{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T11:00:28Z","timestamp":1790852428608,"version":"4.1.0"},"reference-count":31,"publisher":"Elsevier BV","issue":"10","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U25C2047"],"award-info":[{"award-number":["U25C2047"]}],"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":["82502355"],"award-info":[{"award-number":["82502355"]}],"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":["82071928"],"award-info":[{"award-number":["82071928"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013804","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100013804","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["YG2025QNB03"],"award-info":[{"award-number":["YG2025QNB03"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["YG2024ZD03"],"award-info":[{"award-number":["YG2024ZD03"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["academicradiology.org","clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Academic Radiology"],"published-print":{"date-parts":[[2026,10]]},"DOI":"10.1016\/j.acra.2026.07.037","type":"journal-article","created":{"date-parts":[[2026,8,8]],"date-time":"2026-08-08T11:23:56Z","timestamp":1786188236000},"page":"4336-4348","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["Predicting Breast Cancer with Super-Resolution Ultrasound-Based Radiomics: A Multicenter Retrospective Study"],"prefix":"10.1016","volume":"33","author":[{"given":"JiaLe","family":"Xu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"YuHang","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"XiaoHong","family":"Jia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qing","family":"Hua","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"ShuJun","family":"Xia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"BingHui","family":"Tang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"SiYu","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"XiaoYing","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiao","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"XueQin","family":"Hou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"YanFeng","family":"Yao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"XiaoCen","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan","family":"Lyu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"LiJuan","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Kong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"YanLing","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"GuoYong","family":"Hua","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"YuLu","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"FangGang","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuan","family":"Tian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"YiJie","family":"Dong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Shi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"JianQiao","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.acra.2026.07.037_bib1","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1016\/j.cell.2011.02.013","article-title":"Hallmarks of cancer: the next generation","volume":"144","author":"Hanahan","year":"2011","journal-title":"Cell"},{"key":"10.1016\/j.acra.2026.07.037_bib2","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1126\/science.1104819","article-title":"Normalization of tumor vasculature: an emerging concept in antiangiogenic therapy","volume":"307","author":"Jain","year":"2005","journal-title":"Science"},{"key":"10.1016\/j.acra.2026.07.037_bib3","doi-asserted-by":"crossref","first-page":"4474","DOI":"10.7150\/jca.44313","article-title":"Angiogenesis in breast cancer progression, diagnosis, and treatment","volume":"11","author":"Madu","year":"2020","journal-title":"J Cancer"},{"key":"10.1016\/j.acra.2026.07.037_bib4","doi-asserted-by":"crossref","first-page":"7503","DOI":"10.1007\/s00330-024-10796-3","article-title":"Super-resolution ultrasound and microvasculomics: a consensus statement","volume":"34","author":"Xia","year":"2024","journal-title":"Eur Radiol"},{"key":"10.1016\/j.acra.2026.07.037_bib5","doi-asserted-by":"crossref","DOI":"10.1063\/1.4826597","article-title":"Sono-activated ultrasound localization microscopy","volume":"103","author":"Desailly","year":"2013","journal-title":"Appl Phys Lett"},{"key":"10.1016\/j.acra.2026.07.037_bib6","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1109\/TMI.2014.2359650","article-title":"In vivo acoustic super-resolution and