Analysis of dynamic texture and spatial spectral descriptors of dynamic contrast-enhanced brain magnetic resonance images for studying small vessel disease

Bernal, J., Valdes-Hernandez, M. d. C., Escudero, J., Viksne, L., Heye, A. K., Armitage, P. A., Makin, S., Touyz, R. and Wardlaw, J. M. (2019) Analysis of dynamic texture and spatial spectral descriptors of dynamic contrast-enhanced brain magnetic resonance images for studying small vessel disease. Magnetic Resonance Imaging, (doi: 10.1016/j.mri.2019.11.001) (PMID:31730881) (In Press)

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Abstract

Cerebral small vessel disease (SVD) comprises various pathological processes affecting small brain vessels and damaging white and grey matter. In this paper, we propose a framework comprising region of interest sampling, dynamic spectral and texture description, functional principal component analysis, and statistical analysis to study exogenous contrast agent distribution over time in various brain regions in patients with recent mild stroke and SVD features.We compared our results against current semi-quantitative surrogates of dysfunction such as signal enhancement area and slope. Biological sex, stroke lesion type and overall burden of white matter hyperintensities (WMH) were significant predictors of intensity, spectral, and texture features extracted from the ventricular region (p-value < 0.05), explaining between a fifth and a fourth of the data variance (0.20 ≤Adj.R2 ≤ 0.25). We observed that spectral feature reflected more the dysfunction compared to other descriptors since the overall WMH burden explained consistently the power spectra variability in blood vessels, cerebrospinal fluid, deep grey matter and white matter. Our preliminary results show the potential of the framework for the analysis of dynamic contrast-enhanced brain magnetic resonance imaging acquisitions in SVD since significant variation in our metrics was related to the burden of SVD features. Therefore, our proposal may increase sensitivity to detect subtle features of small vessel dysfunction. A public version of the code will be released on our research website.

Item Type:Articles
Additional Information:This work was supported by the Row Fogo Charitable Trust (MVH) grant no. BRO-D.FID3668413, Wellcome Trust (patient recruitment, scanning, primary study Ref No. WT088134/Z/09/A), Fondation Leducq (Perivascular Spaces Transatlantic Network of Excellence), and EU Horizon 2020 (SVDs@Target) and the MRC UK Dementia Research Institute at the University of Edinburgh (Wardlaw programme).
Status:In Press
Refereed:Yes
Glasgow Author(s) Enlighten ID:Makin, Dr Stephen and Touyz, Professor Rhian
Authors: Bernal, J., Valdes-Hernandez, M. d. C., Escudero, J., Viksne, L., Heye, A. K., Armitage, P. A., Makin, S., Touyz, R., and Wardlaw, J. M.
College/School:College of Medical Veterinary and Life Sciences > Institute of Cardiovascular and Medical Sciences
Journal Name:Magnetic Resonance Imaging
Publisher:Elsevier
ISSN:0730-725X
ISSN (Online):0730-725X
Published Online:13 November 2019
Copyright Holders:Copyright © 2019 The Authors
First Published:First published in Magnetic Resonance Imaging 2019
Publisher Policy:Reproduced under a Creative Commons license

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