Impact of computer‐aided characterization for diagnosis of colorectal lesions, including sessile serrated lesions: Multireader, multicase study

医学 结肠镜检查 置信区间 放射科 计算机辅助诊断 活检 内科学 结直肠癌 癌症
作者
Sayuri Kato,Shin‐ei Kudo,Yosuke Minegishi,Yuki Miyata,Yukihide Maeda,Takanori Kuroki,Yuki Takashina,Kenichi Mochizuki,Eri Tamura,Masahiro Abe,Yuta Sato,Tatsuya Sakurai,Yuta Kouyama,Kenta Tanaka,Yushi Ogawa,Hiroki Nakamura,Katsuro Ichimasa,Noriyuki Ogata,Tomokazu Hisayuki,Takemasa Hayashi,Kunihiko Wakamura,Hideyuki Miyachi,Toshiyuki Baba,Fumio Ishida,Tetsuo Nemoto,Masashi Misawa
出处
期刊:Digestive Endoscopy [Wiley]
卷期号:36 (3): 341-350 被引量:2
标识
DOI:10.1111/den.14612
摘要

Computer-aided characterization (CADx) may be used to implement optical biopsy strategies into colonoscopy practice; however, its impact on endoscopic diagnosis remains unknown. We aimed to evaluate the additional diagnostic value of CADx when used by endoscopists for assessing colorectal polyps.This was a single-center, multicase, multireader, image-reading study using randomly extracted images of pathologically confirmed polyps resected between July 2021 and January 2022. Approved CADx that could predict two-tier classification (neoplastic or nonneoplastic) by analyzing narrow-band images of the polyps was used to obtain a CADx diagnosis. Participating endoscopists determined if the polyps were neoplastic or not and noted their confidence level using a computer-based, image-reading test. The test was conducted twice with a 4-week interval: the first test was conducted without CADx prediction and the second test with CADx prediction. Diagnostic performances for neoplasms were calculated using the pathological diagnosis as reference and performances with and without CADx prediction were compared.Five hundred polyps were randomly extracted from 385 patients and diagnosed by 14 endoscopists (including seven experts). The sensitivity for neoplasia was significantly improved by referring to CADx (89.4% vs. 95.6%). CADx also had incremental effects on the negative predictive value (69.3% vs. 84.3%), overall accuracy (87.2% vs. 91.8%), and high-confidence diagnosis rate (77.4% vs. 85.8%). However, there was no significant difference in specificity (80.1% vs. 78.9%).Computer-aided characterization has added diagnostic value for differentiating colorectal neoplasms and may improve the high-confidence diagnosis rate.
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