i) observed in tracts supporting spatial navigation, i.e., fornix and corpus callosum (CC); and (ii) more pronounced in the myelin-specific measures. Medians and distributions of microstructural parameters were derived along the fornix, CC and cingulum (as a comparison tract) using the tractometry approach. Summary measures were derived from different metrics using unsupervised data reduction. Significant pre-vs-post training differences were found in the medians of two principal components loading on: (i) anisotropy indices; and (ii) MT ratio. The most striking effect, however, was seen in the distributions of pre-vs-post training MT ratio in the fornix, consistent with the primary hypothesis, and highlighting the value of this alternative to the standard approach (i.e., comparing means/medians of DT-MRI parameters) for studying neuroplasticity in vivo. Significance statementRecent MRI-studies have demonstrated that white matter (WM) dynamics support learning, even in the mature brain. However, most studies are based on diffusion tensor MRI (DT-MRI) measures, which although providing sensitivity to WM microstructural changes, do not provide a direct translation to the underlying cellular mechanisms making interpretation difficult. Using alternative quantitative MRI approaches, this study provided more specific subcomponent microstructural insights into the brains WM response to water-maze training. We show that myelin-specific MR measures show more marked changes than axonal-specific and DT-MRI measures, in WM tracts responsible for spatial navigation. The results promote adoption of these alternative approaches to DT-MRI for studying neuroplasticity in vivo.

neuroscience↗

bioRxiv2020

DIffusion-Prepared Phase Imaging (DIPPI): quantifying myelin in crossing fibres

PurposeMyelin has long been the target of neuroimaging research due to its importance in brain development, plasticity, and disease. However, most available techniques can only provide a voxel-averaged estimate of myelin content. In the human brain, white matter fibre pathways connecting different brain areas and carrying different functions often cross each other in the same voxel. A measure that can differentiate the degree of myelination of crossing fibres would provide a more specific marker of myelination. Theory & MethodsOne MRI signal property sensitive to myelin is the phase accumulation, which to date has also been limited to voxel-averaged myelin estimates. We use this sensitivity by measuring the phase accumulation of the signal remaining after diffusion weighting, which we call DIffusion-Prepared Phase Imaging (DIPPI). Including diffusion weighting before estimating the phase accumulation has two distinct advantages for estimating the degree of myelination: (1) it increases the relative contribution of intra-axonal water, whose phase is related linearly to the amount of myelin surrounding the axon (in particular the log g-ratio) and (2) it gives directional information, which can be used to distinguish between crossing fibres. ResultsUsing simulations and phantom data we argue that other sources of phase accumulation (i.e., movement-induced phase shift during the diffusion gradients, eddy currents, and other sources of susceptibility) can be either corrected for or are sufficiently small to still allow the g-ratio to be reliably estimated. ConclusionsThis new sequence is capable of providing a g-ratio estimate per fibre population crossing within a voxel.

neuroscience↗

bioRxiv2020

A method to remove the influence of fixative concentration on post-mortem T2 maps using a Kinetic Tensor model

Formalin fixation has been shown to substantially reduce T2 estimates when performing post-mortem imaging, primarily driven by the presence of bulk fixative in tissue. Prior to scanning, post-mortem tissue samples are often placed into a fluid that has more favourable imaging properties, such as matched magnetic susceptibility. This study investigates whether there is any evidence for a change in T2 in regions close to the tissue surface in post-mortem T2 maps due to fixative outflux into this surrounding fluid. Furthermore, we investigate whether a simulated spatial map of fixative concentration can be used as a confound regressor to reduce T2 inhomogeneity. To achieve this, T2 maps and diffusion tensor estimates were obtained in 14 whole, formalin fixed post-mortem brains placed in fluorinert approximately 48 hours prior to scanning. This consisted of 7 brains fixed with 10% formalin and 7 brains fixed with 10% neutral buffered formalin (NBF). Fixative outflux was modelled using a Kinetic Tensor (KT) model, which incorporates voxelwise diffusion tensor estimates to account for diffusion anisotropy and tissue-specific diffusion coefficients. Brains fixed with 10% NBF revealed a spatial T2 pattern consistent with the modelled fixative outflux. Confound regression of fixative concentration reduced T2 inhomogeneity across both white and grey matter, with the greatest reduction attributed to the KT model vs simpler models of fixative outflux. No such effect was observed in brains fixed with 10% formalin. Correlations with ferritin and myelin proteolipid protein (PLP) histology lead to an increased similarity for the relationship between T2 and PLP for the two fixative types after KT correction. Only small correlations were identified between T2 and ferritin before and after KT correction.

neuroscience↗

bioRxiv2020

Methods for quantitative susceptibility and R2* mapping in whole post-mortem brains at 7T

Susceptibility weighted magnetic resonance imaging (MRI) is sensitive to the local concentration of iron and myelin. Here, we describe a robust image processing pipeline for quantitative susceptibility mapping (QSM) and R2* mapping of fixed post-mortem, whole-brain data. Using this pipeline, we compare the resulting quantitative maps in brains from patients with amyotrophic lateral sclerosis (ALS) and controls, with validation against iron and myelin histology. Twelve post-mortem brains were scanned with a multi-echo gradient echo sequence at 7T, from which susceptibility and R2* maps were generated. Semi-quantitative histological analysis for ferritin (the principal iron storage protein) and myelin proteolipid protein was performed in the primary motor, anterior cingulate and visual cortices. Magnetic susceptibility and R2* values in primary motor cortex were higher in ALS compared to control brains. Magnetic susceptibility and R2* showed positive correlations with both myelin and ferritin estimates from histology. Four out of nine ALS brains exhibited clearly visible hyperintense susceptibility and R2* values in the primary motor cortex. Our results demonstrate the potential for MRI-histology studies in whole, fixed post-mortem brains to investigate the biophysical source of susceptibility weighted MRI signals in neurodegenerative diseases like ALS.

neuroscience↗