Chung Goh Eun, Lee Jooyoung, Lim Seon Hee, Kang Hae Yeon, Kim Jung, Song Ji Hyun, Yang Sun Young, Choi Ji Min, Seo Ji Yeon, Bae Jung Ho
Department of Internal Medicine and Healthcare Research Institute, Healthcare System Gangnam Center, Seoul National University Hospital, Seoul, Korea.
Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.
NPJ Digit Med. 2024 Dec 19;7(1):366. doi: 10.1038/s41746-024-01334-y.
This study evaluated the impact of differing false positive (FP) rates in two computer-aided detection (CADe) systems on the clinical effectiveness of artificial intelligence (AI)-assisted colonoscopy. The primary outcomes were adenoma detection rate (ADR) and adenomas per colonoscopy (APC). The ADR in the control, system A (3.2% FP rate), and system B (0.6% FP rate) groups were 44.3%, 43.4%, and 50.4%, respectively, with system B showing a significantly higher ADR than the control group. The APC for the control, A, and B groups were 0.75, 0.83, and 0.90, respectively, with system B also showing a higher APC than the control. The non-true lesion resection rates were 23.8%, 29.2%, and 21.3%, with system B having the lowest. The system with lower FP rates demonstrated improved ADR and APC without increasing the resection of non-neoplastic lesions. These findings suggest that higher FP rates negatively affect the clinical performance of AI-assisted colonoscopy.
本研究评估了两种计算机辅助检测（CADe）系统中不同的假阳性（FP）率对人工智能（AI）辅助结肠镜检查临床效果的影响。主要结局指标为腺瘤检出率（ADR）和每次结肠镜检查的腺瘤数（APC）。对照组、系统A（FP率为3.2%）和系统B（FP率为0.6%）组的ADR分别为44.3%、43.4%和50.4%，系统B的ADR显著高于对照组。对照组、A组和B组的APC分别为0.75、0.83和0.90，系统B的APC也高于对照组。非真实病变切除率分别为23.8%、29.2%和21.3%，系统B的切除率最低。FP率较低的系统在不增加非肿瘤性病变切除的情况下，ADR和APC得到改善。这些发现表明，较高的FP率对AI辅助结肠镜检查的临床性能有负面影响。
