{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T15:21:07Z","timestamp":1778167267147,"version":"3.51.4"},"reference-count":35,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2022,11,7]],"date-time":"2022-11-07T00:00:00Z","timestamp":1667779200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J of Clinical Ultrasound"],"published-print":{"date-parts":[[2023,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>In the recent years, artificial intelligence (AI) algorithms have been used to accurately diagnose musculoskeletal diseases. However, it is not known whether the particular regions of interest (ROI) delineation method would affect the performance of the AI algorithm.<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>The purpose of this study was to investigate the influence of ROI delineation methods on model performance and observer consistency.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>In this retrospective analysis, ultrasound (US) measures of median nerves affected with carpal tunnel syndrome (CTS) were compared to median nerves in a control group without CTS. Two methods were used for delineation of the ROI: (1) the ROI along the hyperechoic medial edge of the median nerve but not including the epineurium (MN) (ROI1); and (2) the ROI including the hyperechoic epineurium (ROI2), respectively. The intra group correlation coefficient (<jats:italic>ICC<\/jats:italic>) was used to compare the observer consistency of ROI features (i.e. the corresponding radiomics parameters). Parameters <jats:italic>\u03b1<\/jats:italic><jats:sub>1<\/jats:sub> and <jats:italic>\u03b1<\/jats:italic><jats:sub>2<\/jats:sub> were obtained based on the <jats:italic>ICC<\/jats:italic> of ROI<jats:sub>1<\/jats:sub> features and ROI<jats:sub>2<\/jats:sub> features. The ROC analysis was used to determine the area under the curve (AUC) and evaluate the performance of the radiologists and network. In addition, four indices, namely sensitivity, specificity, positive prediction and negative prediction were analyzed too.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>A total of 136 wrists of 77 CTS group and 136 wrists of 74 control group were included in the study. Control group was matched to CTS group according to the age and sex. The observer consistency of ROI features delineated by the two schemes was different, and the consistency of ROI<jats:sub>1<\/jats:sub> features was higher (<jats:italic>\u03b1<\/jats:italic>1\u00a0\u02c3\u00a0<jats:italic>\u03b1<\/jats:italic>2). The intra\u2010observer consistency was higher than the inter\u2010observer consistency regardless of the scheme, and the intra\u2010observer consistency was higher when chose scheme one. The performances of models based on the two ROI features were different, although the AUC of each model was greater than 0.8.The model performed better when the MN epineurium was included in the ROI. Among five artificial intelligence algorithms, the Forest models (model<jats:sub>1<\/jats:sub> achieved an AUC of 0.921 in training datasets and 0.830 in testing datasets; model<jats:sub>2<\/jats:sub> achieved an AUC of 0.967 in training datasets and 0.872 in testing datasets.) obtained the highest performance, followed by the support vector machine (SVM) models and the Logistic models. The performances of the models were significantly better than the inexperienced radiologist (Dr. B. Z. achieved an AUC of 0.702).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Different ROI delineation methods may affect the performance of the model and the consistency of observers. Model performance was better when the ROI contained the MN epineurium, and observer consistency was higher when the ROI was delineated along the hyperechoic medial border of the MN.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jcu.23387","type":"journal-article","created":{"date-parts":[[2022,11,7]],"date-time":"2022-11-07T10:49:17Z","timestamp":1667818157000},"page":"498-506","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Ultrasound\u2010based radiomics in the diagnosis of carpal tunnel syndrome: The influence of regions of interest delineation method on mode"],"prefix":"10.1002","volume":"51","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0126-7255","authenticated-orcid":false,"given":"Shuyi","family":"Lyu","sequence":"first","affiliation":[{"name":"Department of Interventional Therapy Hwa Mei Hospital, University of Chinese Academy of Sciences  Ningbo People's Republic of China"},{"name":"Ningbo Clinical Research Center for Medical Imaging  Ningbo China"},{"name":"Provinicial and Municipal Co\u2010construction Key Discipline for Medical Imaging  Ningbo China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Interventional Therapy Hwa Mei Hospital, University of Chinese Academy of Sciences  Ningbo People's Republic of China"},{"name":"Ningbo Clinical Research Center for Medical Imaging  Ningbo China"},{"name":"Provinicial and Municipal Co\u2010construction Key Discipline for Medical Imaging  Ningbo China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meiwu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Interventional Therapy Hwa Mei Hospital, University of Chinese Academy of Sciences  Ningbo People's Republic of China"},{"name":"Ningbo Clinical Research Center for Medical Imaging  Ningbo China"},{"name":"Provinicial and Municipal Co\u2010construction Key Discipline for Medical Imaging  Ningbo China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maoqing","family":"Jiang","sequence":"additional","affiliation":[{"name":"Ningbo Clinical Research Center for Medical Imaging  Ningbo China"},{"name":"Provinicial and Municipal Co\u2010construction Key Discipline for Medical Imaging  Ningbo