دورية أكاديمية

Artificial intelligence (AI) real-time detection vs. routine colonoscopy for colorectal neoplasia: a meta-analysis and trial sequential analysis.

التفاصيل البيبلوغرافية
العنوان: Artificial intelligence (AI) real-time detection vs. routine colonoscopy for colorectal neoplasia: a meta-analysis and trial sequential analysis.
المؤلفون: Deliwala, Smit S., Hamid, Kewan, Barbarawi, Mahmoud, Lakshman, Harini, Zayed, Yazan, Kandel, Pujan, Malladi, Srikanth, Singh, Adiraj, Bachuwa, Ghassan, Gurvits, Grigoriy E., Chawla, Saurabh
المصدر: International Journal of Colorectal Disease; Nov2021, Vol. 36 Issue 11, p2291-2303, 13p
مصطلحات موضوعية: SEQUENTIAL analysis, ARTIFICIAL intelligence, ADENOMATOUS polyps, TUMORS, COLORECTAL cancer
مستخلص: Goals and background: Studies analyzing artificial intelligence (AI) in colonoscopies have reported improvements in detecting colorectal cancer (CRC) lesions, however its utility in the realworld remains limited. In this systematic review and meta-analysis, we evaluate the efficacy of AI-assisted colonoscopies against routine colonoscopy (RC). Study: We performed an extensive search of major databases (through January 2021) for randomized controlled trials (RCTs) reporting adenoma and polyp detection rates. Odds ratio (OR) and standardized mean differences (SMD) with 95% confidence intervals (CIs) were reported. Additionally, trial sequential analysis (TSA) was performed to guard against errors. Results: Six RCTs were included (4996 participants). The mean age (SD) was 51.99 (4.43) years, and 49% were females. Detection rates favored AI over RC for adenomas (OR 1.77; 95% CI: 1.570–2.08) and polyps (OR 1.91; 95% CI: 1.68–2.16). Secondary outcomes including mean number of adenomas (SMD 0.23; 95% CI: 0.18–0.29) and polyps (SMD 0.23; 95% CI: 0.17–0.29) detected per procedure favored AI. However, RC outperformed AI in detecting pedunculated polyps. Withdrawal times (WTs) favored AI when biopsies were included, while WTs without biopsies, cecal intubation times, and bowel preparation adequacy were similar. Conclusions: Colonoscopies equipped with AI detection algorithms could significantly detect previously missed adenomas and polyps while retaining the ability to self-assess and improve periodically. More effective clearance of diminutive adenomas may allow lengthening in surveillance intervals, reducing the burden of surveillance colonoscopies, and increasing its accessibility to those at higher risk. TSA ruled out the risk for false-positive results and confirmed a sufficient sample size to detect the observed effect. Currently, these findings suggest that AI-assisted colonoscopy can serve as a useful proxy to address critical gaps in CRC identification. [ABSTRACT FROM AUTHOR]
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قاعدة البيانات: Complementary Index
الوصف
تدمد:01791958
DOI:10.1007/s00384-021-03929-3