{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T02:40:21Z","timestamp":1789958421519,"version":"4.0.1"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2025,3,14]],"date-time":"2025-03-14T00:00:00Z","timestamp":1741910400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,3,14]],"date-time":"2025-03-14T00:00:00Z","timestamp":1741910400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100020950","name":"National Science and Technology Council","doi-asserted-by":"publisher","award":["NSTC 112-2221-E-182 -006-MY3"],"award-info":[{"award-number":["NSTC 112-2221-E-182 -006-MY3"]}],"id":[{"id":"10.13039\/501100020950","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100012553","name":"Chang Gung Memorial Hospital","doi-asserted-by":"publisher","award":["CMRPD1N0011"],"award-info":[{"award-number":["CMRPD1N0011"]}],"id":[{"id":"10.13039\/100012553","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100012553","name":"Chang Gung Memorial Hospital","doi-asserted-by":"publisher","award":["CMRPD1M0401"],"award-info":[{"award-number":["CMRPD1M0401"]}],"id":[{"id":"10.13039\/100012553","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100012553","name":"Chang Gung Memorial Hospital","doi-asserted-by":"publisher","award":["CMRPG1L0021"],"award-info":[{"award-number":["CMRPG1L0021"]}],"id":[{"id":"10.13039\/100012553","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006606","name":"Tianjin Natural Science Foundation","doi-asserted-by":"crossref","award":["22JCZDJC00220"],"award-info":[{"award-number":["22JCZDJC00220"]}],"id":[{"id":"10.13039\/501100006606","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Foundation of State Key Laboratory of Ultrasound in Medicine and Engineering","award":["2022KFKT004"],"award-info":[{"award-number":["2022KFKT004"]}]},{"name":"Tianjin Graduate Research Innovation Project","award":["2022BKY099"],"award-info":[{"award-number":["2022BKY099"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Digit Imaging. Inform. med."],"DOI":"10.1007\/s10278-025-01450-5","type":"journal-article","created":{"date-parts":[[2025,3,14]],"date-time":"2025-03-14T13:35:42Z","timestamp":1741959342000},"page":"3823-3836","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Radiomics with Ultrasound Radiofrequency Data for Improving Evaluation of Duchenne Muscular Dystrophy"],"prefix":"10.1007","volume":"38","author":[{"given":"Dong","family":"Yan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ya-Wen","family":"Chuang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chia-Wei","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeng-Yi","family":"Shieh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wen-Chin","family":"Weng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5604-1800","authenticated-orcid":false,"given":"Po-Hsiang","family":"Tsui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,3,14]]},"reference":[{"issue":"1","key":"1450_CR1","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1186\/s13023-020-01430-8","volume":"15","author":"S Crisafulli","year":"2020","unstructured":"Crisafulli S, Sultana J, Fontana A, Salvo F, Messina S, Trifir\u00f2 G. Global epidemiology of Duchenne muscular dystrophy: an updated systematic review and meta-analysis. Orphanet J Rare Dis. 2020 Jun 5;15(1):141.","journal-title":"Orphanet J Rare Dis"},{"issue":"6","key":"1450_CR2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0287774","volume":"18","author":"M Orso","year":"2023","unstructured":"Orso M, Migliore A, Polistena B, Russo E, Gatto F, Monterubbianesi M, d'Angela D, Spandonaro F, Pane M. Duchenne muscular dystrophy in Italy: A systematic review of epidemiology, quality of life, treatment adherence, and economic impact. PLoS One. 2023 Jun 27;18(6):e0287774.","journal-title":"PLoS One"},{"issue":"8","key":"1450_CR3","doi-asserted-by":"publisher","first-page":"3733","DOI":"10.1007\/s00415-023-11796-x","volume":"270","author":"M Chang","year":"2023","unstructured":"Chang M, Cai Y, Gao Z, Chen X, Liu B, Zhang C, Yu W, Cao Q, Shen Y, Yao X, Chen X, Sun H. Duchenne muscular dystrophy: pathogenesis and promising therapies. J Neurol. 