Arrow Research search

Author name cluster

Michael J. Thrippleton

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

6 papers
1 author row

Possible papers

6

YNICL Journal 2022 Journal Article

Longitudinal microstructural MRI markers of demyelination and neurodegeneration in early relapsing-remitting multiple sclerosis: Magnetisation transfer, water diffusion and g-ratio

  • Elizabeth N. York
  • Rozanna Meijboom
  • Michael J. Thrippleton
  • Mark E. Bastin
  • Agniete Kampaite
  • Nicole White
  • Siddharthan Chandran
  • Adam D. Waldman

INTRODUCTION: Quantitative microstructural MRI, such as myelin-sensitive magnetisation transfer ratio (MTR) or saturation (MTsat), axon-sensitive water diffusion Neurite Orientation Dispersion and Density Imaging (NODDI), and the aggregate g-ratio, may provide more specific markers of white matter integrity than conventional MRI for early patient stratification in relapsing-remitting multiple sclerosis (RRMS). The aim of this study was to determine the sensitivity of such markers to longitudinal pathological change within cerebral white matter lesions (WML) and normal-appearing white matter (NAWM) in recently diagnosed RRMS. METHODS: Seventy-nine people with recently diagnosed RRMS, from the FutureMS longitudinal cohort, were recruited to an extended MRI protocol at baseline and one year later. Twelve healthy volunteers received the same MRI protocol, repeated within two weeks. Ethics approval and written informed consent were obtained. 3T MRI included magnetisation transfer, and multi-shell diffusion-weighted imaging. NAWM and whole brain were segmented from 3D T1-weighted MPRAGE, and WML from T2-weighted FLAIR. MTR, MTsat, NODDI isotropic (ISOVF) and intracellular (ICVF) volume fractions, and g-ratio (calculated from MTsat and NODDI data) were measured within WML and NAWM. Brain parenchymal fraction (BPF) was also calculated. Longitudinal change in BPF and microstructural metrics was assessed with paired t-tests (α = 0.05) and linear mixed models, adjusted for confounding factors with False Discovery Rate (FDR) correction for multiple comparisons. Longitudinal changes were compared with test-retest Bland-Altman limits of agreement from healthy control white matter. The influence of longitudinal change on g-ratio was explored through post-hoc analysis in silico by computing g-ratio with realistic simulated MTsat and NODDI values. RESULTS: In NAWM, g-ratio and ICVF increased, and MTsat decreased over one year (adjusted mean difference = 0.007, 0.005, and -0.057 respectively, all FDR-corrected p < 0.05). There was no significant change in MTR, ISOVF, or BPF. In WML, MTsat, NODDI ICVF and ISOVF increased over time (adjusted mean difference = 0.083, 0.024 and 0.016, respectively, all FDR-corrected p < 0.05). Group-level longitudinal changes exceeded test-retest limits of agreement for NODDI ISOVF and ICVF in WML only. In silico analysis showed g-ratio may increase due to a decrease in MTsat or ISOVF, or an increase in ICVF. DISCUSSION: G-ratio and MTsat changes in NAWM over one year may indicate subtle myelin loss in early RRMS, which were not apparent with BPF or NAWM MTR. Increases in NAWM and WML NODDI ICVF were not anticipated, and raise the possibility of axonal swelling or morphological change. Increases in WML MTsat may reflect myelin repair. Changes in NODDI ISOVF are more likely to reflect alterations in water content. Competing MTsat and ICVF changes may account for the absence of g-ratio change in WML. Longitudinal changes in microstructural measures are significant at a group level, however detection in individual patients in early RRMS is limited by technique reproducibility. CONCLUSION: MTsat and g-ratio are more sensitive than MTR to early pathological changes in RRMS, but complex dependence of g-ratio on NODDI parameters limit the interpretation of aggregate measures in isolation. Improvements in technique reproducibility and validation of MRI biophysical models across a range of pathological tissue states are needed.

