{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T21:12:24Z","timestamp":1790716344319,"version":"4.1.0"},"reference-count":32,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"funder":[{"DOI":"10.13039\/501100003196","name":"Ministry of Health, Italy","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003196","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","ejradiology.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["European Journal of Radiology"],"published-print":{"date-parts":[[2021,1]]},"DOI":"10.1016\/j.ejrad.2020.109460","type":"journal-article","created":{"date-parts":[[2020,12,2]],"date-time":"2020-12-02T11:52:28Z","timestamp":1606909948000},"page":"109460","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":26,"special_numbering":"C","title":["Texture analysis and machine learning to predict water T2 and fat fraction from non-quantitative MRI of thigh muscles in Facioscapulohumeral muscular dystrophy"],"prefix":"10.1016","volume":"134","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9927-4850","authenticated-orcid":false,"given":"Paolo Florent","family":"Felisaz","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giulia","family":"Colelli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3217-8930","authenticated-orcid":false,"given":"Elena","family":"Ballante","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesca","family":"Solazzo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1221-7747","authenticated-orcid":false,"given":"Matteo","family":"Paoletti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giancarlo","family":"Germani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6984-4816","authenticated-orcid":false,"given":"Francesco","family":"Santini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xeni","family":"Deligianni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Niels","family":"Bergsland","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mauro","family":"Monforte","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giorgio","family":"Tasca","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Enzo","family":"Ricci","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefano","family":"Bastianello","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Silvia","family":"Figini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna","family":"Pichiecchio","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ejrad.2020.109460_bib0005","doi-asserted-by":"crossref","DOI":"10.3233\/JND-180333","article-title":"Exploration of new contrasts, targets, and MR imaging and spectroscopy techniques for neuromuscular disease-A workshop report of working group 3 of the biomedicine and molecular biosciences COST action BM1304 MYO-MRI","author":"Strijkers","year":"2019","journal-title":"J. Neuromuscul. Dis."},{"key":"10.1016\/j.ejrad.2020.109460_bib0010","doi-asserted-by":"crossref","DOI":"10.3389\/fneur.2019.00078","article-title":"Advances in quantitative imaging of genetic and acquired myopathies: clinical applications and perspectives","author":"Paoletti","year":"2019","journal-title":"Front. Neurol."},{"key":"10.1016\/j.ejrad.2020.109460_bib0015","doi-asserted-by":"crossref","DOI":"10.1212\/WNL.0000000000004647","article-title":"Adding quantitative muscle MRI to the FSHD clinical trial toolbox","author":"Mul","year":"2017","journal-title":"Neurology"},{"key":"10.1016\/j.ejrad.2020.109460_bib0020","article-title":"MYO-MRI diagnostic protocols in genetic myopathies","author":"Chardon","year":"2019","journal-title":"Neuromuscul. Disord."},{"key":"10.1016\/j.ejrad.2020.109460_bib0025","doi-asserted-by":"crossref","first-page":"e590","DOI":"10.1016\/j.ejrad.2013.05.011","article-title":"Diffusion tensor imaging of the median nerve at 3.0 T using different MR scanners: agreement of FA and ADC measurements","volume":"82","author":"Guggenberger","year":"2013","journal-title":"Eur J Radiol."