2023 Aug;270(8):3733-3749.","journal-title":"J Neurol"},{"issue":"3","key":"1450_CR4","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1016\/S1474-4422(18)30024-3","volume":"17","author":"DJ Birnkrant","year":"2018","unstructured":"Birnkrant DJ, Bushby K, Bann CM, Apkon SD, Blackwell A, Brumbaugh D, Case LE, Clemens PR, Hadjiyannakis S, Pandya S, Street N, Tomezsko J, Wagner KR, Ward LM, Weber DR; DMD Care Considerations Working Group. Diagnosis and management of Duchenne muscular dystrophy, part 1: diagnosis, and neuromuscular, rehabilitation, endocrine, and gastrointestinal and nutritional management. Lancet Neurol. 2018 Mar;17(3):251-267.","journal-title":"Lancet Neurol"},{"issue":"4","key":"1450_CR5","doi-asserted-by":"publisher","first-page":"347","DOI":"10.1016\/S1474-4422(18)30025-5","volume":"17","author":"DJ Birnkrant","year":"2018","unstructured":"Birnkrant DJ, Bushby K, Bann CM, Alman BA, Apkon SD, Blackwell A, Case LE, Cripe L, Hadjiyannakis S, Olson AK, Sheehan DW, Bolen J, Weber DR, Ward LM; DMD Care Considerations Working Group. Diagnosis and management of Duchenne muscular dystrophy, part 2: respiratory, cardiac, bone health, and orthopaedic management. Lancet Neurol. 2018 Apr;17(4):347-361.","journal-title":"Lancet Neurol"},{"issue":"5","key":"1450_CR6","doi-asserted-by":"publisher","first-page":"445","DOI":"10.1016\/S1474-4422(18)30026-7","volume":"17","author":"DJ Birnkrant","year":"2018","unstructured":"Birnkrant DJ, Bushby K, Bann CM, Apkon SD, Blackwell A, Colvin MK, Cripe L, Herron AR, Kennedy A, Kinnett K, Naprawa J, Noritz G, Poysky J, Street N, Trout CJ, Weber DR, Ward LM; DMD Care Considerations Working Group. Diagnosis and management of Duchenne muscular dystrophy, part 3: primary care, emergency management, psychosocial care, and transitions of care across the lifespan. Lancet Neurol. 2018 May;17(5):445-455.","journal-title":"Lancet Neurol."},{"issue":"3","key":"1450_CR7","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1002\/mus.23905","volume":"48","author":"CM McDonald","year":"2013","unstructured":"McDonald CM, Henricson EK, Abresch RT, Florence J, Eagle M, Gappmaier E, Glanzman AM; PTC124-GD-007-DMD Study Group; Spiegel R, Barth J, Elfring G, Reha A, Peltz SW. The 6-minute walk test and other clinical endpoints in duchenne muscular dystrophy: reliability, concurrent validity, and minimal clinically important differences from a multicenter study. Muscle Nerve. 2013 Sep;48(3):357-68.","journal-title":"Muscle Nerve"},{"issue":"4","key":"1450_CR8","doi-asserted-by":"publisher","first-page":"e0283669","DOI":"10.1371\/journal.pone.0283669","volume":"18","author":"V Ayyar Gupta","year":"2023","unstructured":"Ayyar Gupta V, Pitchforth JM, Domingos J, Ridout D, Iodice M, Rye C, Chesshyre M, Wolfe A, Selby V, Mayhew A, Mazzone ES, Ricotti V, Hogrel JY, Niks EH, de Groot I, Servais L, Straub V, Mercuri E, Manzur AY, Muntoni F, iMDEX Consortium and the U.K. NorthStar Clinical Network (2023) Determining minimal clinically important differences in the North Star Ambulatory Assessment (NSAA) for patients with Duchenne muscular dystrophy. PLoS One 18(4):e0283669. https:\/\/doi.org\/10.1371\/journal.pone.0283669","journal-title":"PLoS One"},{"issue":"6","key":"1450_CR9","doi-asserted-by":"publisher","first-page":"476","DOI":"10.1016\/j.nmd.2018.02.007","volume":"28","author":"A Pichiecchio","year":"2018","unstructured":"Pichiecchio A, Alessandrino F, Bortolotto C, Cerica A, Rosti C, Raciti MV, Rossi M, Berardinelli A, Baranello G, Bastianello S, Calliada F (2018) Muscle ultrasound elastography and MRI in preschool children with Duchenne muscular dystrophy. Neuromuscul Disord. 