{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T17:01:15Z","timestamp":1789750875500,"version":"4.0.1"},"reference-count":31,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T00:00:00Z","timestamp":1786406400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T00:00:00Z","timestamp":1786406400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82371978"],"award-info":[{"award-number":["82371978"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82071945"],"award-info":[{"award-number":["82071945"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J of Ultrasound Medicine"],"abstract":"<jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>This study aimed to develop and validate an ultrasound\u2010based IHC4\u2010associated radiomic model for predicting late recurrence in ER\u2010positive breast cancer and to evaluate its potential to support risk stratification and guide decisions on extended endocrine therapy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In this retrospective multicenter study, patients were divided into a training cohort, an internal validation cohort, and two external validation cohorts. Radiomic features associated with the immunohistochemical four\u2010marker (IHC4) score were selected to construct a support vector machine (SVM)\u2010based IHC4\u2010associated radiomic model for generating an IHC4\u2010associated radiomic score. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). Late distant recurrence (DR) was defined as the primary endpoint, and progression\u2010free survival (PFS) was defined as the secondary endpoint. The prognostic value of the score was further evaluated using Cox regression analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 523 patients were included in this study. Seven IHC4\u2010associated radiomic features were selected to construct the IHC4\u2010associated radiomic model. The model demonstrated consistent performance across cohorts, with AUCs of 0.81, 0.84, 0.79, and 0.81 in the training, internal validation, and two external validation cohorts, respectively. The IHC4\u2010associated radiomic score stratified late DR risk across the training, internal validation, and external validation cohorts. In the secondary exploratory PFS analysis, the score remained associated with PFS in multivariable Cox analysis (HR\u2009=\u20094.246, 95% CI: 1.749\u201310.307,\n                      <jats:italic>P<\/jats:italic>\n                      \u2009=\u2009.001).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The IHC4\u2010associated radiomic model may serve as a noninvasive biomarker for predicting prognosis in ER\u2010positive breast cancer.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jum.70410","type":"journal-article","created":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T06:05:02Z","timestamp":1786514702000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Ultrasound\u2010Based\n                    <scp>IHC4<\/scp>\n                    \u2010Associated Radiomic Model for Predicting Late Recurrence in\n                    <scp>ER<\/scp>\n                    \u2010Positive Breast Cancer"],"prefix":"10.1002","author":[{"given":"MengYao","family":"Quan","sequence":"first","affiliation":[{"name":"Department of Ultrasound Fudan University Shanghai Cancer Center  Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"ChangYan","family":"Wang","sequence":"additional","affiliation":[{"name":"Laboratory of the Smart Medicine and AI\u2010Based Radiology Technology (SMART), School of Communication and Information Engineering Shanghai University  Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-1217-3990","authenticated-orcid":false,"given":"Hong","family":"Yuan","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, West China Hospital Sichuan University  Chengdu 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