},{"key":"10.1016\/j.ejrad.2020.109460_bib0030","doi-asserted-by":"crossref","DOI":"10.1053\/ejpn.2002.0617","article-title":"A short protocol for muscle MRI in children with muscular dystrophies","author":"Mercuri","year":"2002","journal-title":"Eur. J. Paediatr. Neurol."},{"key":"10.1016\/j.ejrad.2020.109460_bib0035","doi-asserted-by":"crossref","DOI":"10.1016\/0960-8966(91)90039-U","article-title":"Population frequencies of inherited neuromuscular diseases-A world survey","author":"Emery","year":"1991","journal-title":"Neuromuscul. Disord."},{"key":"10.1016\/j.ejrad.2020.109460_bib0040","doi-asserted-by":"crossref","DOI":"10.1007\/s00330-010-1799-2","article-title":"Neuromuscular imaging in inherited muscle diseases","author":"Wattjes","year":"2010","journal-title":"Eur. Radiol."},{"key":"10.1016\/j.ejrad.2020.109460_bib0045","doi-asserted-by":"crossref","DOI":"10.1002\/ana.24640","article-title":"Magnetic resonance imaging in a large cohort of facioscapulohumeral muscular dystrophy patients: pattern refinement and implications for clinical trials","author":"Tasca","year":"2016","journal-title":"Ann. Neurol."},{"key":"10.1016\/j.ejrad.2020.109460_bib0050","doi-asserted-by":"crossref","DOI":"10.1002\/jcsm.12473","article-title":"Tracking muscle wasting and disease activity in facioscapulohumeral muscular dystrophy by qualitative longitudinal imaging","author":"Monforte","year":"2019","journal-title":"J. Cachexia. Sarcopenia Muscle."},{"key":"10.1016\/j.ejrad.2020.109460_bib0055","doi-asserted-by":"crossref","DOI":"10.1212\/WNL.0000000000002640","article-title":"Quantitative MRI reveals decelerated fatty infiltration in muscles of active FSHD patients","author":"Janssen","year":"2016","journal-title":"Neurology"},{"key":"10.1016\/j.ejrad.2020.109460_bib0060","doi-asserted-by":"crossref","DOI":"10.1109\/TSMC.1973.4309314","article-title":"Textural features for image classification","author":"Haralick","year":"1973","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"10.1016\/j.ejrad.2020.109460_bib0065","article-title":"Optimization of fat-water separation algorithm selection and options using image-based metrics with validation by ISMRM fat-water challenge datasets","author":"Welch","year":"2013","journal-title":"Proc. 21st Sci. Meet. Int. Soc. Magn. Reson. Med."},{"key":"10.1016\/j.ejrad.2020.109460_bib0070","doi-asserted-by":"crossref","DOI":"10.1002\/nbm.3459","article-title":"Simultaneous muscle water T2 and fat fraction mapping using transverse relaxometry with stimulated echo compensation","author":"Marty","year":"2016","journal-title":"NMR Biomed."},{"key":"10.1016\/j.ejrad.2020.109460_bib0075","doi-asserted-by":"crossref","DOI":"10.1002\/jmri.24619","article-title":"Extended phase graphs: dephasing, RF pulses, and echoes - pure and simple","author":"Weigel","year":"2015","journal-title":"J. Magn. Reson. Imaging."},{"key":"10.1016\/j.ejrad.2020.109460_bib0080","doi-asserted-by":"crossref","DOI":"10.1158\/0008-5472.CAN-18-0125","article-title":"Lifex: a freeware for radiomic feature calculation in multimodality imaging to accelerate advances in the characterization of tumor heterogeneity","author":"Nioche","year":"2018","journal-title":"Cancer Res."},{"key":"10.1016\/j.ejrad.2020.109460_bib0085","series-title":"Elements of Statistical Learning","author":"Hastie","year":"2009"},{"key":"10.1016\/j.ejrad.2020.109460_bib0090","article-title":"Ridge regression: biased estimation for nonorthogonal problems","author":"Hoerl","year":"1970","journal-title":"Technometrics"},{"key":"10.1016\/j.ejrad.2020.109460_bib0095","doi-asserted-by":"crossref","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","article-title":"Regression shrinkage and selection via the lasso","author":"Tibshirani","year":"1996","journal-title":"J. R. Stat. Soc. Ser. B."},{"key":"10.1016\/j.ejrad.2020.109460_bib0100","series-title":"Stat. Model. S","article-title":"Generalized additive models","author":"Hastie","year":"2017"},{"key":"10.1016\/j.ejrad.2020.109460_bib0105","doi-asserted-by":"crossref","DOI":"10.1109\/TIT.1967.1053964","article-title":"Nearest neighbor pattern classification","author":"Cover","year":"1967","journal-title":"IEEE Trans. Inf. Theory."