{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T08:26:58Z","timestamp":1793867218051,"version":"4.6.1"},"reference-count":43,"publisher":"Elsevier BV","issue":"11","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"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":[[2026,11]]},"DOI":"10.1016\/j.acra.2026.08.101","type":"journal-article","created":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T11:38:33Z","timestamp":1789731513000},"page":"5218-5230","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["Radiomics and Deep Learning Models Based on Manual and Semi-automatic Segmentation of Ultrasound Images for HER2 Prediction in Bladder Cancer"],"prefix":"10.1016","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7021-7852","authenticated-orcid":false,"given":"Jiajing","family":"Zhuang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yihan","family":"Xie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuefan","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenting","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangtian","family":"Lian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yifan","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huiping","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoqing","family":"Fan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fen","family":"Fu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1310-9641","authenticated-orcid":false,"given":"Qin","family":"Ye","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.acra.2026.08.101_bib1","first-page":"229","article-title":"Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"74","author":"Bray","year":"2024","journal-title":"CA Cancer J Clin"},{"issue":"6","key":"10.1016\/j.acra.2026.08.101_bib2","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1016\/j.eururo.2024.07.027","article-title":"European Association of Urology Guidelines on Non-muscle-invasive Bladder Cancer (TaT1 and Carcinoma In Situ)-a summary of the 2024 Guidelines Update","volume":"86","author":"Gontero","year":"2024","journal-title":"Eur Urol"},{"issue":"5","key":"10.1016\/j.acra.2026.08.101_bib3","doi-asserted-by":"crossref","first-page":"582","DOI":"10.1016\/j.eururo.2025.02.019","article-title":"European Association of Urology Guidelines on Muscle-invasive and Metastatic Bladder Cancer: summary of the 2025 Guidelines","volume":"87","author":"van der Heijden","year":"2025","journal-title":"Eur Urol"},{"issue":"2","key":"10.1016\/j.acra.2026.08.101_bib4","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1158\/1078-0432.CCR-25-1982","article-title":"Advances in targeting HER2 across cancer subtypes: a pan-tumor approach","volume":"32","author":"Adesoye","year":"2026","journal-title":"Clin Cancer Res"},{"issue":"10","key":"10.1016\/j.acra.2026.08.101_bib5","first-page":"1759","article-title":"Analysis of HER2 expression in different histological subtypes and IHC-based molecular variants of muscle-invasive bladder carcinoma","volume":"61","author":"Kraevska","year":"2025","journal-title":"Med (Kaunas)"},{"issue":"6","key":"10.1016\/j.acra.2026.08.101_bib6","doi-asserted-by":"crossref","first-page":"653","DOI":"10.1097\/MOU.0000000000001330","article-title":"Antibody-drug conjugates for non-muscle invasive bladder cancer: current status and future development","volume":"35","author":"Bracco","year":"2025","journal-title":"Curr Opin Urol"},{"issue":"10","key":"10.1016\/j.acra.2026.08.101_bib7","article-title":"Efficacy of disitamab vedotin and immune profiles in high-risk non-muscle-invasive bladder cancer with HER2 overexpression","volume":"6","author":"Liu","year":"2025","journal-title":"MedComm (2020)"},{"key":"10.1016\/j.acra.2026.08.101_bib8","doi-asserted-by":"crossref","DOI":"10.1007\/s11255-026-05110-7","article-title":"Stage-specific associations of HER2 overexpression with clinical and pathological features in bladder cancer: a systematic review and meta-analysis","author":"Guo","year":"2026","journal-title":"Int Urol Nephrol"},{"issue":"8","key":"10.1016\/j.acra.2026.08.101_bib9","doi-asserted-by":"crossref","DOI":"10.1136\/jitc-2025-011881","article-title":"Overcoming