Introduction
Effective withdrawal time (EWT), as measured by EndoScreener QC (Wision A.I.), is a novel artificial intelligence (AI)-derived colonoscopy quality metric, which measures the actual duration of clear images obtained during scope withdrawal from cecum to rectum. We have previously demonstrated the superiority of EWT to standard withdrawal time (SWT) on adenoma detection rate (ADR) in a retrospective study.(1) This prospective study determines the association between EWT and colonic lesion detection rates.
Aims & Methods
This was a prospective evaluation of the use of real-time determination of EWT, as measured by the EndoScreener QC, of endoscopists who were blinded to the output of the system. Patients were recruited in our hospital from Nov 2023 to Feb 2024. All examination was performed with high-definition endoscopes (EVIS-EXERA 290 video system, Olympus Optical, Tokyo, Japan) under white light. In all examination, colonoscope was first advanced to the cecum as confirmed by identification of the appendiceal orifice and ileocecal valve or by intubation of the ileum. After cecal intubation, the colonoscopy was slowly withdrawn. The AI derived (AI) real time effective mucosal examination monitor system (EndoScreen QC) was initiated during scope withdrawal, starting from cecum to anus. The SWT was defined as total withdrawal time from cecum to rectum after excluding polypectomy and biopsy time. All detected polyps were removed during scope withdrawal only. The size (measured with biopsy forceps), location and morphology of each polyp was recorded by an independent observer. The bowel preparation quality was graded according to the Boston Bowel Preparation Scale. The primary outcome was the correlation between EWT and ADR, which was determined by the Pearson correlation coefficient (r); and compared with SWT. Other outcomes included correlation between EWT and polyp detection rate (PDR) or serrated lesion detection rate (SDR).
Results
In the prospective analysis, 185 colonoscopies performed by 9 endoscopists were analyzed. The mean age was 67.4 year (SD: 10.5) and 57.3% (n=106) were male. 83.9% (n=154) were diagnostic colonoscopy. The median Boston Bowel Preparation score (BBPS) was 7. The mean ADR was 49.2% (95% CI: 41.6-56.2, n=91), mean EWT was 4.4 (95% CI: 4.1-4.6) minutes and mean SWT was 7.1 (95% CI: 6.7-7.5) minutes. The correlation between EWT and ADR was significantly higher (r=0.98, 95%CI: 0.96-1.00) than between SWT and ADR (r=0.80, 95%CI: 0.53-0.98, p<0.01). For PDR, the correlation between EWT and PDR was also significantly higher than between SWT and PDR (r=0.97, 95%CI: 0.95-1.00 vs r=0.73, 95%CI: 0.30-0.98, p=0.02). However, there was no significant difference between EWT and SWT on SDR [r=0.92, 95%CI: 0.72-1.00 vs r=0.93, 95%CI: 0.86-0.98, p=0.89].
Table 1: Baseline characteristics and outcomes of the study
Number
Mean age in years (SD)
Male sex, % (n)
| 185
67.4 (10.5)
106 (57.3)
|
Indications:
Screening, % (n)
Diagnostic, % (n)
Bowel preparation in BBPS, median (range)
Mean standard withdrawal time in mins (95%CI)
Mean EWT in mins (95%CI)
|
31 (16.8)
154 (83.9)
7 (6-9)
7.1 (6.7-7.5)
4.4 (4.1-4.6)
|
ADR %(n)
PDR %(n)
SDR % (n)
Mean number of adenoma (SD)
Mean number of polyp (SD)
Mean number of serrated lesion (SD)
| 49.2 (91)
58.9 (109)
20.0 (37)
1.1 (0.1)
1.6 (0.1)
0.4 (0.1)
|
r between SWT and ADR (95%CI)
r between EWT and ADR (95%CI)
r between SWT and PDR (95%CI)
r between EWT and PDR (95%CI)
r between SWT and SDR (95%CI)
r between EWT and SDR (95%CI)
| 0.80 (0.53-0.98)
0.98 (0.96-1.00)
0.73 (0.30-0.98)
0.97 (0.95-1.00)
0.93 (0.86-0.98)
0.92 (0.72-1.00)
|
Conclusion
The novel AI-derived EWT demonstrated better correlation with ADR and PDR than SWT in this prospective study. Further studies should evaluate the role of applying real-time monitoring EWT on endoscopy training and quality improvement of endoscopists with low ADR.
References
1. Lui TKL, Ko MKL, Liu JJ, Xiao X, Leung WK. Artificial intelligence-assisted real-time monitoring of effective withdrawal time during colonoscopy: a novel quality marker of colonoscopy. Gastrointest Endosc. 2024;99(3):419-27.e6.
Disclosure
The following companies had given donation to our team for research.
Olympus, Fujifilm, Medronic, Wision AI, Insign Medical Co Ltd