28(6):476\u2013483","journal-title":"Neuromuscul Disord."},{"issue":"4","key":"1450_CR10","doi-asserted-by":"publisher","first-page":"674","DOI":"10.1002\/jcu.23411","volume":"51","author":"J Hu","year":"2023","unstructured":"Hu J, Jiang L, Hong S, Cheng L, Wang Q, Peng X, Qin J, Zou L (2023) Quantitative muscle ultrasound in children with Duchenne muscular dystrophy: Comparing to magnetic resonance imaging. J Clin Ultrasound. 51(4):674\u2013679","journal-title":"J Clin Ultrasound."},{"issue":"11","key":"1450_CR11","doi-asserted-by":"publisher","first-page":"2646","DOI":"10.1007\/s00415-018-9037-y","volume":"265","author":"K Mul","year":"2018","unstructured":"Mul K, Horlings CGC, Vincenten SCC, Voermans NC, van Engelen BGM, van Alfen N. Quantitative muscle MRI and ultrasound for facioscapulohumeral muscular dystrophy: complementary imaging biomarkers. J Neurol. 2018 Nov;265(11):2646-2655.","journal-title":"J Neurol."},{"issue":"2","key":"1450_CR12","doi-asserted-by":"publisher","first-page":"715","DOI":"10.1109\/JBHI.2021.3100319","volume":"26","author":"H Wen","year":"2022","unstructured":"Wen H, Zheng W, Li M, Li Q, Liu Q, Zhou J, Liu Z, Chen X. Multiparametric Quantitative US Examination of Liver Fibrosis: A Feature-Engineering and Machine-Learning Based Analysis. IEEE J Biomed Health Inform. 2022 Feb;26(2):715-726.","journal-title":"IEEE J Biomed Health Inform."},{"issue":"5","key":"1450_CR13","doi-asserted-by":"publisher","first-page":"633","DOI":"10.1002\/ana.24904","volume":"81","author":"CM Zaidman","year":"2017","unstructured":"Zaidman CM, Wu JS, Kapur K, Pasternak A, Madabusi L, Yim S, Pacheck A, Szelag H, Harrington T, Darras BT, Rutkove SB (2017) Quantitative muscle ultrasound detects disease progression in Duchenne muscular dystrophy. Ann Neurol. 81(5):633\u2013640. https:\/\/doi.org\/10.1002\/ana.24904","journal-title":"Ann Neurol."},{"key":"1450_CR14","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1016\/j.ejpn.2020.06.001","volume":"28","author":"K Vill","year":"2020","unstructured":"Vill K, Sehri M, M\u00fcller C, Hannibal I, Huf V, Idriess M, Gerstl L, Bonfert MV, Tacke M, Schroeder AS, Landgraf MN, M\u00fcller-Felber W, Blaschek A. Qualitative and quantitative muscle ultrasound in patients with Duchenne muscular dystrophy: Where do sonographic changes begin? Eur J Paediatr Neurol. 2020 Sep;28:142-150.","journal-title":"Eur J Paediatr Neurol."},{"issue":"2","key":"1450_CR15","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1002\/mus.24296","volume":"51","author":"I Shklyar","year":"2015","unstructured":"Shklyar I, Geisbush TR, Mijialovic AS, Pasternak A, Darras BT, Wu JS, Rutkove SB, Zaidman CM (2015) Quantitative muscle ultrasound in Duchenne muscular dystrophy: a comparison of techniques. Muscle Nerve. 51(2):207\u2013213. https:\/\/doi.org\/10.1002\/mus.24296","journal-title":"Muscle Nerve."},{"issue":"1","key":"1450_CR16","doi-asserted-by":"publisher","first-page":"4429","DOI":"10.1038\/s41598-017-04131-8","volume":"7","author":"WC Weng","year":"2017","unstructured":"Weng WC, Tsui PH, Lin CW, Lu CH, Lin CY, Shieh JY, Lu FL, Ee TW, Wu KW, Lee WT. Evaluation of muscular changes by ultrasound Nakagami imaging in Duchenne muscular dystrophy. Sci Rep. 2017 Jun 30;7(1):4429.","journal-title":"Sci Rep."