{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T16:54:28Z","timestamp":1793120068393,"version":"4.5.0"},"reference-count":33,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T00:00:00Z","timestamp":1763078400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T00:00:00Z","timestamp":1763078400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J of Clinical Ultrasound"],"published-print":{"date-parts":[[2026,5]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aims to develop and validate a deep learning radiomics (DLR) model based on ultrasound images for non\u2010invasively distinguishing the myometrial infiltration (MI) of patients with endometrial cancer (EC).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We retrospectively collected 310 patients with EC who underwent surgical resection from center 1 from September 2017 to January 2025, forming a training group and a validation group. An external testing group was comprised of 80 patients from center 2. We extracted deep learning (DL) features and radiomics features from ultrasound images, establishing a DLR model after dimensionality reduction. The receiver operating characteristic analysis was used to evaluate the practicality of the proposed model. The utility of the proposed model was evaluated using receiver operating characteristic, calibration, and decision curve analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 390 EC patients were included in the study. In the validation set, the AUC of the radiomics model was 0.874 (0.774\u20130.949), and in the testing group, the AUC of the DL model was 0.844 (0.699\u20130.957). The DLR model was superior to radiomics models and DL models in interpreting images, and also outperformed the diagnostic performance of advanced ultrasound physicians.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The DLR model based on ultrasound images can accurately and non\u2010invasively distinguish the MI depth of EC patients, assisting doctors in formulating more favorable treatment plans for patients.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jcu.70134","type":"journal-article","created":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T12:56:02Z","timestamp":1763124962000},"page":"836-844","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Deep Learning Radiomics Model Based on Ultrasound Images Predicts Myometrial Infiltration of Endometrial Cancer"],"prefix":"10.1002","volume":"54","author":[{"given":"Guo","family":"Yuanyuan","sequence":"first","affiliation":[{"name":"Department of Ultrasound Affiliated Hospital of North Sichuan Medical College  Nanchong Sichuan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8293-7689","authenticated-orcid":false,"given":"Chen","family":"Jiao","sequence":"additional","affiliation":[{"name":"Department of Ultrasound Affiliated Hospital of North Sichuan Medical College  Nanchong Sichuan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luo","family":"Yuqun","sequence":"additional","affiliation":[{"name":"Department of Ultrasound Affiliated Hospital of North Sichuan Medical College  Nanchong Sichuan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huang","family":"Jianghua","sequence":"additional","affiliation":[{"name":"Department of Ultrasound Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College (University)  Nanchong Sichuan China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,11,14]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/ijgo.15193"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/uog.14905"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1148\/rg.240084"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2014.11.010"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.23736\/S0026-4806.20.07125-6"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00261-024-04766-y"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(22)00323-3"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eclinm.2022.101348"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1136\/ijgc-2023-005217"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eclinm.2025.103098"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bpobgyn.2014.04.007"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1002\/uog.18909"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1155\/2017\/1318203"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ygyno.2018.06.027"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.radonc.2025.110770"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2022.881850"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1046\/j.1469-0705.1992.02010035.x"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijgc.2024.100017"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41523-024-00628-4"},{"key":"e_1_2_10_21_1","first-page":"1","article-title":"A Unified Approach to Interpreting Model Predictions","volume":"30","author":"Lundberg S. M.","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.3390\/cancers16050907"},{"key":"e_1_2_10_23_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12880-025-01579-3"},{"key":"e_1_2_10_24_1","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.118.222893"},{"key":"e_1_2_10_25_1","doi-asserted-by":"publisher","DOI":"10.21037\/qims-23-1621"},{"key":"e_1_2_10_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2021.109717"},{"key":"e_1_2_10_27_1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21654"},{"issue":"7","key":"e_1_2_10_28_1","first-page":"6445","article-title":"Risk Assessment of Extra\u2010Uterine Involvement and Prognosis in Young Type I Endometrial Carcinoma With High or Moderate Differentiation and Less Than 1\/2 Myometrial Invasion","volume":"16","author":"Sun Y.","year":"2024","journal-title":"Aging"},{"key":"e_1_2_10_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijgc.2024.100041"},{"key":"e_1_2_10_30_1","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2024.1474427"},{"key":"e_1_2_10_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00586-025-08696-1"},{"key":"e_1_2_10_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.clinimag.2021.03.024"},{"key":"e_1_2_10_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultrasmedbio.2022.03.007"},{"key":"e_1_2_10_34_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12916-022-02469-z"}],"container-title":["Journal of Clinical Ultrasound"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/jcu.70134","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/jcu.70134","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/jcu.70134","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T08:24:45Z","timestamp":1783931085000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/jcu.70134"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,14]]},"references-count":33,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2026,5]]}},"alternative-id":["10.1002\/jcu.70134"],"URL":"https:\/\/doi.org\/10.1002\/jcu.70134","archive":["Portico"],"relation":{},"ISSN":["0091-2751","1097-0096"],"issn-type":[{"value":"0091-2751","type":"print"},{"value":"1097-0096","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,14]]},"assertion":[{"value":"2025-05-27","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-10-28","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-11-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}