YNIMG Journal 2021 Journal Article

A four-dimensional computational model of dynamic contrast-enhanced magnetic resonance imaging measurement of subtle blood-brain barrier leakage

  • Jose Bernal
  • Maria d.C. Valdés-Hernández
  • Javier Escudero
  • Anna K. Heye
  • Eleni Sakka
  • Paul A. Armitage
  • Stephen Makin
  • Rhian M. Touyz

Dynamic contrast-enhanced MRI (DCE-MRI) is increasingly used to quantify and map the spatial distribution of blood-brain barrier (BBB) leakage in neurodegenerative disease, including cerebral small vessel disease and dementia. However, the subtle nature of leakage and resulting small signal changes make quantification challenging. While simplified one-dimensional simulations have probed the impact of noise, scanner drift, and model assumptions, the impact of spatio-temporal effects such as gross motion, k-space sampling and motion artefacts on parametric leakage maps has been overlooked. Moreover, evidence on which to base the design of imaging protocols is lacking due to practical difficulties and the lack of a reference method. To address these problems, we present an open-source computational model of the DCE-MRI acquisition process for generating four dimensional Digital Reference Objects (DROs), using a high-resolution brain atlas and incorporating realistic patient motion, extra-cerebral signals, noise and k-space sampling. Simulations using the DROs demonstrated a dominant influence of spatio-temporal effects on both the visual appearance of parameter maps and on measured tissue leakage rates. The computational model permits greater understanding of the sensitivity and limitations of subtle BBB leakage measurement and provides a non-invasive means of testing and optimising imaging protocols for future studies.

YNICL Journal 2021 Journal Article

Tracer kinetic assessment of blood–brain barrier leakage and blood volume in cerebral small vessel disease: Associations with disease burden and vascular risk factors

  • Michael S. Stringer
  • Anna K. Heye
  • Paul A. Armitage
  • Francesca Chappell
  • Maria del C. Valdés Hernández
  • Stephen D.J. Makin
  • Eleni Sakka
  • Michael J. Thrippleton

Subtle blood–brain barrier (BBB) permeability increases have been shown in small vessel disease (SVD) using various analysis methods. Following recent consensus recommendations, we used Patlak tracer kinetic analysis, considered optimal in low permeability states, to quantify permeability-surface area product (PS), a BBB leakage estimate, and blood plasma volume (vP ) in 201 patients with SVD who underwent dynamic contrast-enhanced MRI scans. We ran multivariable regression models with a quantitative or qualitative metric of white matter hyperintensity (WMH) severity, demographic and vascular risk factors. PS increased with WMH severity in grey (B = 0. 15, Confidence Interval (CI): [0. 001, 0. 299], p = 0. 049) and normal-appearing white matter (B = 0. 015, CI: [−0. 008, 0. 308], p = 0. 062). Patients with more severe WMH had lower vP in WMH (B = -0. 088, CI: [−0. 138, -0. 039], p < 0. 001), but higher vP in normal-appearing white matter (B = 0. 031, CI: [−0. 004, 0. 065], p = 0. 082). PS and vP were lower at older ages in WMH, grey and white matter. We conclude higher PS in normal-appearing tissue with more severe WMH suggests impaired BBB integrity beyond visible lesions indicating that the microvasculature is compromised in normal-appearing white matter and WMH. BBB dysfunction is an important mechanism in SVD, but associations with clinical variables are complex and underlying damage affecting vascular surface area may alter interpretation of tracer kinetic results.

YNICL Journal 2020 Journal Article

Neonatal morphometric similarity mapping for predicting brain age and characterizing neuroanatomic variation associated with preterm birth

  • Paola Galdi
  • Manuel Blesa
  • David Q. Stoye
  • Gemma Sullivan
  • Gillian J. Lamb
  • Alan J. Quigley
  • Michael J. Thrippleton
  • Mark E. Bastin

Multi-contrast MRI captures information about brain macro- and micro-structure which can be combined in an integrated model to obtain a detailed "fingerprint" of the anatomical properties of an individual's brain. Inter-regional similarities between features derived from structural and diffusion MRI, including regional volumes, diffusion tensor metrics, neurite orientation dispersion and density imaging measures, can be modelled as morphometric similarity networks (MSNs). Here, individual MSNs were derived from 105 neonates (59 preterm and 46 term) who were scanned between 38 and 45 weeks postmenstrual age (PMA). Inter-regional similarities were used as predictors in a regression model of age at the time of scanning and in a classification model to discriminate between preterm and term infant brains. When tested on unseen data, the regression model predicted PMA at scan with a mean absolute error of 0.70 ± 0.56 weeks, and the classification model achieved 92% accuracy. We conclude that MSNs predict chronological brain age accurately; and they provide a data-driven approach to identify networks that characterise typical maturation and those that contribute most to neuroanatomic variation associated with preterm birth.