},{"issue":"7","key":"1450_CR17","doi-asserted-by":"publisher","first-page":"715","DOI":"10.3390\/e22070715","volume":"22","author":"D Yan","year":"2020","unstructured":"Yan D, Li Q, Lin CW, Shieh JY, Weng WC, Tsui PH. Clinical Evaluation of Duchenne Muscular Dystrophy Severity Using Ultrasound Small-Window Entropy Imaging. Entropy (Basel). 2020 Jun 28;22(7):715.","journal-title":"Entropy (Basel)."},{"issue":"2","key":"1450_CR18","doi-asserted-by":"publisher","first-page":"336","DOI":"10.1109\/TUFFC.2015.2513958","volume":"63","author":"ML Oelze","year":"2016","unstructured":"Oelze ML, Mamou J. Review of Quantitative Ultrasound: Envelope Statistics and Backscatter Coefficient Imaging and Contributions to Diagnostic Ultrasound. IEEE Trans Ultrason Ferroelectr Freq Control. 2016 Feb;63(2):336-51.","journal-title":"IEEE Trans Ultrason Ferroelectr Freq Control."},{"issue":"4","key":"1450_CR19","doi-asserted-by":"publisher","first-page":"488","DOI":"10.2967\/jnumed.118.222893","volume":"61","author":"ME Mayerhoefer","year":"2020","unstructured":"Mayerhoefer ME, Materka A, Langs G, H\u00e4ggstr\u00f6m I, Szczypi\u0144ski P, Gibbs P, Cook G (2020) Introduction to Radiomics. J Nucl Med. 61(4):488\u2013495. https:\/\/doi.org\/10.2967\/jnumed.118.222893","journal-title":"J Nucl Med."},{"issue":"12","key":"1450_CR20","doi-asserted-by":"publisher","first-page":"749","DOI":"10.1038\/nrclinonc.2017.141","volume":"14","author":"P Lambin","year":"2017","unstructured":"Lambin P, Leijenaar RTH, Deist TM, Peerlings J, de Jong EEC, van Timmeren J, Sanduleanu S, Larue RTHM, Even AJG, Jochems A, van Wijk Y, Woodruff H, van Soest J, Lustberg T, Roelofs E, van Elmpt W, Dekker A, Mottaghy FM, Wildberger JE, Walsh S (2017) Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol. 14(12):749\u2013762","journal-title":"Nat Rev Clin Oncol."},{"issue":"11","key":"1450_CR21","doi-asserted-by":"publisher","first-page":"2737","DOI":"10.3390\/diagnostics12112737","volume":"12","author":"M Al-Hasani","year":"2022","unstructured":"Al-Hasani M, Sultan LR, Sagreiya H, Cary TW, Karmacharya MB, Sehgal CM. Ultrasound Radiomics for the Detection of Early-Stage Liver Fibrosis. Diagnostics (Basel). 2022;12(11):2737.","journal-title":"Diagnostics (Basel)."},{"key":"1450_CR22","doi-asserted-by":"publisher","first-page":"1203","DOI":"10.3389\/fonc.2019.01203","volume":"9","author":"Y Dong","year":"2019","unstructured":"Dong Y, Wang QM, Li Q, Li LY, Zhang Q, Yao Z, Dai M, Yu J, Wang WP (2019) Preoperative Prediction of Microvascular Invasion of Hepatocellular Carcinoma: Radiomics Algorithm Based on Ultrasound Original Radio Frequency Signals. Front Oncol. 9:1203","journal-title":"Front Oncol."},{"issue":"4","key":"1450_CR23","doi-asserted-by":"publisher","first-page":"2386","DOI":"10.1007\/s00330-022-09268-3","volume":"33","author":"XY Ge","year":"2023","unstructured":"Ge XY, Lan ZK, Lan QQ, Lin HS, Wang GD, Chen J. Diagnostic accuracy of ultrasound-based multimodal radiomics modeling for fibrosis detection in chronic kidney disease. Eur Radiol. 2023;33(4):2386-2398.","journal-title":"Eur Radiol."},{"issue":"6245","key":"1450_CR24","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1126\/science.aaa8415","volume":"349","author":"MI Jordan","year":"2015","unstructured":"Jordan MI, Mitchell TM. Machine learning: Trends, perspectives, and prospects. Science. 2015 Jul 17;349(6245):255-60.","journal-title":"Science."},{"issue":"6","key":"1450_CR25","doi-asserted-by":"publisher","first-page":"803","DOI":"10.1038\/s41592-023-01886-z","volume":"20","author":"J Banerjee","year":"2023","unstructured":"Banerjee J, Taroni JN, Allaway RJ, Prasad DV, Guinney J, Greene C. Machine learning in rare disease. Nat Methods. 