{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T00:28:30Z","timestamp":1786667310723,"version":"build-2736575974"},"reference-count":19,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,8,13]],"date-time":"2026-08-13T00:00:00Z","timestamp":1786579200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,8,13]],"date-time":"2026-08-13T00:00:00Z","timestamp":1786579200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["bjui-journals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["BJU International"],"abstract":"<jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>To evaluate the feasibility and accuracy of an artificial intelligence (AI) model to assist surgeons through automated real\u2010time detection and segmentation of key anatomical structures during robot\u2010assisted single\u2010port transvesical enucleation of the prostate (STEP).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Patients and Methods<\/jats:title>\n                    <jats:p>This retrospective single\u2010centre study utilised surgical videos from patients undergoing single\u2010port robot\u2010assisted transvesical prostate enucleation performed by a single expert surgeon. Selected frames extracted from these surgical videos were manually annotated to identify anatomical landmarks during the key step of the procedure. The structures annotated were the bladder neck, prostatic adenoma, and the peripheral zone. A convolutional neural network based on the You Only Look Once version 11 architecture was trained using these annotated frames. Model performance was quantitatively assessed through recall, precision, F1\u2010score, Intersection over Union, Dice Similarity Coefficient, and mean average precision (AP). Real\u2010time performance was assessed qualitatively through visual inspection and confirmed quantitatively by measuring frame inference speeds.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The study included 611 annotated frames derived from 37 surgical videos. The model demonstrated strong detection performance, with class\u2010specific F1\u2010scores of 0.88 (adenoma), 0.69 (bladder neck), and 0.70 (peripheral zone). Segmentation accuracy, measured by Dice Similarity Coefficient, resulted in adenoma: 0.86; bladder neck: 0.83; peripheral zone: 0.82. Mean AP across all anatomical classes was 0.43. The model consistently operated at &gt;60\u2009frames\/s, confirming real\u2010time applicability without perceptible lag.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This pilot study demonstrates the potential utility of AI to provide intraoperative anatomical guidance during STEP, establishing a foundation for future clinical integration and performance optimization.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/bju.70424","type":"journal-article","created":{"date-parts":[[2026,8,13]],"date-time":"2026-08-13T23:38:43Z","timestamp":1786664323000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Real\u2010time artificial intelligence\u2010based anatomy recognition in single\u2010port transvesical enucleation of the prostate"],"prefix":"10.1111","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8965-6414","authenticated-orcid":false,"given":"Luca A.","family":"Morgantini","sequence":"first","affiliation":[{"name":"Department of Urology University of Illinois at Chicago  Chicago IL USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laura","family":"Cruciani","sequence":"additional","affiliation":[{"name":"NEAR Lab Politecnico di Milano  Milan Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrea Calzolai","family":"Lettieri","sequence":"additional","affiliation":[{"name":"Department of Urology Humanitas University  Milan Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-5830-0975","authenticated-orcid":false,"given":"Fabio M.","family":"Valenzi","sequence":"additional","affiliation":[{"name":"Department of Urology University of Illinois at Chicago  Chicago IL 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USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giovanni","family":"Lughezzani","sequence":"additional","affiliation":[{"name":"Department of Urology Humanitas University  Milan Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marco","family":"Paciotti","sequence":"additional","affiliation":[{"name":"Department of Urology Humanitas University  Milan Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elena","family":"De Momi","sequence":"additional","affiliation":[{"name":"NEAR Lab Politecnico di Milano  Milan Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicol\u00f2 M.","family":"Buffi","sequence":"additional","affiliation":[{"name":"Department of Urology Humanitas University  Milan Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simone","family":"Crivellaro","sequence":"additional","affiliation":[{"name":"Department of Urology University of Illinois at Chicago  Chicago IL 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