{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T04:45:09Z","timestamp":1782708309566,"version":"3.54.5"},"reference-count":16,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,6,28]],"date-time":"2026-06-28T00:00:00Z","timestamp":1782604800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,6,28]],"date-time":"2026-06-28T00:00:00Z","timestamp":1782604800000},"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"],"abstract":"ABSTRACT<\/jats:title>\n \n Purpose<\/jats:title>\n \n To develop and internally validate a super\u2010resolution ultrasound microvascular imaging (\n SR<\/jats:styled-content>\n \u2010\n UMI<\/jats:styled-content>\n ) model for noninvasive preoperative prediction of sentinel lymph node (\n SLN<\/jats:styled-content>\n ) involvement in breast cancer and to assess incremental value over clinical variables.\n <\/jats:p>\n <\/jats:sec>\n \n Materials and Methods<\/jats:title>\n \n In this prospective single\u2010center study (January\u2013June 2025), 162 consecutive patients with pathologically confirmed breast cancer underwent contrast\u2010enhanced\n SR<\/jats:styled-content>\n \u2010\n UMI<\/jats:styled-content>\n of the primary tumor prior to axillary surgery and\n SLNB<\/jats:styled-content>\n .\n SonoVue<\/jats:styled-content>\n (2.4\u2009\n mL<\/jats:styled-content>\n ) was administered as an antecubital venous bolus. Examinations were performed on an Ultimus\n 9E<\/jats:styled-content>\n ultrasound system using a 5\u201315\u2009\n MHz<\/jats:styled-content>\n linear transducer at low\n MI<\/jats:styled-content>\n (0.08). Three predictor sets were evaluated: clinical\u2010only (9 variables),\n SR<\/jats:styled-content>\n \u2010\n UMI<\/jats:styled-content>\n \u2010only (98 features), and combined (107 predictors). Elastic net\u2013regularized logistic regression (\n EN<\/jats:styled-content>\n \u2010\n LR<\/jats:styled-content>\n ) was prespecified as the primary model and evaluated using nested stratified cross\u2010validation (outer 5\u2010fold, inner 3\u2010fold) with pooled out\u2010of\u2010fold (\n OOF<\/jats:styled-content>\n ) predictions, assessing discrimination, calibration, and decision\u2010curve analysis (\n DCA<\/jats:styled-content>\n ).\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n SLN<\/jats:styled-content>\n involvement was present in 55\/162 patients (34.0%).\n EN<\/jats:styled-content>\n \u2010\n LR<\/jats:styled-content>\n achieved\n AUC<\/jats:styled-content>\n 0.662,\n PR<\/jats:styled-content>\n \u2010\n AUC<\/jats:styled-content>\n 0.471, and Brier 0.232 for clinical\u2010only predictors;\n SR<\/jats:styled-content>\n \u2010\n UMI<\/jats:styled-content>\n \u2010only improved performance (\n AUC<\/jats:styled-content>\n 0.800;\n PR<\/jats:styled-content>\n \u2010\n AUC<\/jats:styled-content>\n 0.572; Brier 0.185). The combined model performed similarly (\n AUC<\/jats:styled-content>\n 0.802;\n PR<\/jats:styled-content>\n \u2010\n AUC<\/jats:styled-content>\n 0.574; Brier 0.185). At the Youden operating point (threshold 0.514), the combined model yielded sensitivity 0.782, specificity 0.766,\n PPV<\/jats:styled-content>\n 0.632, and\n NPV<\/jats:styled-content>\n 0.872. Bootstrap\n OOF<\/jats:styled-content>\n comparisons showed significant\n AUC<\/jats:styled-content>\n improvements for\n SR<\/jats:styled-content>\n \u2010\n UMI<\/jats:styled-content>\n \u2010only versus clinical\u2010only and combined vs. clinical\u2010only, whereas combined vs.\n SR<\/jats:styled-content>\n \u2010\n UMI<\/jats:styled-content>\n \u2010only was not significant. Calibration showed a negative intercept and slope >\u20091 (combined: \u22120.637, 1.270).\n DCA<\/jats:styled-content>\n demonstrated higher net benefit for\n EN<\/jats:styled-content>\n \u2010\n LR<\/jats:styled-content>\n than treat\u2010all\/treat\u2010none across threshold probabilities 0.05\u20130.60.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n \n SR<\/jats:styled-content>\n \u2010\n UMI<\/jats:styled-content>\n microvascular features enabled good internal\u2010validation performance and significantly improved discrimination over clinical\/biopsy variables. The combined model offered no meaningful gain over\n SR<\/jats:styled-content>\n \u2010\n UMI<\/jats:styled-content>\n only. External validation with recalibration is warranted.