{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T11:54:07Z","timestamp":1791028447216,"version":"4.1.0"},"reference-count":29,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T00:00:00Z","timestamp":1775520000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Science and Technology Research and Development Program of Qinhuangdao City","award":["202301A199"],"award-info":[{"award-number":["202301A199"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Ultrason Imaging"],"published-print":{"date-parts":[[2026,11]]},"abstract":"<jats:p>\n                    To develop a logistic prediction model based on multimodal ultrasound to enhance the diagnostic performance for non-microcalcified BI-RADS 4 breast lesions. We retrospectively analyzed ultrasound data from 334 patients with BI-RADS 4 breast lesions, incorporating 10 multimodal features. Model 1 was constructed using the entire cohort, while Model 2 focused on a subset of 225 non-microcalcified cases, with features selected via Lasso regularization and performance evaluated through 10-fold cross-validation. Model 1 identified lesion size\u2009&gt;2\u2009cm (\n                    <jats:italic toggle=\"yes\">OR<\/jats:italic>\n                    \u2009=\u20091.65,\n                    <jats:italic toggle=\"yes\">p<\/jats:italic>\n                    \u2009=\u2009.041), microcalcification (\n                    <jats:italic toggle=\"yes\">OR<\/jats:italic>\n                    \u2009=\u20093.62,\n                    <jats:italic toggle=\"yes\">p<\/jats:italic>\n                    \u2009&lt;\u2009.001), and\n                    <jats:italic toggle=\"yes\">E<\/jats:italic>\n                    max (\n                    <jats:italic toggle=\"yes\">OR<\/jats:italic>\n                    \u2009=\u20091.02,\n                    <jats:italic toggle=\"yes\">p<\/jats:italic>\n                    \u2009=\u2009.001) as independent predictors, with an AUC of 0.85 (95%\n                    <jats:italic toggle=\"yes\">CI<\/jats:italic>\n                    : 0.78\u20130.91). Model 2 selected lesion size, Adler grade, and\n                    <jats:italic toggle=\"yes\">E<\/jats:italic>\n                    max as significant features, achieving an AUC of 0.88 (95%\n                    <jats:italic toggle=\"yes\">CI<\/jats:italic>\n                    : 0.81\u20130.92), with a 10-fold cross-validated accuracy of 0.81, Kappa of .57, and Hosmer-Lemeshow test (\n                    <jats:italic toggle=\"yes\">\u03c7<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    \u2009=\u20095.23,\n                    <jats:italic toggle=\"yes\">p<\/jats:italic>\n                    \u2009=\u2009.850) for calibration. The multimodal ultrasound-based logistic model significantly improves the diagnosis of non-microcalcified BI-RADS 4 breast lesions (AUC\u2009=\u20090.88), with lesion size, Adler grade, and\n                    <jats:italic toggle=\"yes\">E<\/jats:italic>\n                    max as key predictors, offering a cost-effective tool to reduce unnecessary biopsies in clinical practice.\n                  <\/jats:p>","DOI":"10.1177\/01617346261434982","type":"journal-article","created":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T07:51:56Z","timestamp":1775548316000},"page":"425-435","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Optimizing Diagnosis of Non-Microcalcified BI-RADS 4 Breast Lesions Using Multimodal Ultrasound Logistic Regression"],"prefix":"10.1177","volume":"48","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-2840-4798","authenticated-orcid":false,"given":"Yuqing","family":"He","sequence":"first","affiliation":[{"name":"Department of Ultrasound, The First Hospital of Qinhuangdao, Qinhuangdao, Hebei, PR China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-5086-0350","authenticated-orcid":false,"given":"Shuai","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, The First Hospital of Qinhuangdao, Qinhuangdao, Hebei, PR China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8253-0352","authenticated-orcid":false,"given":"Zizheng","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, The First Hospital of Qinhuangdao, Qinhuangdao, Hebei, PR China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-5611-3786","authenticated-orcid":false,"given":"Qingzhuang","family":"Gao","sequence":"additional","affiliation":[{"name":"Qinhuangdao Health School, Qinhuangdao, Hebei, PR China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7835-785X","authenticated-orcid":false,"given":"Hui","family":"Li","sequence":"additional","affiliation":[{"name":"Qinhuangdao Health School, Qinhuangdao, Hebei, PR China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-5355-843X","authenticated-orcid":false,"given":"Shanbing","family":"Gao","sequence":"additional","affiliation":[{"name":"Qinhuangdao Health School, Qinhuangdao, Hebei, PR China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,4,7]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21660"},{"key":"e_1_3_2_3_2","doi-asserted-by":"crossref","unstructured":"Palanisamy