Review

Application of texture analysis to muscle MRI: 2 – technical recommendations

¹ Medical Research Institute, Ninewells Hospital, Dundee, Scotland, UK
² Institute of Myology, University Hospital Pitié-Salpêtrière, Paris, France
³ Faculty of Computer Science, Bialystok University of Technology, Bialystok, Poland
⁴ Nalecz Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences, Warsaw, Poland
⁵ Laboratory of Image Science and Technology, School of Computer Science and Engineering, Southeast University, Nanjing, 210096, China
⁶ Centre de Recherche en Information Biomédicale Sino-français (CRIBs), Nanjing, China
⁷ INSERM, U1099, Rennes, F-35000, France
⁸ Université de Rennes 1, LTSI, Rennes, F-35042, France
⁹ Centre de Recherche en Information Biomédicale Sino-français (CRIBs), Rennes, F-35000, France
¹⁰ PRISM-Bio-SCANs, University of Rennes, Rennes, France

^* e-mail: r.a.lerski@dundee.ac.uk

Received: 10 December 2014
Accepted: 26 February 2015
Published online: 19 March 2015

Abstract

A goal of the multicenter European Cooperation in Science and Technology (COST) action MYO-MRI is to optimize Magnetic Resonance Imaging Texture Analysis (MRI-TA) methods for application in the study of muscle disease. This paper deals with recommendations on the optimal methodology to collect the MRI data, to analyse it via texture analysis and to make conclusions from the resultant texture parameter data. A full and detailed description is provided with respect to MR image quality control, sequence choice, image pre-processing, region of interest selection, texture analysis methods and data analysis. A series of conclusions are presented.