YNIMG Journal 2016 Journal Article

Tracer kinetic modelling for DCE-MRI quantification of subtle blood–brain barrier permeability

  • Anna K. Heye
  • Michael J. Thrippleton
  • Paul A. Armitage
  • Maria del C. Valdés Hernández
  • Stephen D. Makin
  • Andreas Glatz
  • Eleni Sakka
  • Joanna M. Wardlaw

There is evidence that subtle breakdown of the blood–brain barrier (BBB) is a pathophysiological component of several diseases, including cerebral small vessel disease and some dementias. Dynamic contrast-enhanced MRI (DCE-MRI) combined with tracer kinetic modelling is widely used for assessing permeability and perfusion in brain tumours and body tissues where contrast agents readily accumulate in the extracellular space. However, in diseases where leakage is subtle, the optimal approach for measuring BBB integrity is likely to differ since the magnitude and rate of enhancement caused by leakage are extremely low; several methods have been reported in the literature, yielding a wide range of parameters even in healthy subjects. We hypothesised that the Patlak model is a suitable approach for measuring low-level BBB permeability with low temporal resolution and high spatial resolution and brain coverage, and that normal levels of scanner instability would influence permeability measurements. DCE-MRI was performed in a cohort of mild stroke patients (n =201) with a range of cerebral small vessel disease severity. We fitted these data to a set of nested tracer kinetic models, ranking their performance according to the Akaike information criterion. To assess the influence of scanner drift, we scanned 15 healthy volunteers that underwent a “sham” DCE-MRI procedure without administration of contrast agent. Numerical simulations were performed to investigate model validity and the effect of scanner drift. The Patlak model was found to be most appropriate for fitting low-permeability data, and the simulations showed v p and K Trans estimates to be reasonably robust to the model assumptions. However, signal drift (measured at approximately 0. 1% per minute and comparable to literature reports in other settings) led to systematic errors in calculated tracer kinetic parameters, particularly at low permeabilities. Our findings justify the growing use of the Patlak model in low-permeability states, which has the potential to provide valuable information regarding BBB integrity in a range of diseases. However, absolute values of the resulting tracer kinetic parameters should be interpreted with extreme caution, and the size and influence of signal drift should be measured where possible.

YNICL Journal 2014 Journal Article

Assessment of blood–brain barrier disruption using dynamic contrast-enhanced MRI. A systematic review

  • Anna K. Heye
  • Ross D. Culling
  • Maria del C. Valdés Hernández
  • Michael J. Thrippleton
  • Joanna M. Wardlaw

There is increasing recognition of the importance of blood-brain barrier (BBB) disruption in aging, dementia, stroke and multiple sclerosis in addition to more commonly-studied pathologies such as tumors. Dynamic contrast-enhanced MRI (DCE-MRI) is a method for studying BBB disruption in vivo. We review pathologies studied, scanning protocols and data analysis procedures to determine the range of available methods and their suitability to different pathologies. We systematically review the existing literature up to February 2014, seeking studies that assessed BBB integrity using T1-weighted DCE-MRI techniques in animals and humans in normal or abnormal brain tissues. The literature search provided 70 studies that were eligible for inclusion, involving 417 animals and 1564 human subjects in total. The pathologies most studied are intracranial neoplasms and acute ischemic strokes. There are large variations in the type of DCE-MRI sequence, the imaging protocols and the contrast agents used. Moreover, studies use a variety of different methods for data analysis, mainly based on model-free measurements and on the Patlak and Tofts models. Consequently, estimated K (Trans) values varied widely. In conclusion, DCE-MRI is shown to provide valuable information in a large variety of applications, ranging from common applications, such as grading of primary brain tumors, to more recent applications, such as assessment of subtle BBB dysfunction in Alzheimer's disease. Further research is required in order to establish consensus-based recommendations for data acquisition and analysis and, hence, improve inter-study comparability and promote wider use of DCE-MRI.

v2026.09.13