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

Author:

Shaukat Aasma1,Colucci Daniel2,Erisson Lavi2,Phillips Sloane2,Ng Jonathan2,Iglesias Juan Eugenio2345,Saltzman John R.6,Somers Samuel7,Brugge William8

Affiliation:

1. University of Minnesota – GI, Minneapolis, Minnesota, United States

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

6. Brigham and Women’s Hospital – Gastroenterology, Boston, Massachusetts, United States

7. Concord Hospital – Gastroenterology, Concord, New Hampshire, United States

8. Mount Auburn Hospital – Gastroenterology, Cambridge, Massachusetts, United States

Abstract

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.

Publisher

Georg Thieme Verlag KG

Subject

Gastroenterology,Medicine (miscellaneous)

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