{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T04:10:35Z","timestamp":1792037435489,"version":"4.4.0"},"reference-count":30,"publisher":"Georg Thieme Verlag KG","issue":"04","funder":[{"name":"the Fundamental Research Funds for the Central Universities","award":["2042022kf1099"],"award-info":[{"award-number":["2042022kf1099"]}]},{"name":"National Natural Science Foundation of China-Youth Science Fund Project","award":["82202257"],"award-info":[{"award-number":["82202257"]}]},{"name":"Innovation Team Project of Health Commission of Hubei Province","award":["WJ2021C003"],"award-info":[{"award-number":["WJ2021C003"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Endoscopy"],"published-print":{"date-parts":[[2024,4]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>\n            Background The choice of polypectomy device and surveillance intervals for colorectal polyps are primarily decided by polyp size. We developed a deep learning-based system (ENDOANGEL-CPS) to estimate colorectal polyp size in real time.<\/jats:p><jats:p>\n            Methods ENDOANGEL-CPS calculates polyp size by estimating the distance from the endoscope lens to the polyp using the parameters of the lens. The depth estimator network was developed on 7297 images from five virtually produced colon videos and tested on 730 images from seven virtual colon videos. The performance of the system was first evaluated in nine videos of a simulated colon with polyps attached, then tested in 157 real-world prospective videos from three hospitals, with the outcomes compared with that of nine endoscopists over 69 videos. Inappropriate surveillance recommendations caused by incorrect estimation of polyp size were also analyzed.<\/jats:p><jats:p>\n            Results The relative error of depth estimation was 11.3% (SD\n      6.0%) in successive virtual colon images. The concordance correlation coefficients (CCCs)\n      between system estimation and ground truth were 0.89 and 0.93 in images of a simulated colon\n      and multicenter videos of 157 polyps. The mean CCC of ENDOANGEL-CPS surpassed all endoscopists\n      (0.89 vs. 0.41 [SD 0.29]; P&lt;0.001). The relative accuracy of\n      ENDOANGEL-CPS was significantly higher than that of endoscopists (89.9% vs. 54.7%; P&lt;0.001). Regarding inappropriate surveillance recommendations, the\n      system's error rate is also lower than that of endoscopists (1.5% vs. 16.6%; P&lt;0.001).<\/jats:p><jats:p>\n            Conclusions ENDOANGEL-CPS could potentially improve the accuracy of colorectal polyp size measurements and size-based surveillance intervals.<\/jats:p>","DOI":"10.1055\/a-2189-7036","type":"journal-article","created":{"date-parts":[[2023,10,12]],"date-time":"2023-10-12T23:34:12Z","timestamp":1697153652000},"page":"260-270","source":"Crossref","is-referenced-by-count":40,"title":["A real-time deep learning-based system for colorectal polyp size estimation by white-light endoscopy: development and multicenter prospective validation"],"prefix":"10.1055","volume":"56","clinical-trial-number":[{"clinical-trial-number":"chictr2200059453","registry":"10.18810\/chictr"}],"author":[{"given":"Jing","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China"},{"name":"Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China"},{"name":"Hubei Key Laboratory of Digestive System, Renmin Hospital of Wuhan University, Wuhan, China"},{"name":"Engineering Research Center for Artificial Intelligence Endoscopy Interventional Treatment of Hubei Province, Renmin Hospital of Wuhan University, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Li","sequence":"first","affiliation":[{"name":"Department of Endoscopy, Eighth Hospital of Wuhan, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuyu","family":"Li","sequence":"first","affiliation":[{"name":"Department of Endoscopy, Third People\u2018s Hospital of Hubei Province, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Honggang","family":"Yu","sequence":"first","affiliation":[{"name":"Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China"},{"name":"Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China"},{"name":"Hubei Key Laboratory of Digestive System, Renmin Hospital of Wuhan University, Wuhan, China"},{"name":"Engineering Research Center for Artificial Intelligence Endoscopy Interventional Treatment of Hubei Province, Renmin Hospital of Wuhan University, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Boru","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China"},{"name":"Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan 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Renmin Hospital of Wuhan University, Wuhan, China"},{"name":"Hubei Key Laboratory of Digestive System, Renmin Hospital of Wuhan University, Wuhan, China"},{"name":"Engineering Research Center for Artificial Intelligence Endoscopy Interventional Treatment of Hubei Province, Renmin Hospital of Wuhan University, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lianlian","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China"},{"name":"Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China"},{"name":"Hubei Key Laboratory of Digestive System, Renmin Hospital of Wuhan University, Wuhan, China"},{"name":"Engineering Research Center for Artificial Intelligence Endoscopy Interventional Treatment of Hubei Province, Renmin Hospital of Wuhan University, Wuhan, 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