AI Article Synopsis

  • Computer-aided diagnosis (CADx) aims to improve the prediction of polyp histology during colonoscopy, potentially decreasing unnecessary removals of harmless polyps, though its overall benefits and risks remain uncertain.
  • The study sought to evaluate the effectiveness of CADx for diagnosing small rectosigmoid polyps (≤5-mm) by comparing the accuracy of endoscopists' predictions with and without CADx assistance.
  • Analysis of ten studies involving over 3,600 patients indicated that while CADx showed high sensitivity (87.3%) and specificity (88.9%) in identifying neoplastic polyps, there was no significant change in the rate of nonneoplastic polyps predicted to be avoided for removal when CADx

Article Abstract

Background: Computer-aided diagnosis (CADx) allows prediction of polyp histology during colonoscopy, which may reduce unnecessary removal of nonneoplastic polyps. However, the potential benefits and harms of CADx are still unclear.

Purpose: To quantify the benefit and harm of using CADx in colonoscopy for the optical diagnosis of small (≤5-mm) rectosigmoid polyps.

Data Sources: Medline, Embase, and Scopus were searched for articles published before 22 December 2023.

Study Selection: Histologically verified diagnostic accuracy studies that evaluated the real-time performance of physicians in predicting neoplastic change of small rectosigmoid polyps without or with CADx assistance during colonoscopy.

Data Extraction: The clinical benefit and harm were estimated on the basis of accuracy values of the endoscopist before and after CADx assistance. The certainty of evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework. The outcome measure for benefit was the proportion of polyps predicted to be nonneoplastic that would avoid removal with the use of CADx. The outcome measure for harm was the proportion of neoplastic polyps that would be not resected and left in situ due to an incorrect diagnosis with the use of CADx. Histology served as the reference standard for both outcomes.

Data Synthesis: Ten studies, including 3620 patients with 4103 small rectosigmoid polyps, were analyzed. The studies that assessed the performance of CADx alone (9 studies; 3237 polyps) showed a sensitivity of 87.3% (95% CI, 79.2% to 92.5%) and specificity of 88.9% (CI, 81.7% to 93.5%) in predicting neoplastic change. In the studies that compared histology prediction performance before versus after CADx assistance (4 studies; 2503 polyps), there was no difference in the proportion of polyps predicted to be nonneoplastic that would avoid removal (55.4% vs. 58.4%; risk ratio [RR], 1.06 [CI, 0.96 to 1.17]; moderate-certainty evidence) or in the proportion of neoplastic polyps that would be erroneously left in situ (8.2% vs. 7.5%; RR, 0.95 [CI, 0.69 to 1.33]; moderate-certainty evidence).

Limitation: The application of optical diagnosis was only simulated, potentially altering the decision-making process of the operator.

Conclusion: Computer-aided diagnosis provided no incremental benefit or harm in the management of small rectosigmoid polyps during colonoscopy.

Primary Funding Source: European Commission. (PROSPERO: CRD42023402197).

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Source
http://dx.doi.org/10.7326/M23-2865DOI Listing

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