super-resolved velocity mapping using microbubbles","volume":"34","author":"Christensen-Jeffries","year":"2014","journal-title":"IEEE Trans Med Imaging"},{"key":"10.1016\/j.acra.2026.07.037_bib7","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1038\/nature16066","article-title":"Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging","volume":"527","author":"Errico","year":"2015","journal-title":"Nature"},{"key":"10.1016\/j.acra.2026.07.037_bib8","article-title":"Ultrasound super-resolution imaging for differential diagnosis of breast masses","volume":"12","author":"Zhang","year":"2022","journal-title":"Front Oncol"},{"key":"10.1016\/j.acra.2026.07.037_bib9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s41747-024-00540-3","article-title":"Focal liver lesions: multiparametric microvasculature characterization via super-resolution ultrasound imaging","volume":"8","author":"Zeng","year":"2024","journal-title":"Eur Radiol Exp"},{"key":"10.1016\/j.acra.2026.07.037_bib10","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1186\/s41747-025-00561-6","article-title":"Mapping of prostate cancer microvascular patterns using super-resolution ultrasound imaging","volume":"9","author":"Butler","year":"2025","journal-title":"Eur Radiol Exp"},{"key":"10.1016\/j.acra.2026.07.037_bib11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40644-024-00819-z","article-title":"Ultrasound super-resolution imaging for non-invasive assessment of microvessel in prostate lesion","volume":"25","author":"Huang","year":"2025","journal-title":"Cancer Imaging"},{"key":"10.1016\/j.acra.2026.07.037_bib12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00330-025-11520-5","article-title":"Super-resolution ultrasound imaging of intranodal lymphatic sinuses for predicting sentinel lymph node metastasis in breast cancer: a preliminary study","volume":"35","author":"Xia","year":"2025","journal-title":"Eur Radiol"},{"key":"10.1016\/j.acra.2026.07.037_bib13","doi-asserted-by":"crossref","first-page":"e262","DOI":"10.1016\/S1470-2045(19)30149-4","article-title":"Big data and machine learning algorithms for health-care delivery","volume":"20","author":"Ngiam","year":"2019","journal-title":"Lancet Oncol"},{"key":"10.1016\/j.acra.2026.07.037_bib14","doi-asserted-by":"crossref","first-page":"9511","DOI":"10.1007\/s00330-021-08009-2","article-title":"Clinical value of radiomics and machine learning in breast ultrasound: a multicenter study for differential diagnosis of benign and malignant lesions","volume":"31","author":"Romeo","year":"2021","journal-title":"Eur Radiol"},{"key":"10.1016\/j.acra.2026.07.037_bib15","doi-asserted-by":"crossref","first-page":"1961","DOI":"10.1002\/jum.15873","article-title":"Machine learning assisted Doppler features for enhancing thyroid cancer diagnosis: a multi-cohort study","volume":"41","author":"Zhu","year":"2022","journal-title":"J Ultrasound Med"},{"key":"10.1016\/j.acra.2026.07.037_bib16","doi-asserted-by":"crossref","first-page":"1797","DOI":"10.1016\/j.ultrasmedbio.2017.05.002","article-title":"A machine-learning algorithm toward color analysis for chronic liver disease classification, employing ultrasound shear wave elastography","volume":"43","author":"Gatos","year":"2017","journal-title":"Ultrasound Med Biol"},{"key":"10.1016\/j.acra.2026.07.037_bib17","doi-asserted-by":"crossref","DOI":"10.3389\/fonc.2023.1158736","article-title":"Conventional ultrasound and contrast-enhanced ultrasound radiomics in breast cancer and molecular subtype diagnosis","volume":"13","author":"Gong","year":"2023","journal-title":"Front Oncol"},{"key":"10.1016\/j.acra.2026.07.037_bib18","doi-asserted-by":"crossref","first-page":"1058","DOI":"10.1016\/j.ultrasmedbio.2016.12.016","article-title":"Sonoelastomics for breast tumor classification: a radiomics approach with clustering-based feature selection on sonoelastography","volume":"43","author":"Zhang","year":"2017","journal-title":"Ultrasound Med Biol"},{"key":"10.1016\/j.acra.2026.07.037_bib19","series-title":"2019 41st annual international conference of the IEEE engineering in medicine and biology society (EMBC)","first-page":"933","article-title":"Ultrasound-based diagnosis of breast tumor with parameter transfer multilayer kernel extreme learning machine","author":"Fei","year":"2019"},{"key":"10.1016\/j.acra.2026.07.037_bib20","series-title":"A study of cross-validation and bootstrap for accuracy estimation and model