{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,4]],"date-time":"2026-11-04T01:03:01Z","timestamp":1793754181327,"version":"4.6.1"},"reference-count":30,"publisher":"Elsevier BV","issue":"7","license":[{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"funder":[{"DOI":"10.13039\/501100019413","name":"Yunnan Provincial Department of Education Science Research Fund Project","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100019413","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["academicradiology.org","clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Academic Radiology"],"published-print":{"date-parts":[[2025,7]]},"DOI":"10.1016\/j.acra.2025.01.026","type":"journal-article","created":{"date-parts":[[2025,2,3]],"date-time":"2025-02-03T07:19:46Z","timestamp":1738567186000},"page":"4061-4081","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":6,"title":["Radiomics Analysis of Different Machine Learning Models based on Multiparametric MRI to Identify Benign and Malignant Testicular Lesions"],"prefix":"10.1016","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3802-9752","authenticated-orcid":false,"given":"Yuanxi","family":"Jian","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suping","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Tan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qian","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junlin","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuan","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.acra.2025.01.026_bib1","first-page":"7","article-title":"Cancer statistics","volume":"70","author":"Siegel","year":"2020","journal-title":"2020. CA-A Cancer J Clin"},{"issue":"3","key":"10.1016\/j.acra.2025.01.026_bib2","doi-asserted-by":"crossref","first-page":"820","DOI":"10.1002\/ijc.32810","article-title":"Testicular cancer incidence predictions in Europe 2010-2035: a rising burden despite population ageing","volume":"147","author":"Znaor","year":"2020","journal-title":"Int J Cancer"},{"issue":"5","key":"10.1016\/j.acra.2025.01.026_bib3","doi-asserted-by":"crossref","first-page":"566","DOI":"10.1016\/j.euo.2022.06.009","article-title":"Worldwide distribution, risk factors, and temporal trends of testicular cancer incidence and mortality: a global analysis","volume":"5","author":"Huang","year":"2022","journal-title":"Eur Urol Oncol"},{"issue":"3","key":"10.1016\/j.acra.2025.01.026_bib4","first-page":"233","article-title":"Colorectal cancer statistics","volume":"73","author":"Siegel","year":"2023","journal-title":"2023. CA-A CANCER JOURNAL FOR CLINICIANS"},{"issue":"4","key":"10.1016\/j.acra.2025.01.026_bib5","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1016\/j.ejca.2013.11.035","article-title":"Testicular cancer incidence to rise by 25% by 2025 in Europe? model-based predictions in 40 countries using population-based registry data","volume":"50","author":"Le Cornet","year":"2014","journal-title":"Eur J Cancer"},{"issue":"12","key":"10.1016\/j.acra.2025.01.026_bib6","doi-asserted-by":"crossref","first-page":"1529","DOI":"10.6004\/jnccn.2019.0058","article-title":"Testicular Cancer, Version 2.2020, NCCN Clinical Practice Guidelines in Oncology","volume":"17","author":"Gilligan","year":"2019","journal-title":"Journal of the National Comprehensive Cancer Network"},{"issue":"2","key":"10.1016\/j.acra.2025.01.026_bib7","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1097\/JU.0000000000000318","article-title":"Diagnosis and Treatment of Early Stage Testicular Cancer: AUA Guideline","volume":"202","author":"Stephenson","year":"2019","journal-title":"JOURNAL OF UROLOGY"},{"issue":"4","key":"10.1016\/j.acra.2025.01.026_bib8","doi-asserted-by":"crossref","first-page":"760","DOI":"10.1097\/JU.0000000000000579","article-title":"Testis Sparing Surgery of Small Testicular Masses: Retrospective Analysis of a Multicenter Cohort","volume":"203","author":"Gentile","year":"2020","journal-title":"JOURNAL OF UROLOGY"},{"issue":"1","key":"10.1016\/j.acra.2025.01.026_bib9","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1007\/s00330-017-4944-3","article-title":"MRI