{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T13:13:32Z","timestamp":1780406012646,"version":"3.54.1"},"reference-count":50,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T00:00:00Z","timestamp":1780012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med. Technol."],"abstract":"<jats:p>Cervical intraepithelial neoplasia (CIN) grading relies on both morphological assessment from hematoxylin and eosin (H&amp;amp;E) slides and biomarker expression from immunohistochemistry (IHC), such as p16 and Ki-67. However, conventional IHC staining is time-consuming, costly, and requires additional tissue sections. To address these limitations, we propose an attention-guided and multi-instance learning (MIL) constrained CycleGAN framework for high-fidelity virtual IHC staining generation from H&amp;amp;E images. To better utilize the correspondence between H&amp;amp;E and IHC slides, we adopt a weakly paired training strategy. Specifically, whole-slide image registration is first applied to align H&amp;amp;E and corresponding IHC slides, followed by patch-level pairing for model training. Considering the inherent spatial misalignment between adjacent tissue sections, the proposed framework integrates attention-guided constraints and MIL-based supervision to enhance structural consistency and biomarker distribution reliability. In addition to quantitative image-level and diagnostic evaluations, we further conduct an expert-based clinical assessment. Two experienced pathologists independently evaluated CIN grading using H&amp;amp;E slides with and without virtual staining. The results demonstrate that the inclusion of virtual IHC improves diagnostic performance, supporting the clinical utility of the proposed method. To evaluate generalization capability, we additionally validate the model on an external dataset (ACROBAT) under cross-domain conditions. This experiment is designed to assess robustness rather than direct task alignment, providing supplementary evidence of model transferability. We also acknowledge the potential risk of false-positive biomarker synthesis in virtual staining. To address this, we incorporate statistical consistency constraints and provide quantitative evaluation, including diagnostic consistency and expert assessment, which together support the biological plausibility of the generated staining patterns. Overall, the proposed framework provides a practical and clinically relevant solution for virtual IHC generation, achieving superior performance across key evaluation metrics including accuracy (ACC), area under the curve (AUC), and kappa scores, while also demonstrating improved diagnostic support and cross-domain generalization capability.<\/jats:p>","DOI":"10.3389\/fmedt.2026.1783365","type":"journal-article","created":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T06:10:53Z","timestamp":1780035053000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Attention-guided and MIL-constrained CycleGAN for high-fidelity virtual p16 and Ki-67 staining"],"prefix":"10.3389","volume":"8","author":[{"given":"Xinli","family":"Lei","sequence":"first","affiliation":[{"name":"Department of Pathology, Maternal and Child Health Hospital of Ganzhou City","place":["Ganzhou, Jiangxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuefeng","family":"Xie","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University","place":["Tianjin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andi","family":"Duan","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University","place":["Tianjin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuhang","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University","place":["Tianjin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linhong","family":"Liao","sequence":"additional","affiliation":[{"name":"Department of Pathology, Maternal and Child Health Hospital of Ganzhou City","place":["Ganzhou, Jiangxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xi","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Pathology, Maternal and Child Health Hospital of Ganzhou City","place":["Ganzhou, Jiangxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,5,29]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"209","DOI":"10.3322\/caac.21660","article-title":"Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"71","author":"Sung","year":"2021","journal-title":"CA Cancer J Clin"},{"key":"B2","volume-title":"Diagnostic Gynecologic and Obstetric Pathology E-Book","author":"Crum","year":"2017"},{"key":"B3","doi-asserted-by":"publisher","first-page":"1266","DOI":"10.5858\/arpa.LGT200570","article-title":"The lower anogenital squamous terminology standardization project for HPV-associated lesions: background and consensus recommendations from the College of American Pathologists and the American Society for Colposcopy and Cervical Pathology","volume":"136","author":"Darragh","year":"2012","journal-title":"Arch Pathol Lab Med"},{"key":"B4","doi-asserted-by":"publisher","first-page":"e191","DOI":"10.1016\/S2214-109X(19)30482-6","article-title":"Estimates