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CC BY-NC-ND 4.0 · Endosc Int Open 2021; 09(02): E263-E270
DOI: 10.1055/a-1321-1317
Original article

Improvement in adenoma detection using a novel artificial intelligence-aided polyp detection device

Aasma Shaukat
1   University of Minnesota – GI, Minneapolis, Minnesota, United States
,
Daniel Colucci
2   Iterative Scopes, Cambridge, Massachusetts, United States
,
Lavi Erisson
2   Iterative Scopes, Cambridge, Massachusetts, United States
,
Sloane Phillips
2   Iterative Scopes, Cambridge, Massachusetts, United States
,
Jonathan Ng
2   Iterative Scopes, Cambridge, Massachusetts, United States
,
Juan Eugenio Iglesias
2   Iterative Scopes, Cambridge, Massachusetts, United States
3   University College London – European Research Council, London, United Kingdom
4   Massachusetts General Hospital – Martinos Center for Biological Imaging, Boston, Massachusetts, United States
5   Massachusetts Institute of Technology – MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, Massachusetts, United States
,
John R. Saltzman
6   Brigham and Women’s Hospital – Gastroenterology, Boston, Massachusetts, United States
,
Samuel Somers
7   Concord Hospital – Gastroenterology, Concord, New Hampshire, United States
,
William Brugge
8   Mount Auburn Hospital – Gastroenterology, Cambridge, Massachusetts, United States
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Abstract

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.



Publication History

Received: 04 August 2020

Accepted: 20 October 2020

Article published online:
03 February 2021

© 2021. 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/)

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