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Mark Drakesmith

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8 papers

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YNIMG Journal 2022 Journal Article

Estimating axial diffusivity in the NODDI model

Amy FD Howard
Michiel Cottaar
Mark Drakesmith
Qiuyun Fan
Susie Y. Huang
Derek K. Jones
Frederik J. Lange
Jeroen Mollink

To estimate microstructure-related parameters from diffusion MRI data, biophysical models make strong, simplifying assumptions about the underlying tissue. The extent to which many of these assumptions are valid remains an open research question. This study was inspired by the disparity between the estimated intra-axonal axial diffusivity from literature and that typically assumed by the Neurite Orientation Dispersion and Density Imaging (NODDI) model ( d ∥ = 1. 7 μ m 2 /ms ). We first demonstrate how changing the assumed axial diffusivity results in considerably different NODDI parameter estimates. Second, we illustrate the ability to estimate axial diffusivity as a free parameter of the model using high b-value data and an adapted NODDI framework. Using both simulated and in vivo data we investigate the impact of fitting to either real-valued or magnitude data, with Gaussian and Rician noise characteristics respectively, and what happens if we get the noise assumptions wrong in this high b-value and thus low SNR regime. Our results from real-valued human data estimate intra-axonal axial diffusivities of ∼ 2 − 2. 5 μ m 2 /ms, in line with current literature. Crucially, our results demonstrate the importance of accounting for both a rectified noise floor and/or a signal offset to avoid biased parameter estimates when dealing with low SNR data.

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YNIMG Journal 2021 Journal Article

MICRA: Microstructural image compilation with repeated acquisitions

Kristin Koller
Umesh Rudrapatna
Maxime Chamberland
Erika P. Raven
Greg D. Parker
Chantal M.W. Tax
Mark Drakesmith
Fabrizio Fasano

We provide a rich multi-contrast microstructural MRI dataset acquired on an ultra-strong gradient 3T Connectom MRI scanner comprising 5 repeated sets of MRI microstructural contrasts in 6 healthy human participants. The availability of data sets that support comprehensive simultaneous assessment of test-retest reliability of multiple microstructural contrasts (i.e., those derived from advanced diffusion, multi-component relaxometry and quantitative magnetisation transfer MRI) in the same population is extremely limited. This unique dataset is offered to the imaging community as a test-bed resource for conducting specialised analyses that may assist and inform their current and future research. The Microstructural Image Compilation with Repeated Acquisitions (MICRA) dataset includes raw data and computed microstructure maps derived from multi-shell and multi-direction encoded diffusion, multi-component relaxometry and quantitative magnetisation transfer acquisition protocols. Our data demonstrate high reproducibility of several microstructural MRI measures across scan sessions as shown by intra-class correlation coefficients and coefficients of variation. To illustrate a potential use of the MICRA dataset, we computed sample sizes required to provide sufficient statistical power a priori across different white matter pathways and microstructure measures for different statistical comparisons. We also demonstrate whole brain white matter voxel-wise repeatability in several microstructural maps. The MICRA dataset will be of benefit to researchers wishing to conduct similar reliability tests, power estimations or to evaluate the robustness of their own analysis pipelines.

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YNIMG Journal 2020 Journal Article

Virtual histology of multi-modal magnetic resonance imaging of cerebral cortex in young men

Yash Patel
Jean Shin
Mark Drakesmith
John Evans
Zdenka Pausova
Tomas Paus

Neurobiology underlying inter-regional variations - across the human cerebral cortex - in measures derived with multi-modal magnetic resonance imaging (MRI) is poorly understood. Here, we characterize inter-regional variations in a large number of such measures, including T1 and T2 relaxation times, myelin water fraction (MWF), T1w/T2w ratio, mean diffusivity (MD), fractional anisotropy (FA), magnetization transfer ratio (MTR) and cortical thickness. We then employ a virtual-histology approach and relate these inter-regional profiles to those in cell-specific gene expression. Virtual histology revealed that most MRI-derived measures, including T1, T2 relaxation time, MWF, T1w/T2w ratio, MTR, FA and cortical thickness, are associated with expression profiles of genes specific to CA1 pyramidal cells; these genes are enriched in biological processes related to dendritic arborisation. In addition, T2 relaxation time, MWF and T1w/T2w ratio are associated with oligodendrocyte-specific gene-expression profiles, supporting their use as measures sensitive to intra-cortical myelin. MWF contributes more variance than T1w/T2w ratio to the mean oligodendrocyte expression profile, suggesting greater sensitivity to myelin. These cell-specific MRI associations may help provide a framework for determining which MRI sequences to acquire in studies with specific neurobiological hypotheses.

