{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T04:39:00Z","timestamp":1773117540374,"version":"3.50.1"},"reference-count":45,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2025,8,3]],"date-time":"2025-08-03T00:00:00Z","timestamp":1754179200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"abstract":"<jats:p>Background\/Objectives: Colorectal anastomotic leak (CAL) is one of the most severe postoperative complications in colorectal surgery, impacting patient morbidity and mortality. Current risk assessment methods rely on clinical and intraoperative factors, but no real-time predictive tool exists. This study aimed to develop an artificial intelligence model based on intraoperative laparoscopic recording of the anastomosis for CAL prediction. Methods: A convolutional neural network (CNN) was trained with annotated frames from colorectal surgery videos across three international high-volume centers (Instituto Portugu\u00eas de Oncologia de Lisboa, Hospital das Cl\u00ednicas de Ribeir\u00e3o Preto, and Royal Liverpool University Hospital). The dataset included a total of 5356 frames from 26 patients, 2007 with CAL and 3349 showing normal anastomosis. Four CNN architectures (EfficientNetB0, EfficientNetB7, ResNet50, and MobileNetV2) were tested. The models\u2019 performance was evaluated using their sensitivity, specificity, accuracy, and area under the receiver operating characteristic (AUROC) curve. Heatmaps were generated to identify key image regions influencing predictions. Results: The best-performing model achieved an accuracy of 99.6%, AUROC of 99.6%, sensitivity of 99.2%, specificity of 100.0%, PPV of 100.0%, and NPV of 98.9%. The model reliably identified CAL-positive frames and provided visual explanations through heatmaps. Conclusions: To our knowledge, this is the first AI model developed to predict CAL using intraoperative video analysis. Its accuracy suggests the potential to redefine surgical decision-making by providing real-time risk assessment. Further refinement with a larger dataset and diverse surgical techniques could enable intraoperative interventions to prevent CAL before it occurs, marking a paradigm shift in colorectal surgery.<\/jats:p>","DOI":"10.3390\/jcm14155462","type":"journal-article","created":{"date-parts":[[2025,8,5]],"date-time":"2025-08-05T08:46:55Z","timestamp":1754383615000},"page":"5462","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A Novel Deep Learning Model for Predicting Colorectal Anastomotic Leakage: A Pioneer Multicenter Transatlantic Study"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0340-0830","authenticated-orcid":false,"given":"Miguel","family":"Mascarenhas","sequence":"first","affiliation":[{"name":"Precision Medicine Unit, Department of Gastroenterology, Unidade Local de Sa\u00fade S\u00e3o Jo\u00e3o, 4200-319 Porto, Portugal"},{"name":"WGO Gastroenterology and Hepatology Training Center, 4200-427 Porto, Portugal"},{"name":"Faculty of Medicine, University of Porto, 4200-427 Porto, Portugal"},{"name":"CINTESIS-RISE, Department of Community Medicine, Information and Health Decision Sciences (MEDCIDS), Faculty of Medicine, University of Porto, 4200-427 Porto, Portugal"},{"name":"DigestAID, Digestive Artificial Intelligence Development, 4200-135 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5890-7049","authenticated-orcid":false,"given":"Francisco","family":"Mendes","sequence":"additional","affiliation":[{"name":"Precision Medicine Unit, Department of Gastroenterology, Unidade Local de Sa\u00fade S\u00e3o Jo\u00e3o, 4200-319 Porto, Portugal"},{"name":"WGO Gastroenterology and Hepatology Training Center, 4200-427 Porto, Portugal"},{"name":"Faculty of Medicine, University of Porto, 4200-427 Porto, Portugal"},{"name":"DigestAID, Digestive Artificial Intelligence Development, 4200-135 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9003-3871","authenticated-orcid":false,"given":"Filipa","family":"Fonseca","sequence":"additional","affiliation":[{"name":"Instituto Portugu\u00eas de Oncologia de Lisboa, 1099-023 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-0729-7008","authenticated-orcid":false,"given":"Eduardo","family":"Carvalho","sequence":"additional","affiliation":[{"name":"INEGI\u2014Instituto de Ci\u00eancia e Inova\u00e7\u00e3o em Engenharia Mec\u00e2nica e Engenharia Industrial, 4200-465 Porto, Portugal"},{"name":"Faculty of Engineering, University of Porto, 4200-427 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9676-6128","authenticated-orcid":false,"given":"Andre","family":"Santos","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, University of Porto, 4200-427 Porto, Portugal"},{"name":"DigestAID, Digestive Artificial Intelligence Development, 4200-135 Porto, Portugal"}]},{"given":"Daniela","family":"Cavadas","sequence":"additional","affiliation":[{"name":"Instituto Portugu\u00eas de Oncologia de Lisboa, 1099-023 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-5001-5539","authenticated-orcid":false,"given":"Guilherme","family":"Barbosa","sequence":"additional","affiliation":[{"name":"INEGI\u2014Instituto de Ci\u00eancia e Inova\u00e7\u00e3o em Engenharia Mec\u00e2nica e Engenharia Industrial, 4200-465 Porto, Portugal"},{"name":"Faculty of Engineering, University of Porto, 4200-427 Porto, Portugal"}]},{"given":"Antonio","family":"Pinto da Costa","sequence":"additional","affiliation":[{"name":"DigestAID, Digestive Artificial Intelligence Development, 4200-135 Porto, Portugal"},{"name":"Hospital Universitario Puerta de Hierro Majadahonda, 28222 Madrid, Spain"}]},{"given":"Miguel","family":"Martins","sequence":"additional","affiliation":[{"name":"Precision Medicine Unit, Department of Gastroenterology, Unidade Local de Sa\u00fade S\u00e3o Jo\u00e3o, 4200-319 Porto, Portugal"},{"name":"WGO Gastroenterology and Hepatology Training Center, 4200-427 Porto, Portugal"},{"name":"Faculty of Medicine, University of Porto, 4200-427 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-7857-2415","authenticated-orcid":false,"given":"Abdullah","family":"Bunaiyan","sequence":"additional","affiliation":[{"name":"Royal Liverpool University Hospital, Liverpool L7 8YE, UK"}]},{"given":"Ma\u00edsa","family":"Vasconcelos","sequence":"additional","affiliation":[{"name":"Hospital das Clinicas da Faculdade de Medicina da Universidade de S\u00e3o Paulo, Cl\u00ednica de Ribeirao Preto, Ribeirao 05403-010, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4440-2023","authenticated-orcid":false,"given":"Marley Ribeiro","family":"Feitosa","sequence":"additional","affiliation":[{"name":"Hospital das Clinicas da Faculdade de Medicina da Universidade de S\u00e3o Paulo, Cl\u00ednica de Ribeirao Preto, Ribeirao 05403-010, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2743-7918","authenticated-orcid":false,"given":"Shay","family":"Willoughby","sequence":"additional","affiliation":[{"name":"Royal Liverpool University Hospital, Liverpool L7 8YE, UK"}]},{"given":"Shakil","family":"Ahmed","sequence":"additional","affiliation":[{"name":"Royal Liverpool University Hospital, Liverpool L7 8YE, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0402-2285","authenticated-orcid":false,"given":"Muhammad Ahsan","family":"Javed","sequence":"additional","affiliation":[{"name":"Royal Liverpool University Hospital, Liverpool L7 8YE, UK"}]},{"given":"Nilza","family":"Rami\u00e3o","sequence":"additional","affiliation":[{"name":"INEGI\u2014Instituto de Ci\u00eancia e Inova\u00e7\u00e3o em Engenharia Mec\u00e2nica e Engenharia Industrial, 4200-465 Porto, Portugal"},{"name":"Faculty of Engineering, University of Porto, 4200-427 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9387-9872","authenticated-orcid":false,"given":"Guilherme","family":"Macedo","sequence":"additional","affiliation":[{"name":"Precision Medicine Unit, Department of Gastroenterology, Unidade Local de Sa\u00fade S\u00e3o Jo\u00e3o, 4200-319 Porto, Portugal"},{"name":"WGO Gastroenterology and Hepatology Training Center, 4200-427 Porto, Portugal"},{"name":"Faculty of Medicine, University of Porto, 4200-427 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4645-1574","authenticated-orcid":false,"given":"Manuel","family":"Limbert","sequence":"additional","affiliation":[{"name":"Instituto Portugu\u00eas de Oncologia de Lisboa, 1099-023 Lisboa, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1097\/01.sla.0000225083.27182.85","article-title":"Anastomotic leaks after intestinal anastomosis: It\u2019s later than you 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