{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T16:18:20Z","timestamp":1767975500920,"version":"3.49.0"},"reference-count":36,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2025,4,3]],"date-time":"2025-04-03T00:00:00Z","timestamp":1743638400000},"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 Ultrasound Medicine"],"published-print":{"date-parts":[[2025,8]]},"abstract":"<jats:sec><jats:title>Objectives<\/jats:title><jats:p>Testicular tumors are the most common solid malignancy among males aged 15\u201335. This study aimed to establish an ultrasound (US) based clinical\u2010radiomic nomogram for the preoperative prediction of testicular tumors histologic subtypes, differentiating testicular germ cell tumors (TGCTs) from testicular non\u2010germ cell tumors (TNGCTs) and then differentiating seminomas (SGCTs) from non\u2010seminomatous tumors (NSGCTs).<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>This retrospective study included 148 patients with testicular tumors confirmed by pathology, with 120 cases of TGCTs, including 65 SGCTs and 55 NSGCTs. All patients underwent preoperative ultrasound examinations, and data on clinical information, US features, and radiomics features were collected. The Radscore model was constructed after feature selection. Independent risk factors were identified using univariate and multivariate logistic regression analysis. The nomogram model was assessed using the receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA).<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The TGCTs radiomics nomogram model achieved AUCs of 0.89 in both the training and validation datasets. The SGCTs radiomics nomogram model achieved AUCs of 0.93 in the training dataset and 0.91 in the validation dataset, surpassing the predictive performance of both Radscore and clinical models. The calibration curves showed that the nomogram estimation was consistent with the actual observations. DCA also verified the clinical value of the combined model.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>The ultrasound\u2010based clinical\u2010radiomics nomogram has the potential to non\u2010invasively discriminate the histologic subtypes of testicular tumors.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jum.16701","type":"journal-article","created":{"date-parts":[[2025,4,4]],"date-time":"2025-04-04T20:30:24Z","timestamp":1743798624000},"page":"1457-1471","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Development of an Ultrasound\u2010Based Clinical\u2010Radiomic Nomogram for Predicting Histologic Subtypes in Focal Testicular Tumors"],"prefix":"10.1002","volume":"44","author":[{"given":"Tuo","family":"Lin","sequence":"first","affiliation":[{"name":"Department of Ultrasound imaging The First Affiliated Hospital of Wenzhou Medical University  Wenzhou 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