China"},{"name":"Department of PET\u2010CT and Nuclear Medicine Hwa Mei Hospital, University of Chinese Academy of Sciences  Ningbo People's Republic of China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianjun","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Neuroelectrophysiology Hwa Mei Hospital, University of Chinese Academy of Sciences  Ningbo People's Republic of China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiazhen","family":"Zhu","sequence":"additional","affiliation":[{"name":"Ningbo Clinical Research Center for Medical Imaging  Ningbo China"},{"name":"Provinicial and Municipal Co\u2010construction Key Discipline for Medical Imaging  Ningbo China"},{"name":"Multi\u2010disciplinary diagnosis and treatment department Hwa Mei Hospital, University of Chinese Academy of Sciences  Ningbo People's Republic of China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baisong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Interventional Therapy Hwa Mei Hospital, University of Chinese Academy of Sciences  Ningbo People's Republic of China"},{"name":"Ningbo Clinical Research Center for Medical Imaging  Ningbo China"},{"name":"Provinicial and Municipal Co\u2010construction Key Discipline for Medical Imaging  Ningbo China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2022,11,7]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1474-4422(16)30231-9"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cnp.2017.07.004"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s13760-018-0963-3"},{"key":"e_1_2_9_5_1","first-page":"463","article-title":"Electrosonodiagnosis in carpal tunnel syndrome: a proposed diagnostic algorithm based on an analytic literature review","volume":"8","author":"Goldberg GJMZ","year":"2016","journal-title":"Phys. Med. Rehabil."},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultrasmedbio.2017.08.1886"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhsa.2015.07.010"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejca.2011.11.036"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2015151169"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrclinonc.2017.141"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2020.109518"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2020.02.020"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1080\/0284186X.2018.1445283"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.1038\/ncpneuro0216"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.58.11.1589"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11910-012-0328-x"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultrasmedbio.2011.06.011"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1002\/mus.22019"},{"key":"e_1_2_9_19_1","doi-asserted-by":"publisher","DOI":"10.1080\/15548627.2020.1797280"},{"key":"e_1_2_9_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jht.2021.04.014"},{"key":"e_1_2_9_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11999-010-1637-5"},{"key":"e_1_2_9_22_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.25661"},{"key":"e_1_2_9_23_1","article-title":"Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA\/TCIA data set. NPJ","volume":"2","author":"Li H","year":"2016","journal-title":"Breast Cancer"},{"key":"e_1_2_9_24_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12967-019-1911-6"},{"key":"e_1_2_9_25_1","doi-asserted-by":"publisher","DOI":"10.1002\/jum.15201"},{"key":"e_1_2_9_26_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-021-97043-7"},{"key":"e_1_2_9_27_1","doi-asserted-by":"publisher","DOI":"10.4329\/wjr.v8.i8.726"},{"key":"e_1_2_9_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultrasmedbio.2010.07.009"},{"issue":"11","key":"e_1_2_9_29_1","first-page":"1654","article-title":"Evaluation of several classification methods in carpal tunnel syndrome","volume":"67","author":"Sayin R","year":"2017","journal-title":"J. Pak. Med. Assoc."},{"key":"e_1_2_9_30_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2012.09.065"},{"key":"e_1_2_9_31_1","doi-asserted-by":"publisher","DOI":"10.1002\/sam.11498"},{"key":"e_1_2_9_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2979466"},{"issue":"19","key":"e_1_2_9_33_1","article-title":"Logistisk regresjon \u2013 anvendt og anvendelig [Logistic regression \u2013 applied and applicable","volume":"137","author":"Thoresen M","year":"2017","journal-title":"Tidsskr nor Laegeforen"},{"key":"e_1_2_9_34_1","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/61\/13\/R150"},{"key":"e_1_2_9_35_1","doi-asserted-by":"publisher","DOI":"10.2174\/1573405616999200918150259"},{"key":"e_1_2_9_36_1","doi-asserted-by":"publisher","DOI":"10.3390\/info11060332"}],"container-title":["Journal of Clinical Ultrasound"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/jcu.23387","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/jcu.23387","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/jcu.23387","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,8]],"date-time":"2023-12-08T13:55:41Z","timestamp":1702043741000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/jcu.23387"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,7]]},"references-count":35,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2023,3]]}},"alternative-id":["10.1002\/jcu.23387"],"URL":"https:\/\/doi.org\/10.1002\/jcu.23387","archive":["Portico"],"relation":{},"ISSN":["0091-2751","1097-0096"],"issn-type":[{"value":"0091-2751","type":"print"},{"value":"1097-0096","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,11,7]]},"assertion":[{"value":"2022-09-20","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-10-07","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-11-07","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}