2023;20(6):803-814.","journal-title":"Nat Methods."},{"issue":"4","key":"1450_CR26","doi-asserted-by":"publisher","first-page":"2157","DOI":"10.1007\/s00330-018-5747-x","volume":"29","author":"Y Zhang","year":"2019","unstructured":"Zhang Y, Zhang B, Liang F, Liang S, Zhang Y, Yan P, Ma C, Liu A, Guo F, Jiang C (2019) Radiomics features on non-contrast-enhanced CT scan can precisely classify AVM-related hematomas from other spontaneous intraparenchymal hematoma types. Eur Radiol. 29(4):2157\u20132165","journal-title":"Eur Radiol."},{"issue":"4","key":"1450_CR27","doi-asserted-by":"publisher","first-page":"880","DOI":"10.1016\/j.ultrasmedbio.2020.12.012","volume":"47","author":"MT Paris","year":"2021","unstructured":"Paris MT, Mourtzakis M. Muscle Composition Analysis of Ultrasound Images: A Narrative Review of Texture Analysis. Ultrasound Med Biol. 2021;47(4):880-895.","journal-title":"Ultrasound Med Biol."},{"key":"1450_CR28","doi-asserted-by":"publisher","first-page":"78","DOI":"10.3389\/fneur.2019.00078","volume":"10","author":"M Paoletti","year":"2019","unstructured":"Paoletti M, Pichiecchio A, Cotti Piccinelli S, Tasca G, Berardinelli AL, Padovani A, Filosto M (2019) Advances in Quantitative Imaging of Genetic and Acquired Myopathies: Clinical Applications and Perspectives. Front Neurol. 10:78. https:\/\/doi.org\/10.3389\/fneur.2019.00078","journal-title":"Front Neurol."},{"issue":"1","key":"1450_CR29","first-page":"5","volume":"9","author":"E Ciafaloni","year":"2016","unstructured":"Ciafaloni E, Kumar A, Liu K, Pandya S, Westfield C, Fox DJ, Caspers Conway KM, Cunniff C, Mathews K, West N, Romitti PA, McDermott MP (2016) Age at onset of first signs or symptoms predicts age at loss of ambulation in Duchenne and Becker Muscular Dystrophy: Data from the MD STARnet. J Pediatr Rehabil Med. 9(1):5\u201311","journal-title":"J Pediatr Rehabil Med."},{"issue":"21","key":"1450_CR30","doi-asserted-by":"publisher","first-page":"e104","DOI":"10.1158\/0008-5472.CAN-17-0339","volume":"77","author":"JJM van Griethuysen","year":"2017","unstructured":"van Griethuysen JJM, Fedorov A, Parmar C, Hosny A, Aucoin N, Narayan V, Beets-Tan RGH, Fillion-Robin JC, Pieper S, Aerts HJWL. Computational Radiomics System to Decode the Radiographic Phenotype. Cancer Res. 2017 Nov 1;77(21):e104-e107.","journal-title":"Cancer Res."},{"issue":"2","key":"1450_CR31","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1109\/TCYB.2021.3139898","volume":"53","author":"Y Wang","year":"2023","unstructured":"Wang Y, Li X, Ruiz R. Feature Selection With Maximal Relevance and Minimal Supervised Redundancy. IEEE Trans Cybern. 2023 Feb;53(2):707-717.","journal-title":"IEEE Trans Cybern."},{"issue":"5","key":"1450_CR32","doi-asserted-by":"publisher","first-page":"e185","DOI":"10.1002\/mp.13678","volume":"47","author":"M Avanzo","year":"2020","unstructured":"Avanzo M, Wei L, Stancanello J, Valli\u00e8res M, Rao A, Morin O, Mattonen SA, El Naqa I (2020) Machine and deep learning methods for radiomics. Med Phys. 47(5):e185\u2013e202","journal-title":"Med Phys."},{"issue":"16","key":"1450_CR33","doi-asserted-by":"publisher","first-page":"15103","DOI":"10.1007\/s00432-023-05327-4","volume":"149","author":"C Wu","year":"2023","unstructured":"Wu C, Du X, Zhang Y, Zhu L, Chen J, Chen Y, Wei Y, Liu Y (2023) Five machine learning-based radiomics models for preoperative prediction of histological grade in hepatocellular carcinoma. J Cancer Res Clin Oncol. 149(16):15103\u201315112","journal-title":"J Cancer Res Clin Oncol."