{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T15:52:53Z","timestamp":1787241173165,"version":"build-2736575974"},"reference-count":18,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T00:00:00Z","timestamp":1779926400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T00:00:00Z","timestamp":1779926400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Int J of Urology"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>To evaluate nerve\u2010sparing status objectively using an artificial intelligence method applied to intraoperative images and to determine whether combining this assessment with preserved urethral length improves prediction of urinary continence recovery after robot\u2010assisted radical prostatectomy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We analyzed 195 patients with intraoperative still images from robot\u2010assisted radical prostatectomy performed between May 2020 and 2022. Images were evaluated with a deep learning image classification model that determined whether the neurovascular bundle was preserved. Patients were categorized into two groups: those with both preserved urethral length of at least 26\u2009mm and artificial intelligence\u2013assessed neurovascular bundle preservation, and all other patients. The primary endpoint was time to urinary continence recovery. Kaplan\u2013Meier analysis and Cox proportional hazards models were used.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Artificial intelligence reclassified neurovascular bundle preservation in 60 of 195 patients (30.8%), including 48 cases of surgeon overestimation and 12 of underestimation. Patients who met both criteria had significantly better urinary continence recovery than the other patients, with higher continence rates at 30, 60, 90, and 365\u2009days after surgery on log\u2010rank testing. In multivariable Cox models, the combined factor independently predicted continence recovery at 60, 90, and 365\u2009days, with hazard ratios of 1.99, 1.78, and 1.49 and corresponding 95% confidence intervals of 1.07\u20133.72, 1.07\u20132.95, and 1.09\u20132.04 (\n                      <jats:italic>p<\/jats:italic>\n                      values 0.03, 0.03, and 0.01, respectively).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Objective evaluation of nerve\u2010sparing status using artificial intelligence, when combined with preserved urethral length, improves prediction of early urinary continence recovery after robot\u2010assisted radical prostatectomy and may provide an indicator of surgical quality.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/iju.70514","type":"journal-article","created":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T08:02:55Z","timestamp":1779955375000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Artificial Intelligence\u2013Based Objective Evaluation of Nerve\u2010Sparing Status Combined With Preserved Urethral Length Predicts Urinary Continence Recovery After Robot\u2010Assisted Radical Prostatectomy"],"prefix":"10.1111","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9964-1219","authenticated-orcid":false,"given":"Satoshi","family":"Ando","sequence":"first","affiliation":[{"name":"Department of Urology Jichi Medical University  Tochigi Japan"},{"name":"Reprocare Clinic Otakanomori  Chiba Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8540-1818","authenticated-orcid":false,"given":"Diego Andres","family":"del Aguila Moraga","sequence":"additional","affiliation":[{"name":"Department of Medical Engineering Graduate School of Science and Engineering, Chiba University  Chiba Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hayato","family":"Hoshina","sequence":"additional","affiliation":[{"name":"Department of Urology Jichi Medical University  Tochigi Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5265-5111","authenticated-orcid":false,"given":"Hiroshi","family":"Kawahira","sequence":"additional","affiliation":[{"name":"Medical Simulation Center, Jichi Medical University  Tochigi Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8348-6178","authenticated-orcid":false,"given":"Toshiya","family":"Nakaguchi","sequence":"additional","affiliation":[{"name":"Center for Frontier Medical Engineering, Chiba University  Chiba Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3421-8273","authenticated-orcid":false,"given":"Tetsuya","family":"Fujimura","sequence":"additional","affiliation":[{"name":"Department of Urology Jichi Medical University  Tochigi Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,5,28]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eururo.2023.04.021"},{"key":"e_1_2_11_3_1","article-title":"An In\u2010Depth Look Into the Epidemiological and Etiological Aspects of Prostate Cancer: A Literature Review","volume":"15","author":"Al\u2010Ghazawi M.","year":"2023","journal-title":"Cureus"},{"key":"e_1_2_11_4_1","unstructured":"Cancer Registry and Statistics \u201cCancer Information Service National Cancer Center \u201d(2025)."},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1111\/iju.15388"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/bco2.128"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11548\u2010025\u201003544\u20105"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/s41095-023-0364-2"},{"key":"e_1_2_11_9_1","doi-asserted-by":"crossref","unstructured":"M.Caron H.Touvron I.Misra H.Jegou J.Mairal andP.Bojanowski \u201cEmerging Properties in Self\u2010Supervised Vision Transformers. 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