of incidence and mortality of cervical cancer in 2018: a worldwide analysis","volume":"8","author":"Arbyn","year":"2020","journal-title":"Lancet Glob Health"},{"key":"B5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1097\/LGT.0b013e318287d329","article-title":"2012 updated consensus guidelines for the management of abnormal cervical cancer screening tests and cancer precursors","volume":"17","author":"Massad","year":"2013","journal-title":"J Low Genit Tract Dis"},{"key":"B6","doi-asserted-by":"publisher","first-page":"1500","DOI":"10.1001\/jama.285.11.1500","article-title":"Interobserver reproducibility of cervical cytologic and histologic interpretations: realistic estimates from the ASCUS-LSIL Triage Study","volume":"285","author":"Stoler","year":"2001","journal-title":"Jama"},{"key":"B7","doi-asserted-by":"publisher","first-page":"e140","DOI":"10.1016\/S1470-2045(24)00524-2","article-title":"Active surveillance of cervical intraepithelial neoplasia grade 2: 2025 British Society of Colposcopy and Cervical Pathology and European Society of Gynaecologic Oncology consensus statement","volume":"26","author":"Kyrgiou","year":"2025","journal-title":"Lancet Oncol"},{"key":"B8","doi-asserted-by":"publisher","first-page":"4154","DOI":"10.1158\/1078-0432.CCR-12-0270","article-title":"Performance of p16\/Ki-67 immunostaining to detect cervical cancer precursors in a colposcopy referral population","volume":"18","author":"Wentzensen","year":"2012","journal-title":"Clin Cancer Res"},{"key":"B9","doi-asserted-by":"publisher","first-page":"2600431","DOI":"10.1080\/10667857.2025.2600431","article-title":"Redefining detection with nanobiosensors: exploring sensor types, fabrication techniques, and multi-scale applications","volume":"40","author":"Thalluri","year":"2025","journal-title":"Mater Technol"},{"key":"B10","doi-asserted-by":"publisher","first-page":"492","DOI":"10.1002\/ijc.33250","article-title":"Dual staining for p16\/Ki-67 to detect high-grade cervical lesions: results from the screening triage ascertaining intraepithelial neoplasia by immunostain testing study","volume":"148","author":"El-Zein","year":"2021","journal-title":"Int J Cancer"},{"key":"B11","doi-asserted-by":"publisher","first-page":"884","DOI":"10.1097\/00000478-200107000-00006","article-title":"Ki-67, cyclin E, and p16 INK4 are complimentary surrogate biomarkers for human papilloma virus-related cervical neoplasia","volume":"25","author":"Keating","year":"2001","journal-title":"Am J Surg Pathol"},{"key":"B12","doi-asserted-by":"publisher","first-page":"1296","DOI":"10.3332\/ecancer.2021.1296","article-title":"Oncology training and education initiatives in low and middle income countries: a scoping review","volume":"15","author":"Karim","year":"2021","journal-title":"Ecancermedicalscience"},{"key":"B13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.4102\/ajlm.v5i1.187","article-title":"Development of immunohistochemistry services for cancer care in western Kenya: Implications for low-and middle-income countries","volume":"5","author":"Patel","year":"2016","journal-title":"Afr J Lab Med"},{"key":"B14","doi-asserted-by":"publisher","first-page":"1953","DOI":"10.1016\/S0140-6736(18)30460-4","article-title":"Delivering modern, high-quality, affordable pathology and laboratory medicine to low-income and middle-income countries: a call to action","volume":"391","author":"Horton","year":"2018","journal-title":"Lancet"},{"key":"B15","doi-asserted-by":"publisher","first-page":"100777","DOI":"10.1016\/j.jvacx.2025.100777","article-title":"Evolving COVID-19 subvariants and waning vaccine-induced immunity: a new public health risk for the African continent","volume":"28","author":"Bukke","year":"2026","journal-title":"Vaccine: X"},{"key":"B16","doi-asserted-by":"publisher","first-page":"102992","DOI":"10.1016\/j.eclinm.2024.102992","article-title":"Performance of artificial intelligence for diagnosing cervical intraepithelial neoplasia and cervical cancer: a systematic review and meta-analysis","volume":"80","author":"Liu","year":"2025","journal-title":"EClinicalMedicine"},{"key":"B17","doi-asserted-by":"publisher","first-page":"1177","DOI":"10.1016\/j.tibtech.2024.02.009","article-title":"Virtual staining for histology by deep learning","volume":"42","author":"Latonen","year":"2024","journal-title":"Trends Biotechnol"},{"key":"B18","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1038\/s41746-023-00901-z","article-title":"Predicting HPV association using deep learning and regular H&E stains allows granular stratification of oropharyngeal cancer patients","volume":"6","author":"Klein","year":"2023","journal-title":"npj Digit Med"},{"key":"B19","doi-asserted-by":"publisher","first-page":"100354","DOI":"10.1016\/j.jpi.2023.100354","article-title":"A deep learning model to predict Ki-67 positivity in oral squamous cell carcinoma","volume":"15","author":"Martino","year":"2024","journal-title":"J Pathol Inform"},{"key":"B20","doi-asserted-by":"publisher","first-page":"102420","DOI":"10.1016\/j.artmed.2022.102420","article-title":"CycleGAN