},{"issue":"1","key":"1450_CR34","doi-asserted-by":"publisher","first-page":"13923","DOI":"10.1038\/s41598-024-64208-z","volume":"14","author":"H Horng","year":"2024","unstructured":"Horng H, Scott C, Winham S, Jensen M, Pantalone L, Mankowski W, Kerlikowske K, Vachon CM, Kontos D, Shinohara RT (2024) Multivariate testing and effect size measures for batch effect evaluation in radiomic features. Sci Rep. 14(1):13923","journal-title":"Sci Rep."},{"issue":"5","key":"1450_CR35","doi-asserted-by":"publisher","first-page":"1399","DOI":"10.1002\/jmri.27434","volume":"53","author":"H Peng","year":"2021","unstructured":"Peng H, Huo J, Li B, Cui Y, Zhang H, Zhang L, Ma L (2021) Predicting Isocitrate Dehydrogenase (IDH) Mutation Status in Gliomas Using Multiparameter MRI Radiomics Features. J Magn Reson Imaging. 53(5):1399\u20131407","journal-title":"J Magn Reson Imaging."},{"key":"1450_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.jocn.2016.01.041","volume":"33","author":"NG Simon","year":"2016","unstructured":"Simon NG, Noto YI, Zaidman CM. Skeletal muscle imaging in neuromuscular disease. J Clin Neurosci. 2016 Nov;33:1-10.","journal-title":"J Clin Neurosci."},{"issue":"1","key":"1450_CR37","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1038\/s41572-021-00248-3","volume":"7","author":"D Duan","year":"2021","unstructured":"Duan D, Goemans N, Takeda S, Mercuri E, Aartsma-Rus A. Duchenne muscular dystrophy. Nat Rev Dis Primers. 2021 Feb 18;7(1):13.","journal-title":"Nat Rev Dis Primers."},{"issue":"1","key":"1450_CR38","doi-asserted-by":"publisher","first-page":"67","DOI":"10.3233\/JND-221575","volume":"10","author":"CM McDonald","year":"2023","unstructured":"McDonald CM, Mayer OH, Hor KN, Miller D, Goemans N, Henricson EK, Marden JR, Freimark J, Lane H, Zhang A, Frean M, Trifillis P, Koladicz K, Signorovitch J (2023) PRO-DMD-01 consortium investigators. Functional and Clinical Outcomes Associated with Steroid Treatment among Non-ambulatory Patients with Duchenne Muscular Dystrophy1. J Neuromuscul Dis. 10(1):67\u201379","journal-title":"J Neuromuscul Dis."},{"issue":"7","key":"1450_CR39","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1038\/s41582-019-0203-3","volume":"15","author":"IEC Verhaart","year":"2019","unstructured":"Verhaart IEC, Aartsma-Rus A. Therapeutic developments for Duchenne muscular dystrophy. Nat Rev Neurol. 2019 Jul;15(7):373-386.","journal-title":"Nat Rev Neurol."},{"issue":"10","key":"1450_CR40","doi-asserted-by":"publisher","first-page":"2880","DOI":"10.1016\/j.ultrasmedbio.2021.06.008","volume":"47","author":"CW Lin","year":"2021","unstructured":"Lin CW, Tsui PH, Lu CH, Hung YH, Tsai MR, Shieh JY, Weng WC. Quantifying Lower Limb Muscle Stiffness as Ambulation Function Declines in Duchenne Muscular Dystrophy with Acoustic Radiation Force Impulse Shear Wave Elastography. Ultrasound Med Biol. 2021 Oct;47(10):2880-2889.","journal-title":"Ultrasound Med Biol."},{"issue":"12","key":"1450_CR41","doi-asserted-by":"publisher","first-page":"805","DOI":"10.1016\/j.nmd.2010.06.019","volume":"20","author":"CM Zaidman","year":"2010","unstructured":"Zaidman CM, Connolly AM, Malkus EC, Florence JM, Pestronk A. Quantitative ultrasound using backscatter analysis in Duchenne and Becker muscular dystrophy. Neuromuscul Disord. 2010 Dec;20(12):805-9.","journal-title":"Neuromuscul Disord."},{"issue":"2","key":"1450_CR42","doi-asserted-by":"publisher","first-page":"835","DOI":"10.1109\/JBHI.2023.3330578","volume":"28","author":"D Yan","year":"2024","unstructured":"Yan D, Li Q, Lin CW, Shieh JY, Weng WC, Tsui PH. Hybrid QUS Radiomics: A Multimodal-Integrated Quantitative Ultrasound Radiomics for Assessing Ambulatory Function in Duchenne Muscular Dystrophy. IEEE J Biomed Health Inform. 