of the scrotum: Recommendations of the ESUR Scrotal and Penile Imaging Working Group","volume":"28","author":"Tsili","year":"2018","journal-title":"EUROPEAN RADIOLOGY"},{"issue":"12","key":"10.1016\/j.acra.2025.01.026_bib10","doi-asserted-by":"crossref","first-page":"1529","DOI":"10.6004\/jnccn.2019.0058","article-title":"Testicular Cancer, Version 2.2020, NCCN Clinical Practice Guidelines in Oncology","volume":"17","author":"Gilligan","year":"2019","journal-title":"Journal of the National Comprehensive Cancer Network"},{"key":"10.1016\/j.acra.2025.01.026_bib11","article-title":"Advances in diagnosis and treatment of testicular cancer","volume":"379","author":"Chovanec","year":"2022","journal-title":"BMJ (Clinical research ed. )."},{"issue":"6","key":"10.1016\/j.acra.2025.01.026_bib12","doi-asserted-by":"crossref","first-page":"885","DOI":"10.1016\/j.eururo.2005.06.019","article-title":"Guidelines on testicular cancer","volume":"48","author":"Albers","year":"2005","journal-title":"EUROPEAN UROLOGY"},{"issue":"4","key":"10.1016\/j.acra.2025.01.026_bib13","doi-asserted-by":"crossref","first-page":"655","DOI":"10.1590\/S1677-5538.IBJU.2013.0077","article-title":"The value of testicular ultrasound in the prediction of the type and size of testicular tumors","volume":"41","author":"Shtricker","year":"2015","journal-title":"International Braz J Urol"},{"issue":"4","key":"10.1016\/j.acra.2025.01.026_bib14","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1038\/aja.2011.172","article-title":"Diffusion-weighted MR imaging of normal and abnormal scrotum: preliminary results","volume":"14","author":"Tsili","year":"2012","journal-title":"ASIAN JOURNAL OF ANDROLOGY"},{"issue":"2","key":"10.1016\/j.acra.2025.01.026_bib15","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1007\/s13244-017-0592-z","article-title":"Imaging of the scrotum: beyond sonography","volume":"9","author":"Parenti","year":"2018","journal-title":"Insights into imaging"},{"issue":"2","key":"10.1016\/j.acra.2025.01.026_bib16","first-page":"563","article-title":"Radiomics: Images Are More than Pictures","volume":"278","author":"Gillies","year":"2016","journal-title":"They Are Data. RADIOLOGY"},{"issue":"3","key":"10.1016\/j.acra.2025.01.026_bib17","first-page":"2105","article-title":"Can quantitative peritumoral CT radiomics features predict the prognosis of patients with non-small cell lung cancer? A systematic review","volume":"33","author":"Linyu","year":"2023","journal-title":"EUROPEAN RADIOLOGY"},{"issue":"5","key":"10.1016\/j.acra.2025.01.026_bib18","first-page":"2117","article-title":"Multiphase MRI-Based Radiomics for Predicting Histological Grade of Hepatocellular Carcinoma","volume":"60","author":"Yang","year":"2024","journal-title":"JOURNAL OF MAGNETIC RESONANCE IMAGING"},{"issue":"1","key":"10.1016\/j.acra.2025.01.026_bib19","article-title":"MRI radiomics model differentiates small hepatic metastases and abscesses in periampullary cancer patients","volume":"14","author":"Park","year":"2024","journal-title":"Scientific reports"},{"issue":"2","key":"10.1016\/j.acra.2025.01.026_bib20","doi-asserted-by":"crossref","first-page":"1254","DOI":"10.1007\/s00330-019-06384-5","article-title":"Radiomics of small renal masses on multiphasic CT: accuracy of machine learning-based classification models for the differentiation of renal cell carcinoma and angiomyolipoma without visible fat","volume":"30","author":"Yang","year":"2020","journal-title":"EUROPEAN RADIOLOGY"},{"issue":"4","key":"10.1016\/j.acra.2025.01.026_bib21","doi-asserted-by":"crossref","first-page":"2340","DOI":"10.1007\/s00330-021-08322-w","article-title":"Fuhrman nuclear grade prediction of clear cell renal cell carcinoma: influence of volume of interest delineation strategies on machine learning-based dynamic enhanced CT radiomics analysis","volume":"32","author":"Luo","year":"2022","journal-title":"EUROPEAN RADIOLOGY"},{"key":"10.1016\/j.acra.2025.01.026_bib22","doi-asserted-by":"crossref","DOI":"10.3389\/fmed.2023.1279622","article-title":"Comparison