},{"key":"10.1016\/j.ejrad.2020.109460_bib0110","series-title":"Adv. Neural Inf. Process. Syst.","article-title":"Support vector regression machines","author":"Drucker","year":"1997"},{"key":"10.1016\/j.ejrad.2020.109460_bib0115","series-title":"Classification and Regression Trees","author":"Breiman","year":"2017"},{"key":"10.1016\/j.ejrad.2020.109460_bib0120","series-title":"Machine Learning","author":"Breiman","year":"2001"},{"key":"10.1016\/j.ejrad.2020.109460_bib0125","doi-asserted-by":"crossref","DOI":"10.1016\/j.neurol.2016.08.002","article-title":"Muscle MRI of facioscapulohumeral dystrophy (FSHD): a growing demand and a promising approach","author":"Fatehi","year":"2016","journal-title":"Rev. Neurol. (Paris)."},{"key":"10.1016\/j.ejrad.2020.109460_bib0130","doi-asserted-by":"crossref","DOI":"10.1007\/s00415-016-8361-3","article-title":"MRI as outcome measure in facioscapulohumeral muscular dystrophy: 1-year follow-up of 45 patients","author":"Andersen","year":"2017","journal-title":"J. Neurol."},{"key":"10.1016\/j.ejrad.2020.109460_bib0135","doi-asserted-by":"crossref","DOI":"10.1002\/mus.26038","article-title":"MRI change metrics of facioscapulohumeral muscular dystrophy: stir and T1","author":"Ferguson","year":"2018","journal-title":"Muscle and Nerve."},{"key":"10.1016\/j.ejrad.2020.109460_bib0140","doi-asserted-by":"crossref","DOI":"10.1016\/j.mri.2005.10.002","article-title":"Texture analysis of magnetic resonance images of rat muscles during atrophy and regeneration","author":"Mahmoud-Ghoneim","year":"2006","journal-title":"Magn. Reson. Imaging."},{"key":"10.1016\/j.ejrad.2020.109460_bib0145","doi-asserted-by":"crossref","DOI":"10.1016\/S0730-725X(99)00066-1","article-title":"Comparison of automated and visual texture analysis in MRI: characterization of normal and diseased skeletal muscle","author":"Herlidou","year":"1999","journal-title":"Magn. Reson. Imaging."},{"key":"10.1016\/j.ejrad.2020.109460_bib0150","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0184059","article-title":"Automated diagnosis of myositis from muscle ultrasound: exploring the use of machine learning and deep learning methods","author":"Burlina","year":"2017","journal-title":"PLoS One"},{"key":"10.1016\/j.ejrad.2020.109460_bib0155","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-019-44416-8","article-title":"Deep learning convolutional neural networks for the automatic quantification of muscle fat infiltration following whiplash injury","author":"Weber","year":"2019","journal-title":"Sci. Rep."},{"key":"10.1016\/j.ejrad.2020.109460_bib0160","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2018.08.012","article-title":"Texture analysis for muscular dystrophy classification in MRI with improved class activation mapping","author":"Cai","year":"2019","journal-title":"Pattern Recognit."}],"container-title":["European Journal of Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0720048X20306501?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0720048X20306501?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T07:21:55Z","timestamp":1759994515000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0720048X20306501"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1]]},"references-count":32,"alternative-id":["S0720048X20306501"],"URL":"https:\/\/doi.org\/10.1016\/j.ejrad.2020.109460","relation":{},"ISSN":["0720-048X"],"issn-type":[{"value":"0720-048X","type":"print"}],"subject":[],"published":{"date-parts":[[2021,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Texture analysis and machine learning to predict water T2 and fat fraction from non-quantitative MRI of thigh muscles in Facioscapulohumeral muscular dystrophy","name":"articletitle","label":"Article Title"},{"value":"European Journal of Radiology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ejrad.2020.109460","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2020 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"109460"}}