2024 Feb;28(2):835-845.","journal-title":"IEEE J Biomed Health Inform."},{"key":"1450_CR43","doi-asserted-by":"publisher","first-page":"175675","DOI":"10.1016\/j.ejphar.2023.175675","volume":"947","author":"G Patterson","year":"2023","unstructured":"Patterson G, Conner H, Groneman M, Blavo C, Parmar MS (2023) Duchenne muscular dystrophy: Current treatment and emerging exon skipping and gene therapy approach. Eur J Pharmacol. 947:175675","journal-title":"Eur J Pharmacol."},{"issue":"6","key":"1450_CR44","doi-asserted-by":"publisher","first-page":"963","DOI":"10.3390\/diagnostics11060963","volume":"11","author":"AH Liao","year":"2021","unstructured":"Liao AH, Chen JR, Liu SH, Lu CH, Lin CW, Shieh JY, Weng WC, Tsui PH. Deep Learning of Ultrasound Imaging for Evaluating Ambulatory Function of Individuals with Duchenne Muscular Dystrophy. Diagnostics (Basel). 2021 May 27;11(6):963.","journal-title":"Diagnostics (Basel)."},{"issue":"3","key":"1450_CR45","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1016\/j.ultrasmedbio.2008.09.016","volume":"35","author":"S Pillen","year":"2009","unstructured":"Pillen S, Tak RO, Zwarts MJ, Lammens MM, Verrijp KN, Arts IM, van der Laak JA, Hoogerbrugge PM, van Engelen BG, Verrips A. Skeletal muscle ultrasound: correlation between fibrous tissue and echo intensity. Ultrasound Med Biol. 2009 Mar;35(3):443-6.","journal-title":"Ultrasound Med Biol."},{"issue":"13","key":"1450_CR46","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1186\/1471-2407-13-302","volume":"21","author":"CY Lin","year":"2013","unstructured":"Lin CY, Cao LH, Wang JW, Zheng W, Chen Y, Feng ZZ, Li AH, Zhou JH. Ultrasonic spectrum analysis for in vivo characterization of tumor microstructural changes in the evaluation of tumor response to chemotherapy using diagnostic ultrasound. BMC Cancer. 2013 Jun 21;13:302.","journal-title":"BMC Cancer."},{"issue":"8","key":"1450_CR47","doi-asserted-by":"publisher","first-page":"607","DOI":"10.1002\/acn3.319","volume":"3","author":"C Godi","year":"2016","unstructured":"Godi C, Ambrosi A, Nicastro F, Previtali SC, Santarosa C, Napolitano S, Iadanza A, Scarlato M, Natali Sora MG, Tettamanti A, Gerevini S, Cicalese MP, Sitzia C, Venturini M, Falini A, Gatti R, Ciceri F, Cossu G, Torrente Y, Politi LS. Longitudinal MRI quantification of muscle degeneration in Duchenne muscular dystrophy. Ann Clin Transl Neurol. 2016 Jun 16;3(8):607-22.","journal-title":"Ann Clin Transl Neurol."},{"issue":"3","key":"1450_CR48","doi-asserted-by":"publisher","first-page":"1496","DOI":"10.1007\/s00330-018-5680-z","volume":"29","author":"W Li","year":"2019","unstructured":"Li W, Huang Y, Zhuang BW, Liu GJ, Hu HT, Li X, Liang JY, Wang Z, Huang XW, Zhang CQ, Ruan SM, Xie XY, Kuang M, Lu MD, Chen LD, Wang W (2019) Multiparametric ultrasomics of significant liver fibrosis: A machine learning-based analysis. Eur Radiol. 29(3):1496\u20131506","journal-title":"Eur Radiol."},{"issue":"5","key":"1450_CR49","doi-asserted-by":"publisher","first-page":"2175","DOI":"10.1007\/s00330-018-5915-z","volume":"29","author":"A Tang","year":"2019","unstructured":"Tang A, Destrempes F, Kazemirad S, Garcia-Duitama J, Nguyen BN, Cloutier G. Quantitative ultrasound and machine learning for assessment of steatohepatitis in a rat model. Eur Radiol. 2019 May;29(5):2175-2184.","journal-title":"Eur Radiol."},{"issue":"3","key":"1450_CR50","doi-asserted-by":"publisher","first-page":"865","DOI":"10.1148\/radiol.2016152703","volume":"281","author":"LE Collij","year":"2016","unstructured":"Collij LE, Heeman F, Kuijer JP, Ossenkoppele R, Benedictus MR, M\u00f6ller C, Verfaillie SC, Sanz-Arigita EJ, van Berckel BN, van der Flier WM, Scheltens P, Barkhof F, Wink AM. Application of Machine Learning to Arterial Spin Labeling in Mild Cognitive Impairment and Alzheimer Disease. Radiology. 