\n <\/jats:p>\n <\/jats:sec>","DOI":"10.1002\/jcu.70313","type":"journal-article","created":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T04:10:26Z","timestamp":1782706226000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Noninvasive Preoperative Assessment of Sentinel Lymph Node Metastasis in Breast Cancer Using Super\u2010Resolution Ultrasound Microvascular Imaging"],"prefix":"10.1002","author":[{"given":"Ruifang","family":"Guo","sequence":"first","affiliation":[{"name":"Department of Ultrasound Beijing Friendship Hospital, Capital Medical University Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xi","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Ultrasound Beijing Friendship Hospital, Capital Medical University Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junfeng","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Ultrasound Beijing Friendship Hospital, Capital Medical University Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangdong","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Ultrasound Beijing Friendship Hospital, Capital Medical University Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7116-0608","authenticated-orcid":false,"given":"Linxue","family":"Qian","sequence":"additional","affiliation":[{"name":"Department of Ultrasound Beijing Friendship Hospital, Capital Medical University Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,6,28]]},"reference":[{"key":"e_1_2_11_2_1","first-page":"q902","article-title":"TRIPOD+AI Statement: Updated Guidance for Reporting Clinical Prediction Models That Use Regression or Machine Learning Methods","volume":"385","year":"2024","journal-title":"BMJ"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1097\/RUQ.0000000000000671"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCULATIONAHA.114.014508"},{"issue":"1","key":"e_1_2_11_5_1","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1186\/s13058-023-01670-z","article-title":"Noninvasive Prediction of Axillary Lymph Node Breast Cancer Metastasis Using Morphometric Analysis of Nodal Tumor Microvessels in a Contrast\u2010Free Ultrasound Approach","volume":"25","author":"Ferroni G.","year":"2023","journal-title":"Breast Cancer Research"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultrasmedbio.2019.12.008"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2017.11470"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2011.90"},{"key":"e_1_2_11_9_1","doi-asserted-by":"crossref","first-page":"1043185","DOI":"10.3389\/fonc.2022.1043185","article-title":"Diagnostic Value of Multiple Ultrasound Diagnostic Techniques for Axillary Lymph Node Metastases in Breast Cancer: A Systematic Analysis and Network Meta\u2010Analysis","volume":"12","author":"Li J.","year":"2022","journal-title":"Frontiers in Oncology"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2016.71.0947"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.anndiagpath.2025.152571"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJM199101033240101"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.7326\/M18-1376"},{"issue":"2","key":"e_1_2_11_14_1","doi-asserted-by":"crossref","first-page":"100054","DOI":"10.1016\/j.wfumbo.2024.100054","article-title":"Contrast\u2010Enhanced Ultrasound (CEUS) for the Diagnosis of Axillary Lymph Nodes in Breast Cancer: A Systematic Review and Meta\u2010Analysis","volume":"2","author":"XL C. L.","year":"2024","journal-title":"WFUMB Ultrasound Open"},{"key":"e_1_2_11_15_1","doi-asserted-by":"crossref","first-page":"1049991","DOI":"10.3389\/fonc.2022.1049991","article-title":"Ultrasound Super\u2010Resolution Imaging for Differential Diagnosis of Breast Masses","volume":"12","author":"Zhang G.","year":"2022","journal-title":"Frontiers in Oncology"},{"key":"e_1_2_11_16_1","doi-asserted-by":"crossref","first-page":"861151","DOI":"10.3389\/fonc.2022.861151","article-title":"Association Between Vascular Index Measured via Superb Microvascular Imaging and Molecular Subtype of Breast Cancer","volume":"12","author":"Zhang X. 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