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YNIMG Journal 2019 Journal Article

Estimating axon conduction velocity in vivo from microstructural MRI

Mark Drakesmith
Robbert Harms
Suryanarayana Umesh Rudrapatna
Greg D. Parker
C. John Evans
Derek K. Jones

The conduction velocity (CV) of action potentials along axons is a key neurophysiological property central to neural communication. The ability to estimate CV in humans in vivo from non-invasive MRI methods would therefore represent a significant advance in neuroscience. However, there are two major challenges that this paper aims to address: (1) Much of the complexity of the neurophysiology of action potentials cannot be captured with currently available MRI techniques. Therefore, we seek to establish the variability in CV that can be captured when predicting CV purely from parameters that have been reported to be estimatable from MRI: inner axon diameter (AD) and g-ratio. (2) errors inherent in existing MRI-based biophysical models of tissue will propagate through to estimates of CV, the extent to which is currently unknown. Issue (1) is investigated by performing a sensitivity analysis on a comprehensive model of axon electrophysiology and determining the relative sensitivity to various morphological and electrical parameters. The investigations suggest that 85% of the variance in CV is accounted for by variation in AD and g-ratio. The observed dependency of CV on AD and g-ratio is well characterised by the previously reported model by Rushton. Issue (2) is investigated through simulation of diffusion and relaxometry MRI data for a range of axon morphologies, applying models of restricted diffusion and relaxation processes to derive estimates of axon volume fraction (AVF), AD and g-ratio and estimating CV from the derived parameters. The results show that errors in the AVF have the biggest detrimental impact on estimates of CV, particularly for sparse fibre populations (AVF < 0. 3 ). For our equipment set-up and acquisition protocol, CV estimates are most accurate (below 5% error) where AVF is above 0. 3, g-ratio is between 0. 6 and 0. 85 and AD is high (above 4 μm ). CV estimates are robust to errors in g-ratio estimation but are highly sensitive to errors in AD estimation, particularly where ADs are small. We additionally show CV estimates in human corpus callosum in a small number of subjects. In conclusion, we demonstrate accurate CV estimates are possible in regions of the brain where AD is sufficiently large. Problems with estimating ADs for smaller axons presents a problem for estimating CV across the whole CNS and should be the focus of further study.

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YNIMG Journal 2018 Journal Article

Associations between prenatal, childhood, and adolescent stress and variations in white-matter properties in young men

Sarah K.G. Jensen
Melissa Pangelinan
Lassi Björnholm
Anja Klasnja
Alexander Leemans
Mark Drakesmith
C.J. Evans
Edward D. Barker

Objective Previous studies have shown that both pre- and post-natal adversities, the latter including exposures to stress during childhood and adolescence, explain variation in structural properties of white matter (WM) in the brain. While previous studies have examined effects of independent stress exposures within one developmental period, such as childhood, we examine effects of stress across development using data from a prospective longitudinal study. More specifically, we ask how stressful events during prenatal development, childhood, and adolescence relate to variation in WM properties in early adulthood in young men recruited from a birth cohort. Method Using data from 393 mother-son pairs from a community-based birth cohort from England (Avon Longitudinal Study of Parents and Children), we examined how stressful life events relate to variation in different structural properties of WM in the corpus callosum and across the whole brain in early adulthood in men aged 18–21 years. We distinguish between stress occurring during three developmental periods: a) prenatal maternal stress, b) postnatal stress within the first four years of life, c) stress during adolescence (age 12–16 years). To obtain a comprehensive quantification of variation in WM, we assess structural properties of WM using four different measures, namely fractional anisotropy (FA), mean diffusivity (MD), magnetization transfer ratio (MTR) and myelin water fraction (MWF). Results The developmental model shows that prenatal stress is associated with lower MTR and MWF in the genu and/or splenium of the corpus callosum, and with lower MTR in global (lobar) WM. Stress during early childhood is associated with higher MTR in the splenium, and stress during adolescence is associated with higher MTR in the genu and lower MD in the splenium. We see no associations between postnatal stress and variation in global (lobar) WM. Conclusions The current study found evidence for independent effects of stress on WM properties during distinct neurodevelopmental periods. We speculate that these independent effects are due to differences in the developmental processes unfolding at different developmental time points. We suggest that associations between prenatal stress and WM properties may relate to abnormalities in neurogenesis, affecting the number and density of axons, while postnatal stress may interfere with processes related to myelination or radial growth of axons. Potential consequences of prenatal glucocorticoid exposure should be considered in obstetric care.

