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Role of Artificial Intelligence in Colonoscopy Detection of Advanced Neoplasias : A Randomized Trial. | LitMetric

Role of Artificial Intelligence in Colonoscopy Detection of Advanced Neoplasias : A Randomized Trial.

Ann Intern Med

Department of Gastroenterology, Hospital General Universitario Dr. Balmis, Servicio de Medicina Digestiva, Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL), Departamento de Medicina Clínica, Universidad Miguel Hernández, Alicante, Spain (R.J.).

Published: September 2023

AI Article Synopsis

  • * Results showed no significant difference in the overall detection rates of advanced colorectal neoplasia between the CAD-assisted group (34.8%) and the control group (34.6%), indicating CAD might not enhance the detection of these lesions.
  • * However, CAD did lead to an increase in detecting specific types of lesions, such as nonpolypoid lesions and proximal adenomas, suggesting it may still have some benefits in certain scenarios, though the high detection rates in controls could affect the findings' applicability.

Article Abstract

Background: The role of computer-aided detection in identifying advanced colorectal neoplasia is unknown.

Objective: To evaluate the contribution of computer-aided detection to colonoscopic detection of advanced colorectal neoplasias as well as adenomas, serrated polyps, and nonpolypoid and right-sided lesions.

Design: Multicenter, parallel, randomized controlled trial. (ClinicalTrials.gov: NCT04673136).

Setting: Spanish colorectal cancer screening program.

Participants: 3213 persons with a positive fecal immunochemical test.

Intervention: Enrollees were randomly assigned to colonoscopy with or without computer-aided detection.

Measurements: Advanced colorectal neoplasia was defined as advanced adenoma and/or advanced serrated polyp.

Results: The 2 comparison groups showed no significant difference in advanced colorectal neoplasia detection rate (34.8% with intervention vs. 34.6% for controls; adjusted risk ratio [aRR], 1.01 [95% CI, 0.92 to 1.10]) or the mean number of advanced colorectal neoplasias detected per colonoscopy (0.54 [SD, 0.95] with intervention vs. 0.52 [SD, 0.95] for controls; adjusted rate ratio, 1.04 [99.9% CI, 0.88 to 1.22]). Adenoma detection rate also did not differ (64.2% with intervention vs. 62.0% for controls; aRR, 1.06 [99.9% CI, 0.91 to 1.23]). Computer-aided detection increased the mean number of nonpolypoid lesions (0.56 [SD, 1.25] vs. 0.47 [SD, 1.18] for controls; adjusted rate ratio, 1.19 [99.9% CI, 1.01 to 1.41]), proximal adenomas (0.94 [SD, 1.62] vs. 0.81 [SD, 1.52] for controls; adjusted rate ratio, 1.17 [99.9% CI, 1.03 to 1.33]), and lesions of 5 mm or smaller (polyps in general and adenomas and serrated lesions in particular) detected per colonoscopy.

Limitations: The high adenoma detection rate in the control group may limit the generalizability of the findings to endoscopists with low detection rates.

Conclusion: Computer-aided detection did not improve colonoscopic identification of advanced colorectal neoplasias.

Primary Funding Source: Medtronic.

Download full-text PDF

Source
http://dx.doi.org/10.7326/M22-2619DOI Listing

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