2016 Dec;281(3):865-875.","journal-title":"Radiology."},{"key":"1450_CR51","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultsonch.2023.106661","volume":"101","author":"CW Lin","year":"2023","unstructured":"Lin CW, Shieh JY, Tsui PH, Chen CL, Lu CH, Hung YH, Lee HY, Weng WC, Gau SS. Acoustic radiation force impulse shear wave elastography quantifies upper limb muscle in patients with Duchenne muscular dystrophy. Ultrason Sonochem. 2023 Dec;101:106661.","journal-title":"Ultrason Sonochem."},{"issue":"12","key":"1450_CR52","doi-asserted-by":"publisher","first-page":"1808","DOI":"10.3390\/healthcare11121808","volume":"11","author":"P Mahajan","year":"2023","unstructured":"Mahajan P, Uddin S, Hajati F, Moni MA. Ensemble Learning for Disease Prediction: A Review. Healthcare (Basel). 2023;11(12):1808.","journal-title":"Healthcare (Basel)."},{"issue":"4","key":"1450_CR53","doi-asserted-by":"publisher","first-page":"1143","DOI":"10.1016\/j.ijrobp.2018.05.053","volume":"102","author":"A Traverso","year":"2018","unstructured":"Traverso A, Wee L, Dekker A, Gillies R. Repeatability and Reproducibility of Radiomic Features: A Systematic Review. Int J Radiat Oncol Biol Phys. 2018;102(4):1143-1158.","journal-title":"Int J Radiat Oncol Biol Phys."},{"issue":"9","key":"1450_CR54","doi-asserted-by":"publisher","first-page":"5843","DOI":"10.1007\/s00330-022-08662-1","volume":"32","author":"MD Li","year":"2022","unstructured":"Li MD, Cheng MQ, Chen LD, Hu HT, Zhang JC, Ruan SM, Huang H, Kuang M, Lu MD, Li W, Wang W (2022) Reproducibility of radiomics features from ultrasound images: influence of image acquisition and processing. Eur Radiol. 32(9):5843\u20135851","journal-title":"Eur Radiol."}],"container-title":["Journal of Imaging Informatics in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-025-01450-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10278-025-01450-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-025-01450-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T20:02:24Z","timestamp":1765569744000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10278-025-01450-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,14]]},"references-count":54,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["1450"],"URL":"https:\/\/doi.org\/10.1007\/s10278-025-01450-5","relation":{},"ISSN":["2948-2933"],"issn-type":[{"value":"2948-2933","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,3,14]]},"assertion":[{"value":"28 October 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 February 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 February 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 March 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This study was approved by the Institutional Review Board of National Taiwan University Hospital (approval code: 201503025RINC; approval date: 30 March 2015).","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics Approval"}},{"value":"Informed consent was obtained from all individual participants included in the study.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to Participate"}},{"value":"The authors affirm that human research participants provided informed consent for publication of the images in Fig.\u00a0\n                      \n                      .","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for Publication"}},{"value":"The authors declare no competing interests.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing Interests"}}]}}