S650 AI-Assisted vs Traditional Colonoscopy in Colorectal Neoplasia Detection: A Systematic Review and Meta-Analysis of RCTs and Observational Studies

Introduction: In the United States, Colorectal cancer (CRC) remains a leading cause of cancer-related mortality. This systematic review and meta-analysis compare AI-assisted colonoscopy (AI-AC) to traditional colonoscopy (TC), integrating both randomized controlled trials (RCTs) and observational studies (OBS) to evaluate AI’s impact not only in controlled research settings but also in clinical practice. Methods: A comprehensive systematic search was conducted on PubMed, Embase, Scopus, and the Cochrane Library to identify RCTs and OBS comparing AI-AC with TC for adenoma and polyp detection till March 2025. Meta-analysis was conducted using RevMan 5.4.1. For dichotomous outcomes, pooled risk ratios (RRs) with 95% confidence intervals (CIs) were calculated using the Mantel-Haenszel method. For continuous outcomes, mean differences (MDs) with 95% CIs were used. Random or fixed-effects models were applied based on heterogeneity, assessed using Higgins I² statistic. Statistical significance was set at P-value < 0.05. The risk of bias was assessed using the RoB 2.0 tool for RCTs and the Newcastle-Ottawa Scale for OBS. Results: A total of 14 studies were included: 11 RCTs with 10,481 patients (5,252 AI-AC, 5,229 TC) and 3 OBS with 4,544 patients (1,756 AI-AC, 2,788 TC). Adenoma Detection Rate (ADR) was significantly higher with AI-AC in both RCTs (RR 1.41, CI 1.25–1.60, P < 0.00001) and OBS (RR 1.15, CI 1.07–1.23, P < 0.0001), with a pooled RR of 1.34 (CI 1.21–1.48, P < 0.00001). Adenomas per Colonoscopy (APC) was also higher with AI-AC, with a mean difference of 0.19 (CI 0.16–0.22, P < 0.00001) in RCTs, 0.14 (CI 0.07–0.21, P = 0.0002) in OBS, and a pooled mean difference of 0.18 (CI 0.15–0.21, P < 0.00001). Polyp Detection Rate (PDR) was significantly higher in the AI-AC group in RCTs (RR 1.40, CI 1.27–1.55, P < 0.00001) but not in OBS (RR 1.02, CI 0.82–1.28, P = 0.84), with a pooled RR of 1.36 (CI 1.22–1.51, P < 0.00001). AADR was higher with AI-AC in RCTs (RR 1.45, CI 0.94–2.23, P = 0.09) and OBS (RR 1.56, CI 0.84–2.91, P = 0.16) without statistical significance, though pooled analysis showed significant improvement (RR 1.44, CI 1.06–1.95, P = 0.02). Conclusion: Results of RCTs and OBS consistently show that AI-AC significantly improves ADR, APC, PDR, and AADR compared to TC. These findings support that AI-AC enhances neoplasia detection across diverse settings and may improve screening efficacy in routine practice. Variability among studies likely reflects differences in patient populations, endoscopist experience, and AI systems.

Authors

Publication Details

Journal
The American Journal of Gastroenterology
Published
2025-10-01
DOI
https://doi.org/10.14309/01.ajg.0001130060.47564.d4
Primary Topic
Colorectal Cancer Screening and Detection
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

S650 AI-Assisted vs Traditional Colonoscopy in Colorectal Neoplasia Detection: A Systematic Review and Meta-Analysis of RCTs and Observational Studies

Suresh Selvam, Krish Patel, Nadia Ahmed, Fnu Raja et al.
The American Journal of Gastroenterology
Colorectal Cancer Screening and Detection
article

S650 AI-Assisted vs Traditional Colonoscopy in Colorectal Neoplasia Detection: A Systematic Review and Meta-Analysis of RCTs and Observational Studies

Suresh Selvam, Krish Patel, Nadia Ahmed, Fnu Raja, Amogh Verma, Surekha Tayade, Prateek Prateek, A. N. Das, A. K. M. Alauddin Chowdhury, Sneha Modi, Reshmitha Kantamneni, Sri Sai Praneeth Angara, Venkata Dileep Kumar Veldi, Adithya Andanappa, Digvijay Singh Rajawat, Saketh Sainag Mandiga
article en

Abstract

Introduction: In the United States, Colorectal cancer (CRC) remains a leading cause of cancer-related mortality. This systematic review and meta-analysis compare AI-assisted colonoscopy (AI-AC) to traditional colonoscopy (TC), integrating both randomized controlled trials (RCTs) and observational studies (OBS) to evaluate AI’s impact not only in controlled research settings but also in clinical practice. Methods: A comprehensive systematic search was conducted on PubMed, Embase, Scopus, and the Cochrane Library to identify RCTs and OBS comparing AI-AC with TC for adenoma and polyp detection till March 2025. Meta-analysis was conducted using RevMan 5.4.1. For dichotomous outcomes, pooled risk ratios (RRs) with 95% confidence intervals (CIs) were calculated using the Mantel-Haenszel method. For continuous outcomes, mean differences (MDs) with 95% CIs were used. Random or fixed-effects models were applied based on heterogeneity, assessed using Higgins I² statistic. Statistical significance was set at P-value < 0.05. The risk of bias was assessed using the RoB 2.0 tool for RCTs and the Newcastle-Ottawa Scale for OBS. Results: A total of 14 studies were included: 11 RCTs with 10,481 patients (5,252 AI-AC, 5,229 TC) and 3 OBS with 4,544 patients (1,756 AI-AC, 2,788 TC). Adenoma Detection Rate (ADR) was significantly higher with AI-AC in both RCTs (RR 1.41, CI 1.25–1.60, P < 0.00001) and OBS (RR 1.15, CI 1.07–1.23, P < 0.0001), with a pooled RR of 1.34 (CI 1.21–1.48, P < 0.00001). Adenomas per Colonoscopy (APC) was also higher with AI-AC, with a mean difference of 0.19 (CI 0.16–0.22, P < 0.00001) in RCTs, 0.14 (CI 0.07–0.21, P = 0.0002) in OBS, and a pooled mean difference of 0.18 (CI 0.15–0.21, P < 0.00001). Polyp Detection Rate (PDR) was significantly higher in the AI-AC group in RCTs (RR 1.40, CI 1.27–1.55, P < 0.00001) but not in OBS (RR 1.02, CI 0.82–1.28, P = 0.84), with a pooled RR of 1.36 (CI 1.22–1.51, P < 0.00001). AADR was higher with AI-AC in RCTs (RR 1.45, CI 0.94–2.23, P = 0.09) and OBS (RR 1.56, CI 0.84–2.91, P = 0.16) without statistical significance, though pooled analysis showed significant improvement (RR 1.44, CI 1.06–1.95, P = 0.02). Conclusion: Results of RCTs and OBS consistently show that AI-AC significantly improves ADR, APC, PDR, and AADR compared to TC. These findings support that AI-AC enhances neoplasia detection across diverse settings and may improve screening efficacy in routine practice. Variability among studies likely reflects differences in patient populations, endoscopist experience, and AI systems.

The American Journal of GastroenterologyVol. 120(10S2)
Openalex Percentile: Top 58%
Colorectal Cancer Screening and Detection
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.