{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,30]],"date-time":"2026-05-30T15:02:03Z","timestamp":1780153323325,"version":"3.54.0"},"reference-count":45,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T00:00:00Z","timestamp":1778544000000},"content-version":"vor","delay-in-days":112,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Noncommunicable Chronic Diseases-National Science and Technology Major Project","award":["2023ZD0501600"],"award-info":[{"award-number":["2023ZD0501600"]}]},{"name":"Shanghai Eastern Talent Elite Program","award":["BJKJ2025002"],"award-info":[{"award-number":["BJKJ2025002"]}]},{"name":"Changhai hospital special foundation for clinical research","award":["2024LYB05"],"award-info":[{"award-number":["2024LYB05"]}]},{"name":"China National Postdoctoral Program for Innovative Talents","award":["BX20230482"],"award-info":[{"award-number":["BX20230482"]}]},{"name":"Natural Science Foundation of Shanghai","award":["23ZR1478700"],"award-info":[{"award-number":["23ZR1478700"]}]},{"name":"Shanghai Sailing Program","award":["23YF1458600"],"award-info":[{"award-number":["23YF1458600"]}]},{"name":"Chenguang Program of Shanghai Education Development Foundation and Shanghai Municipal Education Commission","award":["22CGA42"],"award-info":[{"award-number":["22CGA42"]}]},{"name":"Special Clinical Research on Health Industry of Shanghai Municipal Health Commission","award":["20244Y0231"],"award-info":[{"award-number":["20244Y0231"]}]},{"name":"Shanghai Eastern Talent Youth Program","award":["QNWS2024108"],"award-info":[{"award-number":["QNWS2024108"]}]},{"name":"Changfeng Guhai Project of Changhai Hospital"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,20]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Polyp size measurement is critical in determining the resection method and surveillance interval; however, the accuracy and reliability of existing measurement methods are suboptimal. We establish a computer-aided measuring (CAM) system to automatically and accurately measure colorectal polyp size in real time.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a hybrid retrospective and prospective preclinical study to develop models retrospectively and validate them prospectively. The CAM system includes two deep learning models: a polyp detection model trained on 15,620 images and tested on 4,438 images and a depth-map prediction model trained on 18,500 red\u2013green\u2013blue depth-map pairs and tested on 1,500 pairs. A digitized three-dimensional model development setting (3D-MDS) was used to validate the CAM system; here, 3,750 red\u2013green\u2013blue images from 15 digital virtual 3D polyps were generated for size measurements. A high-simulation colon\/polyp model was used to test real-time polyp size measurement performance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In the 3D-MDS, the CAM system had an average relative error of 7.9% (standard deviation 4.19%) for the depth-map prediction model and a mean percentage error of 7.9% (interquartile range [IQR] 4.6%\u201310.4%) for the polyp size measurement. In the high-simulation colon\/polyp model, the CAM system\u2019s depth distance measurement had a percentage error of 12.0% (IQR 5.5%\u201315.7%). For the polyp size measurement, the highest accuracy and reliability were achieved at the medium-depth distance and the position within the center field-of-view, with percentage errors of 4.1% (IQR 2.6%\u20134.5%) and 3.3% (IQR 1.8%\u20133.5%) for the first and second measurements, respectively, and an intraclass correlation coefficient of 0.999.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The CAM system showed excellent accuracy and reliability in diverse testing scenarios; here, the medium-depth distance (15\u201335\u2009mm) and the position within the center field-of-view was likely the optimal measurement location.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/gastro\/goag041","type":"journal-article","created":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T11:22:11Z","timestamp":1776684131000},"source":"Crossref","is-referenced-by-count":0,"title":["Development and validation of a real-time computer-aided measuring system for colorectal polyp size (with video)"],"prefix":"10.1093","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-7754-4508","authenticated-orcid":false,"given":"Cheng-Long","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Gastroenterology, Changhai Hospital, Naval Medical University , 168 Changhai Road , Shanghai 200433,","place":["P. 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