immunotherapy resistance in bladder cancer with a novel antibody-drug conjugate RC48","volume":"13","author":"Xiao","year":"2025","journal-title":"J Immunother Cancer"},{"issue":"12","key":"10.1016\/j.acra.2026.08.101_bib10","doi-asserted-by":"crossref","first-page":"2685","DOI":"10.1002\/jum.15659","article-title":"Radiomics analysis based on ultrasound images to distinguish the tumor stage and pathological grade of bladder cancer","volume":"40","author":"Gao","year":"2021","journal-title":"J Ultrasound Med"},{"issue":"11","key":"10.1016\/j.acra.2026.08.101_bib11","doi-asserted-by":"crossref","first-page":"1682","DOI":"10.1016\/j.acra.2022.02.007","article-title":"Bladder urothelial carcinoma: machine learning-based computed tomography radiomics for prediction of histological variant","volume":"29","author":"Evrimler","year":"2022","journal-title":"Acad Radiol"},{"issue":"1","key":"10.1016\/j.acra.2026.08.101_bib12","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1186\/s13244-025-01988-6","article-title":"Deep learning feature-based model for predicting lymphovascular invasion in urothelial carcinoma of bladder using CT images","volume":"16","author":"Xiao","year":"2025","journal-title":"Insights Imaging"},{"issue":"7","key":"10.1016\/j.acra.2026.08.101_bib13","first-page":"3523","article-title":"Image segmentation using deep learning: a survey","volume":"44","author":"Minaee","year":"2022","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"12","key":"10.1016\/j.acra.2026.08.101_bib14","first-page":"1355","article-title":"Radiomics prediction of muscle invasion in bladder cancer using semi-automatic lesion segmentation of MRI compared with manual segmentation","volume":"10","author":"Ye","year":"2023","journal-title":"Bioeng (Basel)"},{"issue":"1","key":"10.1016\/j.acra.2026.08.101_bib15","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1186\/s12880-024-01521-z","article-title":"An ultrasound image segmentation method for thyroid nodules based on dual-path attention mechanism-enhanced UNet+","volume":"24","author":"Dong","year":"2024","journal-title":"BMC Med Imaging"},{"issue":"7","key":"10.1016\/j.acra.2026.08.101_bib16","doi-asserted-by":"crossref","first-page":"967","DOI":"10.1007\/s11548-018-1733-7","article-title":"Automatic bladder segmentation from CT images using deep CNN and 3D fully connected CRF-RNN","volume":"13","author":"Xu","year":"2018","journal-title":"Int J Comput Assist Radiol Surg"},{"issue":"1","key":"10.1016\/j.acra.2026.08.101_bib17","doi-asserted-by":"crossref","first-page":"628","DOI":"10.1038\/s41598-023-27883-y","article-title":"Automatic segmentation of bladder cancer on MRI using a convolutional neural network and reproducibility of radiomics features: a two-center study","volume":"13","author":"Moribata","year":"2023","journal-title":"Sci Rep"},{"key":"10.1016\/j.acra.2026.08.101_bib18","doi-asserted-by":"crossref","first-page":"3992","DOI":"10.1109\/ICCV51070.2023.00371","article-title":"\"Segment Anything","author":"Kirillov","year":"2023","journal-title":"2023 IEEE\/CVF Int Conf Comput Vision (ICCV) Paris Fr"},{"issue":"3","key":"10.1016\/j.acra.2026.08.101_bib19","doi-asserted-by":"crossref","first-page":"230","DOI":"10.5582\/bst.2023.01119","article-title":"The potential of 'Segment Anything' (SAM) for universal intelligent ultrasound image guidance","volume":"17","author":"Ning","year":"2023","journal-title":"Biosci Trends"},{"issue":"6","key":"10.1016\/j.acra.2026.08.101_bib20","doi-asserted-by":"crossref","first-page":"4513","DOI":"10.1002\/mp.17785","article-title":"A segment anything model-guided and match-based semi-supervised segmentation framework for medical imaging","volume":"52","author":"Xu","year":"2025","journal-title":"Med Phys"},{"issue":"2","key":"10.1016\/j.acra.2026.08.101_bib21","article-title":"SAM-MedUS: a foundational model for universal ultrasound image segmentation","volume":"12","author":"Tian","year":"2025","journal-title":"J Med Imaging (Bellingham)"},{"issue":"1","key":"10.1016\/j.acra.2026.08.101_bib22","doi-asserted-by":"crossref","first-page":"654","DOI":"10.1038\/s41467-024-44824-z","article-title":"Segment anything in medical images","volume":"15","author":"Ma","year":"2024","journal-title":"Nat Commun"},{"key":"10.1016\/j.acra.2026.08.101_bib23","article-title":"Rectal-RadioSAM: large model-assisted multi-parametric magnetic resonance imaging pipeline for predicting response to neoadjuvant chemoradiotherapy in rectal cancer without human intervention","volume":"35","author":"Xia","year":"2025","journal-title":"Phys Imaging Radiat Oncol"},{"key":"10.1016\/j.acra.2026.08.101_bib24","doi-asserted-by":"crossref","DOI":"10.3389\/fradi.2026.1702977","article-title":"A vision transformer-radiomics approach for enhanced chemotherapy outcome prediction in ovarian cancer","volume":"6","author":"Abdoli","year":"2026","journal-title":"Front Radiol"},{"key":"10.1016\/j.acra.2026.08.101_bib25","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1186\/s12885-026-15715-x","article-title":"Noninvasive preoperative risk stratification of prostate cancer via a foundational model based deep learning with PSMA PET\/CT","volume":"26","author":"Bian","year":"2026","journal-title":"BMC Cancer"},{"issue":"22","key":"10.1016\/j.acra.2026.08.101_bib26","doi-asserted-by":"crossref","first-page":"3867","DOI":"10.1200\/JCO.22.02864","article-title":"Human epidermal growth factor receptor 2 testing in breast cancer: ASCO-College of American Pathologists Guideline Update","volume":"41","author":"Wolff","year":"2023","journal-title":"J Clin Oncol"},{"issue":"10","key":"10.1016\/j.acra.2026.08.101_bib27","first-page":"1001","article-title":"Clinical pathological expert consensus on HER-2 testing in urothelial carcinoma in China [J]","volume":"43","author":"Tumor Pathology Committee of Chinese Anti-Cancer Association","year":"2021","journal-title":"Chin J Oncol"},{"issue":"7","key":"10.1016\/j.acra.2026.08.101_bib28","doi-asserted-by":"crossref","DOI":"10.1016\/j.modpat.2025.100753","article-title":"Spatial expression of HER2, NECTIN4, and TROP-2 in muscle-invasive bladder cancer and metastases: implications for pathological and clinical management","volume":"38","author":"Dernbach","year":"2025","journal-title":"Mod Pathol"},{"key":"10.1016\/j.acra.2026.08.101_bib29","doi-asserted-by":"crossref","first-page":"4360","DOI":"10.1007\/s00259-025-07314-y","article-title":"Should end-to-end deep learning replace handcrafted radiomics?","volume":"52","author":"Buvat","year":"2025","journal-title":"Eur J Nucl Med Mol Imaging"},{"issue":"1","key":"10.1016\/j.acra.2026.08.101_bib30","doi-asserted-by":"crossref","first-page":"510","DOI":"10.1186\/s12885-024-12277-8","article-title":"Deep learning-assisted diagnosis of benign and malignant parotid tumors based on ultrasound: a retrospective study","volume":"24","author":"Jiang","year":"2024","journal-title":"BMC Cancer"},{"key":"10.1016\/j.acra.2026.08.101_bib31","article-title":"Ultrasound image classification of thyroid nodules based on deep learning","volume":"12","author":"Yang","year":"2022","journal-title":"Front Oncol"},{"issue":"3","key":"10.1016\/j.acra.2026.08.101_bib32","doi-asserted-by":"crossref","first-page":"83","DOI":"10.21037\/tau-2025-1-899","article-title":"Radiomics and deep learning fusion model based on multiphasic CT for predicting HER2 expression status in bladder urothelial carcinoma: a multicenter study","volume":"15","author":"Pan","year":"2026","journal-title":"Transl Androl Urol"},{"issue":"22","key":"10.1016\/j.acra.2026.08.101_bib33","doi-asserted-by":"crossref","first-page":"1117","DOI":"10.1080\/17520363.2025.2590778","article-title":"A CT-based deep learning radiomics model for predicting HER2 expression and prognosis in non-muscle-invasive bladder cancer","volume":"19","author":"Jin","year":"2025","journal-title":"Biomark Med"},{"issue":"21","key":"10.1016\/j.acra.2026.08.101_bib34","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6560\/ad84b2","article-title":"Dual convolution-transformer UNet (DCT-UNet) for organs at risk and clinical target volume segmentation in MRI for cervical cancer