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Recommendations to improve imaging and analysis of brain lesion load and atrophy in longitudinal studies of multiple sclerosis

Vrenken, H; Jenkinson, M; Horsfield, MA; Battaglini, M; van Schijndel, RA; Rostrup, E; Geurts, JJG; ... de Stefano, N; + view all (2013) Recommendations to improve imaging and analysis of brain lesion load and atrophy in longitudinal studies of multiple sclerosis. JOURNAL OF NEUROLOGY , 260 (10) pp. 2458-2471. 10.1007/s00415-012-6762-5. Green open access

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Abstract

Focal lesions and brain atrophy are the most extensively studied aspects of multiple sclerosis (MS), but the image acquisition and analysis techniques used can be further improved, especially those for studying within-patient changes of lesion load and atrophy longitudinally. Improved accuracy and sensitivity will reduce the numbers of patients required to detect a given treatment effect in a trial, and ultimately, will allow reliable characterization of individual patients for personalized treatment. Based on open issues in the field of MS research, and the current state of the art in magnetic resonance image analysis methods for assessing brain lesion load and atrophy, this paper makes recommendations to improve these measures for longitudinal studies of MS. Briefly, they are (1) images should be acquired using 3D pulse sequences, with near-isotropic spatial resolution and multiple image contrasts to allow more comprehensive analyses of lesion load and atrophy, across timepoints. Image artifacts need special attention given their effects on image analysis results. (2) Automated image segmentation methods integrating the assessment of lesion load and atrophy are desirable. (3) A standard dataset with benchmark results should be set up to facilitate development, calibration, and objective evaluation of image analysis methods for MS.

Type: Article
Title: Recommendations to improve imaging and analysis of brain lesion load and atrophy in longitudinal studies of multiple sclerosis
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/s00415-012-6762-5
Publisher version: http://dx.doi.org/ 10.1007/s00415-012-6762-5
Language: English
Additional information: Copyright © The Author(s) 2012. This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
Keywords: Clinical Neurology, Magnetic Resonance Imaging, Multiple Sclerosis, Brain Atrophy, White Matter Lesions, Image Analysis, White-matter Lesions, Gradient Nonlinearity Correction, Sensitive Inversion-recovery, Computer-assisted Techniques, Magnetic-resonance Images, Random-field Model, Mr-images, Automatic Segmentation, Alzheimers-disease, Spatiotemporal Distribution
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Department of Neuromuscular Diseases
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1382122
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