for virtual stain transfer: Is seeing really believing?","volume":"133","author":"Vasiljevi\u0107","year":"2022","journal-title":"Artif Intell Med"},{"key":"B21","author":"Chen","year":""},{"key":"B22","doi-asserted-by":"publisher","first-page":"4369","DOI":"10.1038\/s41467-024-48705-3","article-title":"Artificial intelligence enables precision diagnosis of cervical cytology grades and cervical cancer","volume":"15","author":"Wang","year":"2024","journal-title":"Nat Commun"},{"key":"B23","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1038\/s41596-024-01047-2","article-title":"From whole-slide image to biomarker prediction: end-to-end weakly supervised deep learning in computational pathology","volume":"20","author":"El Nahhas","year":"2025","journal-title":"Nat Protoc"},{"key":"B24","doi-asserted-by":"publisher","first-page":"1305","DOI":"10.1038\/s43018-024-00793-2","article-title":"A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics","volume":"5","author":"Hoang","year":"2024","journal-title":"Nat Cancer"},{"key":"B25","author":"Kilim","year":""},{"key":"B26","author":"Gao","year":""},{"key":"B27","author":"Rao","year":""},{"key":"B28","first-page":"1","article-title":"A unified arbitrary style transfer framework via adaptive contrastive learning","volume":"42","author":"Zhang","year":"2023","journal-title":"ACM Trans Graph"},{"key":"B29","doi-asserted-by":"publisher","first-page":"466","DOI":"10.1038\/s41551-019-0362-y","article-title":"Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning","volume":"3","author":"Rivenson","year":"2019","journal-title":"Nat Biomed Eng"},{"key":"B30","author":"Yata","year":""},{"key":"B31","author":"Choi","year":""},{"key":"B32","author":"Baek","year":""},{"key":"B33","author":"Scalbert","year":""},{"key":"B34","author":"Parmar","year":""},{"key":"B35","author":"Zhu","year":""},{"key":"B36","doi-asserted-by":"publisher","first-page":"1578","DOI":"10.1109\/TPAMI.2024.3498003","article-title":"Diffi2i: efficient diffusion model for image-to-image translation","volume":"47","author":"Xia","year":"2024","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"B37","author":"Zhang","year":""},{"key":"B38","author":"Dubey","year":""},{"key":"B39","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2025.3588196","article-title":"Mitigating data bias in healthcare AI with self-supervised standardization","author":"Lan","year":"2025","journal-title":"IEEE J Biomed Health Inform"},{"key":"B40","doi-asserted-by":"publisher","first-page":"384","DOI":"10.1038\/s41746-025-01741-9","article-title":"H&E to IHC virtual staining methods in breast cancer: an overview and benchmarking","volume":"8","author":"Kl\u00f6ckner","year":"2025","journal-title":"npj Digit Med"},{"key":"B41","doi-asserted-by":"publisher","first-page":"115390","DOI":"10.1016\/j.ejca.2025.115390","article-title":"Artificial intelligence-based virtual staining platform for identifying tumor-associated macrophages from hematoxylin and eosin-stained images","volume":"220","author":"Aggarwal","year":"2025","journal-title":"Eur J Cancer"},{"key":"B42","author":"Yan","year":""},{"key":"B43","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2024.3525299","article-title":"Supervised information mining from weakly paired images for breast IHC virtual staining","author":"Guan","year":"2025","journal-title":"IEEE Trans Med Imaging"},{"key":"B44","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1038\/s41377-024-01554-7","article-title":"Deep learning-based virtual staining, segmentation, and classification in label-free photoacoustic histology of human specimens","volume":"13","author":"Yoon","year":"2024","journal-title":"Light Sci Appl"},{"key":"B45","doi-asserted-by":"publisher","first-page":"688","DOI":"10.3390\/s26020688","article-title":"NTFold: structure-sensing nucleotide attention learning for RNA secondary structure prediction","volume":"26","author":"Jin","year":"2026","journal-title":"Sensors"},{"key":"B46","doi-asserted-by":"publisher","first-page":"1038","DOI":"10.1109\/TETCI.2025.3622647","article-title":"Deep neural networks internal representation via neuron community exploration","volume":"10","author":"Lan","year":"2025","journal-title":"IEEE Trans Emerg Top Comput Intell"},{"key":"B47","author":"Zhang","year":""},{"key":"B48","author":"Jiang","year":""},{"key":"B49","author":"Yang","year":""},{"key":"B50","author":"Xiong","year":""}],"container-title":["Frontiers in Medical Technology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmedt.2026.1783365\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T12:45:56Z","timestamp":1780404356000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmedt.2026.1783365\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,29]]},"references-count":50,"alternative-id":["10.3389\/fmedt.2026.1783365"],"URL":"https:\/\/doi.org\/10.3389\/fmedt.2026.1783365","relation":{},"ISSN":["2673-3129"],"issn-type":[{"value":"2673-3129","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,29]]},"article-number":"1783365"}}