Pilot study of a new freely available computer-aided polyp detection system in clinical practice

Thomas J Lux, Michael Banck, Zita Saßmannshausen, Joel Troya, Adrian Krenzer, Daniel Fitting, Boban Sudarevic, Wolfram G Zoller, Frank Puppe, Alexander Meining, Alexander Hann, Thomas J Lux, Michael Banck, Zita Saßmannshausen, Joel Troya, Adrian Krenzer, Daniel Fitting, Boban Sudarevic, Wolfram G Zoller, Frank Puppe, Alexander Meining, Alexander Hann

Abstract

Purpose: Computer-aided polyp detection (CADe) systems for colonoscopy are already presented to increase adenoma detection rate (ADR) in randomized clinical trials. Those commercially available closed systems often do not allow for data collection and algorithm optimization, for example regarding the usage of different endoscopy processors. Here, we present the first clinical experiences of a, for research purposes publicly available, CADe system.

Methods: We developed an end-to-end data acquisition and polyp detection system named EndoMind. Examiners of four centers utilizing four different endoscopy processors used EndoMind during their clinical routine. Detected polyps, ADR, time to first detection of a polyp (TFD), and system usability were evaluated (NCT05006092).

Results: During 41 colonoscopies, EndoMind detected 29 of 29 adenomas in 66 of 66 polyps resulting in an ADR of 41.5%. Median TFD was 130 ms (95%-CI, 80-200 ms) while maintaining a median false positive rate of 2.2% (95%-CI, 1.7-2.8%). The four participating centers rated the system using the System Usability Scale with a median of 96.3 (95%-CI, 70-100).

Conclusion: EndoMind's ability to acquire data, detect polyps in real-time, and high usability score indicate substantial practical value for research and clinical practice. Still, clinical benefit, measured by ADR, has to be determined in a prospective randomized controlled trial.

Keywords: Artificial intelligence; CADe; Colonoscopy; Deep learning; Polyp.

Conflict of interest statement

The authors declare no competing interests.

© 2022. The Author(s).

Figures

Fig. 1
Fig. 1
EndoMind mounted on an endoscopic tower in one of the participating centers. Presentation of a polyp image on a small screen (lower left corner) and proper detection with a bounding box (upper right corner) by EndoMind (asterisk)
Fig. 2
Fig. 2
Representative selection of EndoMind detections. EndoMind correctly marks a well visible (left) and a stool covered (middle) polyp with a blue bounding box. A common cause for false positive detections represented by stool on the bowel wall is displayed in the right image

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