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Improvement in adenoma detection using a novel artificial intelligence-aided polyp detection device
Background and study aims Detecting colorectal neoplasia is the goal of high-quality screening and surveillance colonoscopy, as reflected by high adenoma detection rate (ADR) and adenomas per colonoscopy (APC). The aim of our study was to evaluate the performance of a novel artificial intelligence...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Georg Thieme Verlag KG
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7857961/ https://www.ncbi.nlm.nih.gov/pubmed/33553591 http://dx.doi.org/10.1055/a-1321-1317 |
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author | Shaukat, Aasma Colucci, Daniel Erisson, Lavi Phillips, Sloane Ng, Jonathan Iglesias, Juan Eugenio Saltzman, John R. Somers, Samuel Brugge, William |
author_facet | Shaukat, Aasma Colucci, Daniel Erisson, Lavi Phillips, Sloane Ng, Jonathan Iglesias, Juan Eugenio Saltzman, John R. Somers, Samuel Brugge, William |
author_sort | Shaukat, Aasma |
collection | PubMed |
description | Background and study aims Detecting colorectal neoplasia is the goal of high-quality screening and surveillance colonoscopy, as reflected by high adenoma detection rate (ADR) and adenomas per colonoscopy (APC). The aim of our study was to evaluate the performance of a novel artificial intelligence (AI)-aided polyp detection device, Skout, with the primary endpoints of ADR and APC in routine colonoscopy. Patients and methods We compared ADR and APC in a cohort of outpatients undergoing routine high-resolution colonoscopy with and without the use of a real-time, AI-aided polyp detection device. Patients undergoing colonoscopy with Skout were enrolled in a single-arm, unblinded, prospective trial and the results were compared with a historical cohort. All resected polyps were examined histologically. Results Eighty-three patients undergoing screening and surveillance colonoscopy at an outpatient endoscopy center were enrolled and outcomes compared with 283 historical control patients. Overall, ADR with and without Skout was 54.2 % and 40.6 % respectively ( P = 0.028) and 53.6 % and 30.8 %, respectively, in screening exams ( P = 0.024). Overall, APC rate with and without Skout was 1.46 and 1.01, respectively, ( P = 0.104) and 1.18 and 0.50, respectively, in screening exams ( P = 0.002). Overall, true histology rate (THR) with and without Skout was 73.8 % and 78.4 %, respectively, ( P = 0.463) and 75.0 % and 71.0 %, respectively, in screening exams ( P = 0.731). Conclusion We have demonstrated that our novel AI-aided polyp detection device increased the ADR in a cohort of patients undergoing screening and surveillance colonoscopy without a significant concomitant increase in hyperplastic polyp resection. AI-aided colonoscopy has the potential for improving the outcomes of patients undergoing colonoscopy. |
format | Online Article Text |
id | pubmed-7857961 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Georg Thieme Verlag KG |
record_format | MEDLINE/PubMed |
spelling | pubmed-78579612021-02-05 Improvement in adenoma detection using a novel artificial intelligence-aided polyp detection device Shaukat, Aasma Colucci, Daniel Erisson, Lavi Phillips, Sloane Ng, Jonathan Iglesias, Juan Eugenio Saltzman, John R. Somers, Samuel Brugge, William Endosc Int Open Background and study aims Detecting colorectal neoplasia is the goal of high-quality screening and surveillance colonoscopy, as reflected by high adenoma detection rate (ADR) and adenomas per colonoscopy (APC). The aim of our study was to evaluate the performance of a novel artificial intelligence (AI)-aided polyp detection device, Skout, with the primary endpoints of ADR and APC in routine colonoscopy. Patients and methods We compared ADR and APC in a cohort of outpatients undergoing routine high-resolution colonoscopy with and without the use of a real-time, AI-aided polyp detection device. Patients undergoing colonoscopy with Skout were enrolled in a single-arm, unblinded, prospective trial and the results were compared with a historical cohort. All resected polyps were examined histologically. Results Eighty-three patients undergoing screening and surveillance colonoscopy at an outpatient endoscopy center were enrolled and outcomes compared with 283 historical control patients. Overall, ADR with and without Skout was 54.2 % and 40.6 % respectively ( P = 0.028) and 53.6 % and 30.8 %, respectively, in screening exams ( P = 0.024). Overall, APC rate with and without Skout was 1.46 and 1.01, respectively, ( P = 0.104) and 1.18 and 0.50, respectively, in screening exams ( P = 0.002). Overall, true histology rate (THR) with and without Skout was 73.8 % and 78.4 %, respectively, ( P = 0.463) and 75.0 % and 71.0 %, respectively, in screening exams ( P = 0.731). Conclusion We have demonstrated that our novel AI-aided polyp detection device increased the ADR in a cohort of patients undergoing screening and surveillance colonoscopy without a significant concomitant increase in hyperplastic polyp resection. AI-aided colonoscopy has the potential for improving the outcomes of patients undergoing colonoscopy. Georg Thieme Verlag KG 2021-02 2021-02-03 /pmc/articles/PMC7857961/ /pubmed/33553591 http://dx.doi.org/10.1055/a-1321-1317 Text en The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commecial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/) https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited. |
spellingShingle | Shaukat, Aasma Colucci, Daniel Erisson, Lavi Phillips, Sloane Ng, Jonathan Iglesias, Juan Eugenio Saltzman, John R. Somers, Samuel Brugge, William Improvement in adenoma detection using a novel artificial intelligence-aided polyp detection device |
title | Improvement in adenoma detection using a novel artificial intelligence-aided polyp detection device |
title_full | Improvement in adenoma detection using a novel artificial intelligence-aided polyp detection device |
title_fullStr | Improvement in adenoma detection using a novel artificial intelligence-aided polyp detection device |
title_full_unstemmed | Improvement in adenoma detection using a novel artificial intelligence-aided polyp detection device |
title_short | Improvement in adenoma detection using a novel artificial intelligence-aided polyp detection device |
title_sort | improvement in adenoma detection using a novel artificial intelligence-aided polyp detection device |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7857961/ https://www.ncbi.nlm.nih.gov/pubmed/33553591 http://dx.doi.org/10.1055/a-1321-1317 |
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