selection","first-page":"1137","author":"Kohavi","year":"1995"},{"key":"10.1016\/j.acra.2026.07.037_bib21","doi-asserted-by":"crossref","first-page":"837","DOI":"10.2307\/2531595","article-title":"Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach","volume":"44","author":"DeLong","year":"1988","journal-title":"Biometrics"},{"key":"10.1016\/j.acra.2026.07.037_bib22","series-title":"Breast imaging reporting and data system","author":"Radiology AC","year":"2003"},{"key":"10.1016\/j.acra.2026.07.037_bib23","doi-asserted-by":"crossref","first-page":"1527","DOI":"10.1038\/s41467-018-03973-8","article-title":"Motion model ultrasound localization microscopy for preclinical and clinical multiparametric tumor characterization","volume":"9","author":"Opacic","year":"2018","journal-title":"Nat Commun"},{"key":"10.1016\/j.acra.2026.07.037_bib24","doi-asserted-by":"crossref","DOI":"10.1259\/bjr.20160546","article-title":"Superb microvascular imaging in diagnosis of breast lesions: a comparative study with contrast-enhanced ultrasonographic microvascular imaging","volume":"89","author":"Xiao","year":"2016","journal-title":"Br J Radiol"},{"key":"10.1016\/j.acra.2026.07.037_bib25","doi-asserted-by":"crossref","first-page":"151","DOI":"10.2147\/BCTT.S176070","article-title":"Epidemiological characteristics of and risk factors for breast cancer in the world","volume":"11","author":"Momenimovahed","year":"2019","journal-title":"Breast Cancer Targets Ther"},{"key":"10.1016\/j.acra.2026.07.037_bib26","doi-asserted-by":"crossref","first-page":"759","DOI":"10.3348\/kjr.2018.0515","article-title":"A prospective study on the value of ultrasound microflow assessment to distinguish malignant from benign solid breast masses: association between ultrasound parameters and histologic microvessel densities","volume":"20","author":"Park","year":"2019","journal-title":"Korean J Radiol"},{"key":"10.1016\/j.acra.2026.07.037_bib27","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1002\/jum.16377","article-title":"Ultrasound radiomics features to identify patients with triple-negative breast cancer: a retrospective, single-center study","volume":"43","author":"Cai","year":"2024","journal-title":"J Ultrasound Med"},{"key":"10.1016\/j.acra.2026.07.037_bib28","doi-asserted-by":"crossref","first-page":"872","DOI":"10.1007\/s00330-022-09043-4","article-title":"Multicenter clinical radiomics\u2013integrated model based on [18F] FDG PET and multi-modal MRI predict ATRX mutation status in IDH-mutant lower-grade gliomas","volume":"33","author":"Zhang","year":"2023","journal-title":"Eur Radiol"},{"key":"10.1016\/j.acra.2026.07.037_bib29","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1002\/uog.24805","article-title":"Developing and validating ultrasound-based radiomics models for predicting high-risk endometrial cancer","volume":"60","author":"Moro","year":"2022","journal-title":"Ultrasound Obstet Gynecol"},{"key":"10.1016\/j.acra.2026.07.037_bib30","doi-asserted-by":"crossref","DOI":"10.1016\/j.jbo.2024.100599","article-title":"Radiomics model based on MRI to differentiate spinal multiple myeloma from metastases: a two-center study","volume":"45","author":"Cao","year":"2024","journal-title":"J Bone Oncol"},{"key":"10.1016\/j.acra.2026.07.037_bib31","doi-asserted-by":"crossref","DOI":"10.1155\/2021\/5491017","article-title":"Research on key algorithms of the lung CAD system based on cascade feature and hybrid swarm intelligence optimization for MKL-SVM","volume":"2021","author":"Chang","year":"2021","journal-title":"Comput Intell Neurosci"}],"container-title":["Academic Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1076633226005441?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1076633226005441?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T10:49:55Z","timestamp":1790851795000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1076633226005441"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":31,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2026,10]]}},"alternative-id":["S1076633226005441"],"URL":"https:\/\/doi.org\/10.1016\/j.acra.2026.07.037","relation":{},"ISSN":["1076-6332"],"issn-type":[{"value":"1076-6332","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Predicting Breast Cancer with Super-Resolution Ultrasound-Based Radiomics: A Multicenter Retrospective Study","name":"articletitle","label":"Article Title"},{"value":"Academic Radiology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.acra.2026.07.037","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Association of Academic Radiology. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}]}}