The Efficacy of Real-time Computer-aided Detection of Colonic Neoplasia in Community Practice: A Pragmatic Randomized Controlled Trial

Nikhil R Thiruvengadam; Pejman Solaimani; Manish Shrestha; Seth Buller; Rachel Carson; Breanna Reyes-Garcia; Ronaldo D Gnass; Bing Wang; Natalie Albasha; Paul Leonor; Monica Saumoy; Raul Coimbra; Arnold Tabuenca; Wichit Srikureja; Steve Serrao

doi:10.1016/j.cgh.2024.02.021

The Efficacy of Real-time Computer-aided Detection of Colonic Neoplasia in Community Practice: A Pragmatic Randomized Controlled Trial

Clin Gastroenterol Hepatol. 2024 Mar 2:S1542-3565(24)00225-8. doi: 10.1016/j.cgh.2024.02.021. Online ahead of print.

Authors

Affiliations

¹ Division of Gastroenterology and Hepatology, Riverside University Health System, Moreno Valley, California; Division of Gastroenterology and Hepatology, Loma Linda University Health, Loma Linda, California. Electronic address: nikhilt88@hotmail.com.
² Division of Gastroenterology and Hepatology, Riverside University Health System, Moreno Valley, California; Division of Gastroenterology and Hepatology, Loma Linda University Health, Loma Linda, California.
³ Loma Linda University School of Medicine, Loma Linda, California.
⁴ Department of Pathology, Riverside University Health System, Moreno Valley, California.
⁵ Department of Pathology, Loma Linda University School of Medicine, Loma Linda, California.
⁶ University of California Riverside School of Medicine, Riverside, California; Department of Medicine, Scripps Green Hospital, La Jolla, California.
⁷ Center for Digestive Health, Penn Medicine Princeton Medical Center, Plainsboro, New Jersey.
⁸ Comparative Effectiveness and Clinical Outcomes Research Center, Riverside University Health System, Moreno Valley, California; Department of Surgery, Riverside University Health System, Moreno Valley, California.
⁹ Department of Surgery, Riverside University Health System, Moreno Valley, California; Department of Surgery, University of California Riverside School of Medicine, Riverside, California.

PMID: 38437999
DOI: 10.1016/j.cgh.2024.02.021

Abstract

Background & aims: The use of computer-aided detection (CADe) has increased the adenoma detection rates (ADRs) during colorectal cancer (CRC) screening/surveillance in randomized controlled trials (RCTs) but has not shown benefit in real-world implementation studies. We performed a single-center pragmatic RCT to evaluate the impact of real-time CADe on ADRs in colonoscopy performed by community gastroenterologists.

Methods: We enrolled 1100 patients undergoing colonoscopy for CRC screening, surveillance, positive fecal-immunohistochemical tests, and diagnostic indications at one community-based center from September 2022 to March 2023. Patients were randomly assigned (1:1) to traditional colonoscopy or real-time CADe. Blinded pathologists analyzed histopathologic findings. The primary outcome was ADR (the percentage of patients with at least 1 histologically proven adenoma or carcinoma). Secondary outcomes were adenomas detected per colonoscopy (APC), sessile-serrated lesion detection rate, and non-neoplastic resection rate.

Results: The median age was 55.5 years (interquartile range, 50-62 years), 61% were female, 72.7% were of Hispanic ethnicity, and 9.1% had inadequate bowel preparation. The ADR for the CADe group was significantly higher than the traditional colonoscopy group (42.5% vs 34.4%; P = .005). The mean APC was significantly higher in the CADe group compared with the traditional colonoscopy group (0.89 ± 1.46 vs 0.60 ± 1.12; P < .001). The improvement in adenoma detection was driven by increased detection of <5 mm adenomas. CADe had a higher sessile-serrated lesion detection rate than traditional colonoscopy (4.7% vs 2.0%; P = .01). The improvement in ADR with CADe was significantly higher in the first half of the study (47.2% vs 33.7%; P = .002) compared with the second half (38.7% vs 34.9%; P = .33).

Conclusions: In a single-center pragmatic RCT, real-time CADe modestly improved ADR and APC in average-detector community endoscopists. (ClinicalTrials.gov number, NCT05963724).

Keywords: Adenoma Detection Rate; Artificial Intelligence; Computer-aided Detection; Screening Colonoscopy.

Associated data

ClinicalTrials.gov/NCT05963724