Introduction
The benefit of computer-assisted detection systems (CADe) has been evaluated in several randomized controlled trials (RCTs) showing improved adenoma detection rate (ADR) and polyp detection rates (PDR) (1-3). However, the generalizability of these studies is questioned as these studies are performed in highly controlled setting and thus not representing a real-world clinical setting (4). It is also believed that the increase in ADR by CADe-assisted colonoscopy is mainly observed in lower detector endoscopists (5, 6).
We aimed to evaluate the effect of CADe-assisted colonoscopy on ADR in an actual clinical setting in a high-volume, non-tertiary endoscopy centre with high detector endoscopists.
Aims & Methods
A single-centre, observational study was conducted on all patients undergoing colonoscopy due to symptoms of colorectal cancer (CRC), screening colonoscopies for CRC, post-polypectomy surveillance, or colonoscopy due to positive results from a fecal immunochemical test in an Australian hospital between March 2023 to October 2023. Colonoscopies were performed by 19 experienced endoscopists using the validated CADe system that allows for real-time image analysis (GI Genius, Cosmo IMD Ireland). Historical procedural data regarding colonoscopies were obtained up to 10 months before the start of the study and were compared to the CADe-assisted colonoscopies in a 2:1 fashion. The primary outcome of the study was the ADR. Data were analyzed using logistic mixed effects models with random intercepts for patient and endoscopist, expressed as Odds ratio (OR) with a 95% confidence interval (CI).
Results
A total of 7798 colonoscopies were performed for 7460 patients during the timeframe, including 2813 colonoscopies using CADe and 4985 standard colonoscopies. The ADR in the CADe-assisted colonoscopy group was 52% compared to 46% in the standard colonoscopy group. There was a significant difference in ADR (OR 1.22, 95% CI 1.09 - 1.36, p<0.001) and PDR (OR 1.22, 95% CI 1.09 - 1.37, p<0.001) between CADe-assisted colonoscopy and standard colonoscopy respectively, adjusted for age, bowel preparation quality, withdrawal time and sex.
Table 1 Adenoma detection and polyp detection rate of the CADe-assisted colonoscopy group compared to the standard colonoscopy group.
| Standard colonoscopy
n=4985 | CADe-assisted colonoscopy
n=2813 | OR (95% CI) |
| ADR (%) | 2318/4985 (46%) | 1455/2813 (52%) | 1.22, 1.09 - 1.36 |
| PDR (%) | 2865/4985 (57%) | 1769/2813 63%) | 1.22, 1.09 - 1.37 |
| Advanced ADR (%) | 536/4985 (11%) | 343/2813 (12%) |
|
| Serrated lesion detection rate (%) | 1107/4985 (22%) | 667/2813 (24%) |
|
| Mean number of adenomas per colonoscopy | 2.0 (1.0-3.0) | 2.0 (1.0-3.0) |
|
| Polyps per colonoscopy | 1.0 (0.0-3.0) | 2.0 (1.0-4.0) |
|
Data are number (%) and median (IQR)
Conclusion
In this real-time, observational study, CADe-assisted colonoscopy significantly improves the adenoma detection rate and polyp detection rate. Our study shows that the implementation of CADe-assisted colonoscopies in daily practice is useful, even in high-detector endoscopists.
References
1. Wang P, Liu X, Berzin TM, Glissen Brown JR, Liu P, et al. Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study. Lancet Gastroenterol Hepatol. 2020;5(4):343-51.
2. Repici A, Spadaccini M, Antonelli G, Correale L, Maselli R, et al. Artificial intelligence and colonoscopy experience: lessons from two randomised trials. Gut. 2022;71(4):757-65.
3. Hassan C, Spadaccini M, Mori Y, Foroutan F, Facciorusso A, et al. Real-Time Computer-Aided Detection of Colorectal Neoplasia During Colonoscopy : A Systematic Review and Meta-analysis. Ann Intern Med. 2023;176(9):1209-20.
4. Patel HK, Mori Y, Hassan C, Rizkala T, Radadiya DK, et al. Lack of Effectiveness of Computer Aided Detection for Colorectal Neoplasia: A Systematic Review and Meta-Analysis of Nonrandomized Studies. Clin Gastroenterol Hepatol. 2023.
5. Karsenti D, Tharsis G, Perrot B, Cattan P, Percie du Sert A, Venezia F, et al. Effect of real-time computer-aided detection of colorectal adenoma in routine colonoscopy (COLO-GENIUS): a single-centre randomised controlled trial. Lancet Gastroenterol Hepatol. 2023;8(8):726-34.
6. Mangas-Sanjuan C, de-Castro L, Cubiella J, Diez-Redondo P, Suarez A, Pellise M, et al. Role of Artificial Intelligence in Colonoscopy Detection of Advanced Neoplasias : A Randomized Trial. Ann Intern Med. 2023;176(9):1145-52.