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YNICL Journal 2016 Journal Article

Volumetric, relaxometric and diffusometric correlates of psychotic experiences in a non-clinical sample of young adults

Mark Drakesmith
Anirban Dutt
Leon Fonville
Stanley Zammit
Abraham Reichenberg
C. John Evans
Philip McGuire
Glyn Lewis

BACKGROUND: Grey matter (GM) abnormalities are robust features of schizophrenia and of people at ultra high-risk for psychosis. However the extent to which neuroanatomical alterations are evident in non-clinical subjects with isolated psychotic experiences is less clear. METHODS: Individuals (mean age 20 years) with (n = 123) or without (n = 125) psychotic experiences (PEs) were identified from a population-based cohort. All underwent T1-weighted structural, diffusion and quantitative T1 relaxometry MRI, to characterise GM macrostructure, microstructure and myelination respectively. Differences in quantitative GM structure were assessed using voxel-based morphometry (VBM). Binary and ordinal models of PEs were tested. Correlations between socioeconomic and other risk factors for psychosis with cortical GM measures were also computed. RESULTS: GM volume in the left supra-marginal gyrus was reduced in individuals with PEs relative to those with no PEs. The greater the severity of PEs, the greater the reduction in T1 relaxation rate (R1) across left temporoparietal and right pre-frontal cortices. In these regions, R1 was positively correlated with maternal education and inversely correlated with general psychopathology. CONCLUSIONS: PEs in non-clinical subjects were associated with regional reductions in grey-matter volume reduction and T1 relaxation rate. The alterations in T1 relaxation rate were also linked to the level of general psychopathology. Follow up of these subjects should clarify whether these alterations predict the later development of an ultra high-risk state or a psychotic disorder.

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YNIMG Journal 2014 Journal Article

Why diffusion tensor MRI does well only some of the time: Variance and covariance of white matter tissue microstructure attributes in the living human brain

Silvia De Santis
Mark Drakesmith
Sonya Bells
Yaniv Assaf
Derek K. Jones

Fundamental to increasing our understanding of the role of white matter microstructure in normal/abnormal function in the living human is the development of MR-based metrics that provide increased specificity to distinct attributes of the white matter (e. g. , local fibre architecture, axon morphology, and myelin content). In recent years, different approaches have been developed to enhance this specificity, and the Tractometry framework was introduced to combine the resulting multi-parametric data for a comprehensive assessment of white matter properties. The present work exploits that framework to characterise the statistical properties, specifically the variance and covariance, of these advanced microstructural indices across the major white matter pathways, with the aim of giving clear indications on the preferred metric(s) given the specific research question. A cohort of healthy subjects was scanned with a protocol that combined multi-component relaxometry with conventional and advanced diffusion MRI acquisitions to build the first comprehensive MRI atlas of white matter microstructure. The mean and standard deviation of the different metrics were analysed in order to understand how they vary across different brain regions/individuals and the correlation between them. Characterising the fibre architectural complexity (in terms of number of fibre populations in a voxel) provides clear insights into correlation/lack of correlation between the different metrics and explains why DT-MRI is a good model for white matter only some of the time. The study also identifies the metrics that account for the largest inter-subject variability and reports the minimal sample size required to detect differences in means, showing that, on the other hand, conventional DT-MRI indices might still be the safest choice in many contexts.

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YNIMG Journal 2012 Journal Article

The variation of function across the human insula mirrors its patterns of structural connectivity: Evidence from in vivo probabilistic tractography

Lauren L. Cloutman
Richard J. Binney
Mark Drakesmith
Geoffrey J.M. Parker
Matthew A. Lambon Ralph

The human insula is a functionally complex yet poorly understood region of the cortex, implicated in a wide range of cognitive, motor, emotion and somatosensory activity. To elucidate the functional role of the insula, the current study used in vivo probabilistic tractography to map the structural connectivity of seven anatomically-defined insular subregions. The connectivity patterns identified reveal two complementary insular networks connected via a dual route architecture, and provide key insights about the neural basis of the numerous functions ascribed to this area. Specifically, anterior-most insular regions were associated with a ventrally-based network involving orbital/inferior frontal and anterior/polar temporal regions, forming part of a key emotional salience and cognitive control network associated with the implementation of goal-directed behavior. The posterior and dorsal-middle insular regions were associated with a network focused on posterior and (to a lesser extent) anterior temporal regions via both dorsal and ventral pathways. This is consistent with the involvement of the insula in sound-to-speech transformations, with an implicated role in the temporal resolution, sequencing, and feedback processes crucial for auditory and motor processing, and the monitoring and adjustment of expressive performance.

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