PK Dev B Sheela MC. BI-RADS: an overview. In: Dev B Joseph LD eds. Holistic Approach to Breast Disease. Springer; 2023 pp.53-60.","DOI":"10.1007\/978-981-99-0035-0_6"},{"key":"e_1_3_2_4_2","article-title":"Positive predictive value of BIRADS (breast imaging reporting and data system) IV lesions in detection of carcinoma breast, using histopathology as a gold standard","volume":"27","author":"Mehdi SA","year":"2020","unstructured":"Mehdi SA, Bukhari H, Shabbir I, Shabbir S. Positive predictive value of BIRADS (breast imaging reporting and data system) IV lesions in detection of carcinoma breast, using histopathology as a gold standard. Prof Med J. 2020;27:172-9.","journal-title":"Prof Med J"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.clinimag.2018.05.007"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41416-021-01459-x"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2022.106073"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-89010-0_4"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(07)61602-X"},{"key":"e_1_3_2_10_2","article-title":"ACR BI-RADS\u00ae atlas, breast imaging reporting and data system","author":"Mendelson EB","year":"2013","unstructured":"Mendelson EB, B\u00f6hm-V\u00e9lez M, Berg WA, et al. ACR BI-RADS\u00ae atlas, breast imaging reporting and data system. American College of Radiology; 2013. pp.97-9.","journal-title":"American College of Radiology;"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/0301-5629(90)90020-D"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12874-022-01681-y"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-48488-4"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2018.07.018"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.21037\/qims-20-1203"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.21037\/gs.2019.05.01"},{"issue":"4","key":"e_1_3_2_17_2","article-title":"Comparative effectiveness of mammography, ultrasound, and MRI in the detection of breast carcinoma in dense breast tissue: a systematic review","volume":"16","author":"Abu Abeelh E","year":"2024","unstructured":"Abu Abeelh E, AbuAbeileh Z. Comparative effectiveness of mammography, ultrasound, and MRI in the detection of breast carcinoma in dense breast tissue: a systematic review. Cureus. 2024;16(4):e58042.","journal-title":"Cureus"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.20892\/j.issn.2095-3941.2021.0676"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12880-024-01287-4"},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.3934\/mbe.2019085"},{"key":"e_1_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12885-020-07423-x"},{"issue":"9","key":"e_1_3_2_22_2","article-title":"A nomogram for predicting breast cancer based on hematologic and ultrasound parameters","volume":"15","author":"Liu Y","year":"2023","unstructured":"Liu Y, Zhu H, Yuan J, Wu G. A nomogram for predicting breast cancer based on hematologic and ultrasound parameters. Am J Transl Res. 2023;15(9):5602-12.","journal-title":"Am J Transl Res"},{"key":"e_1_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10549-022-06804-z"},{"key":"e_1_3_2_24_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12880-021-00707-z"},{"key":"e_1_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12885-022-10240-z"},{"issue":"9","key":"e_1_3_2_26_2","article-title":"Underestimation of invasive breast carcinoma in patients with initial diagnosis of ductal carcinoma in situ: size matters","volume":"99","author":"Bouz\u00f3n Alejandro A","year":"2021","unstructured":"Bouz\u00f3n Alejandro A, Iglesias L\u00f3pez \u00c1, Acea Nebril B, Garc\u00eda Jim\u00e9nez ML, D\u00edaz Carballada CC, Varela RomeroJR. Underestimation of invasive breast carcinoma in patients with initial diagnosis of ductal carcinoma in situ: size matters. Cir Esp. 2021;99(9):655-9.","journal-title":"Cir Esp"},{"key":"e_1_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.3233\/CH-211258"},{"key":"e_1_3_2_28_2","doi-asserted-by":"publisher","DOI":"10.21037\/qims-23-956"},{"key":"e_1_3_2_29_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2024.111415"},{"key":"e_1_3_2_30_2","doi-asserted-by":"publisher","DOI":"10.21037\/qims-21-341"}],"container-title":["Ultrasonic Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/01617346261434982","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/01617346261434982","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/01617346261434982","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T11:18:32Z","timestamp":1791026312000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/01617346261434982"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,7]]},"references-count":29,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2026,11]]}},"alternative-id":["10.1177\/01617346261434982"],"URL":"https:\/\/doi.org\/10.1177\/01617346261434982","relation":{},"ISSN":["0161-7346","1096-0910"],"issn-type":[{"value":"0161-7346","type":"print"},{"value":"1096-0910","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,7]]}}}