1. Performance comparison between two computer-aided detection colonoscopy models by trainees using different false positive thresholds: a cross-sectional study in Thailand.
- Author
-
Kasenee Tiankanon, Julalak Karuehardsuwan, Satimai Aniwan, Parit Mekaroonkamol, Panukorn Sunthornwechapong, Huttakan Navadurong, Kittithat Tantitanawat, Krittaya Mekritthikrai, Salin Samutrangsi, Peerapon Vateekul, and Rungsun Rerknimitr
- Subjects
COMPUTER-aided diagnosis ,COLONOSCOPY ,CROSS-sectional method ,ARTIFICIAL intelligence ,COMPUTATIONAL intelligence - Abstract
Background/Aims: This study aims to compare polyp detection performance of "Deep-GI," a newly developed artificial intelligence (AI) model, to a previously validated AI model computer-aided polyp detection (CADe) using various false positive (FP) thresholds and determining the best threshold for each model. Methods: Colonoscopy videos were collected prospectively and reviewed by three expert endoscopists (gold standard), trainees, CADe (CAD EYE; Fujifilm Corp.), and Deep-GI. Polyp detection sensitivity (PDS), polyp miss rates (PMR), and false-positive alarm rates (FPR) were compared among the three groups using different FP thresholds for the duration of bounding boxes appearing on the screen. Results: In total, 170 colonoscopy videos were used in this study. Deep-GI showed the highest PDS (99.4% vs. 85.4% vs. 66.7%, p<0.01) and the lowest PMR (0.6% vs. 14.6% vs. 33.3%, p<0.01) when compared to CADe and trainees, respectively. Compared to CADe, Deep-GI demonstrated lower FPR at FP thresholds of ≥0.5 (12.1 vs. 22.4) and ≥1 second (4.4 vs. 6.8) (both p<0.05). However, when the threshold was raised to ≥1.5 seconds, the FPR became comparable (2 vs. 2.4, p=0.3), while the PMR increased from 2% to 10%. Conclusions: Compared to CADe, Deep-GI demonstrated a higher PDS with significantly lower FPR at ≥0.5- and ≥1-second thresholds. At the ≥1.5-second threshold, both systems showed comparable FPR with increased PMR. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF