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Computer-Aided Detection Colonoscopy for Surveillance in IBD Patients: Insights from a Single-Center Experience
Adam Goldman1,2,3, Levy Idan2,3, Shomron Ben-Horin2,3
1Department of Epidemiology and Preventive Medicine, School of Public Health, School of Medicine, Tel Aviv University, Tel Aviv, Israel.
Insights
Computer-aided detection (CADe) did not improve neoplasm detection during surveillance colonoscopies for patients with inflammatory bowel disease (IBD). The study found a nonsignificant decline in adenoma detection rates after CADe implementation.
Area of Science:
- Gastroenterology
- Endoscopy
- Artificial Intelligence in Medicine
Background:
- Surveillance colonoscopies are crucial for managing patients with inflammatory bowel disease (IBD).
- The efficacy of computer-aided detection (CADe) systems in enhancing colonoscopy performance for IBD patients remains unclear.
- Establishing the real-world impact of CADe is essential for optimizing IBD surveillance protocols.
Purpose of the Study:
- To evaluate the real-world effectiveness of computer-aided detection (CADe) in improving surveillance colonoscopy outcomes for patients with inflammatory bowel disease (IBD).
- To compare the adenoma detection rate (ADR) before and after the implementation of CADe in an IBD patient cohort.
Main Methods:
- A retrospective, single-center study analyzed surveillance colonoscopies in IBD patients.
- Colonoscopies with adequate preparation and cecal intubation were included.
- Adenoma detection rates (ADR) were compared between pre-CADe (June 2020-June 2021) and post-CADe (July 2021-September 2022) periods.
Main Results:
- The study included 225 procedures pre-CADe and 750 post-CADe.
- Neoplastic lesions or colorectal cancer were detected in 5.8% pre-CADe vs. 3.6% post-CADe.
- The collective adenoma detection rate (ADR) decreased nonsignificantly from 5.2% to 3.8% (P=.315) after CADe implementation.
Conclusions:
- Computer-aided detection (CADe) did not enhance neoplasm detection in IBD surveillance colonoscopies.
- A nonsignificant decline in ADR was observed post-CADe implementation.
- Findings suggest a need for IBD-specific CADe systems and better physician-AI interaction strategies.
Objectives:
The real-world efficacy of computer-aided detection (CADe) in improving surveillance colonoscopy performance for patients with inflammatory bowel disease (IBD) has not been established.
Methods:
A retrospective, single-center study of surveillance colonoscopies in patients with IBD. Only colonoscopies indicated for surveillance, with adequate preparation and documented cecal intubation, were included. The study compared the collective adenoma detection rate (ADR) between the periods before (pre-CADe) (June 2020 to June 2021) and after (July 2021 to September 2022) the introduction of the CADe in all endoscopy units. An adjusted ADR was calculated using a multivariable logistic regression model.
Results:
The study included 225 eligible colonoscopies performed during the pre-CADe period and 750 during the CADe period. Neoplastic lesions or colorectal cancer were detected in 13 (5.8%) of 225 procedures in the pre-CADe period and 27 (3.6%) of 750 procedures during the CADe period. The collective ADR was 5.2% (95% confidence interval, 3.9-6.6) in the pre-CADe period and 3.8% (95% confidence interval, 1.1-6.5) -following CADe implementation (P = .315). Subgroup analyses stratified by endoscopist experience, IBD type, and procedure timing (daytime vs after hours) corroborated a similar nonsignificant declining trend in ADR after CADe introduction.
Conclusions:
In a real-world, single-center experience, the introduction of CADe did not improve neoplasms detection in patients with IBD and was associated with a nonsignificant decline in ADR. These findings call into question the utility of generic CADe systems in IBD surveillance and emphasize the need to foster IBD-specific CADe systems, as well as addressing challenges arising from physician-artificial intelligence interactions.
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