brachytherapy","volume":"69","author":"Kim","year":"2024","journal-title":"Phys Med Biol"},{"issue":"7","key":"10.1016\/j.acra.2026.08.101_bib35","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0308181","article-title":"Deep-learning-based segmentation using individual patient data on prostate cancer radiation therapy","volume":"19","author":"Jeong","year":"2024","journal-title":"PLoS One"},{"issue":"1","key":"10.1016\/j.acra.2026.08.101_bib36","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1016\/j.ultrasmedbio.2025.09.013","article-title":"Prediction of HER2 expression in urothelial carcinoma of the bladder: are ultrasound-based radiomic features significant?","volume":"52","author":"Zhuang","year":"2026","journal-title":"Ultrasound Med Biol"},{"issue":"6","key":"10.1016\/j.acra.2026.08.101_bib37","doi-asserted-by":"crossref","first-page":"3258","DOI":"10.1097\/JS9.0000000000001483","article-title":"Radiomics-based machine learning approach for the prediction of grade and stage in upper urinary tract urothelial carcinoma: a step towards virtual biopsy","volume":"110","author":"Alqahtani","year":"2024","journal-title":"Int J Surg"},{"issue":"3","key":"10.1016\/j.acra.2026.08.101_bib38","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1007\/s11548-025-03562-3","article-title":"Benchmarking variability in semantic segmentation in minimally invasive abdominal surgery","volume":"21","author":"Castro","year":"2026","journal-title":"Int J Comput Assist Radiol Surg"},{"issue":"7","key":"10.1016\/j.acra.2026.08.101_bib39","doi-asserted-by":"crossref","first-page":"3092","DOI":"10.1007\/s00261-024-04715-9","article-title":"A novel artificial intelligence segmentation model for early diagnosis of bladder tumors","volume":"50","author":"Li","year":"2025","journal-title":"Abdom Radiol (NY)"},{"issue":"2","key":"10.1016\/j.acra.2026.08.101_bib40","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1038\/s41585-025-01075-x","article-title":"HER2 and urothelial carcinoma: current understanding and future directions","volume":"23","author":"Raggi","year":"2026","journal-title":"Nat Rev Urol"},{"issue":"19","key":"10.1016\/j.acra.2026.08.101_bib41","doi-asserted-by":"crossref","DOI":"10.1002\/cam4.71289","article-title":"Distinct clinicopathological features of HER2-negative, HER2-low, and HER2-overexpressing urothelial carcinoma in a large Chinese cohort","volume":"14","author":"Wang","year":"2025","journal-title":"Cancer Med"},{"issue":"1","key":"10.1016\/j.acra.2026.08.101_bib42","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1056\/NEJMoa2203690","article-title":"Trastuzumab deruxtecan in previously treated HER2-low advanced breast cancer","volume":"387","author":"Modi","year":"2022","journal-title":"N Engl J Med"},{"issue":"4","key":"10.1016\/j.acra.2026.08.101_bib43","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pdig.0001309","article-title":"Segment anything small for ultrasound: enhancing segmentation with non-generative augmentation","volume":"5","author":"Ferreira","year":"2026","journal-title":"PLOS Digit Health"}],"container-title":["Academic Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1076633226007154?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1076633226007154?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T07:49:44Z","timestamp":1793864984000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1076633226007154"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":43,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2026,11]]}},"alternative-id":["S1076633226007154"],"URL":"https:\/\/doi.org\/10.1016\/j.acra.2026.08.101","relation":{},"ISSN":["1076-6332"],"issn-type":[{"value":"1076-6332","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Radiomics and Deep Learning Models Based on Manual and Semi-automatic Segmentation of Ultrasound Images for HER2 Prediction in Bladder Cancer","name":"articletitle","label":"Article Title"},{"value":"Academic Radiology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.acra.2026.08.101","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"}]}}