and analysis of multiple machine learning models for discriminating benign and malignant testicular lesions based on magnetic resonance imaging radiomics","volume":"10","author":"Feng","year":"2023","journal-title":"Frontiers in medicine"},{"issue":"4","key":"10.1016\/j.acra.2025.01.026_bib23","doi-asserted-by":"crossref","first-page":"403","DOI":"10.3348\/kjr.2014.15.4.403","article-title":"Readout-Segmented Echo-Planar Imaging in Diffusion-Weighted MR Imaging in Breast Cancer: Comparison with Single-Shot Echo-Planar Imaging in Image Quality[J]","volume":"15","author":"Ju","year":"2014","journal-title":"Korean Journal of Radiology"},{"issue":"4","key":"10.1016\/j.acra.2025.01.026_bib24","doi-asserted-by":"crossref","first-page":"607","DOI":"10.3171\/2019.4.SPINE19178","article-title":"Reduced field of view echo-planar imaging diffusion tensor MRI for pediatric spinal tumors","volume":"31","author":"Kim","year":"2019","journal-title":"JOURNAL OF NEUROSURGERY-SPINE"},{"issue":"8","key":"10.1016\/j.acra.2025.01.026_bib25","doi-asserted-by":"crossref","first-page":"3976","DOI":"10.1007\/s00330-018-5975-0","article-title":"Pilot study of rapid MR pancreas screening for patients with BRCA mutation","volume":"29","author":"Corrias","year":"2019","journal-title":"EUROPEAN RADIOLOGY"},{"issue":"16","key":"10.1016\/j.acra.2025.01.026_bib26","doi-asserted-by":"crossref","DOI":"10.3390\/cancers14163912","article-title":"An Overview of the Role of Multiparametric MRI in the Investigation of Testicular Tumors","volume":"14","author":"Tsili","year":"2022","journal-title":"Cancers"},{"issue":"48","key":"10.1016\/j.acra.2025.01.026_bib27","doi-asserted-by":"crossref","DOI":"10.1097\/MD.0000000000027799","article-title":"Testicular tumors: discriminative value of conventional MRI and diffusion weighted imaging","volume":"100","author":"Wang","year":"2021","journal-title":"MEDICINE"},{"issue":"8","key":"10.1016\/j.acra.2025.01.026_bib28","doi-asserted-by":"crossref","first-page":"2525","DOI":"10.1007\/s00261-023-03870-9","article-title":"Machine learning based on gadoxetic acid-enhanced MRI for differentiating atypical intrahepatic mass-forming cholangiocarcinoma from poorly differentiated hepatocellular carcinoma","volume":"48","author":"Chen","year":"2023","journal-title":"Abdominal Radiology"},{"key":"10.1016\/j.acra.2025.01.026_bib29","article-title":"Predictive Study of Machine Learning-Based Multiparametric MRI Radiomics Nomogram for Perineural Invasion in Rectal Cancer: A Pilot Study","author":"Wang","year":"2024","journal-title":"null"},{"issue":"3","key":"10.1016\/j.acra.2025.01.026_bib30","doi-asserted-by":"crossref","DOI":"10.3390\/ijerph20032380","article-title":"Machine Learning Approaches for the Prediction of Hepatitis B and C Seropositivity","volume":"20","author":"Harabor","year":"2023","journal-title":"International journal of environmental research and public health"}],"container-title":["Academic Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1076633225000674?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1076633225000674?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T08:40:26Z","timestamp":1763541626000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1076633225000674"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7]]},"references-count":30,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2025,7]]}},"alternative-id":["S1076633225000674"],"URL":"https:\/\/doi.org\/10.1016\/j.acra.2025.01.026","relation":{},"ISSN":["1076-6332"],"issn-type":[{"value":"1076-6332","type":"print"}],"subject":[],"published":{"date-parts":[[2025,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Radiomics Analysis of Different Machine Learning Models based on Multiparametric MRI to Identify Benign and Malignant Testicular Lesions","name":"articletitle","label":"Article Title"},{"value":"Academic Radiology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.acra.2025.01.026","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Association of Academic Radiology. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}]}}