Clinical evaluation of an artificial intelligence-assisted cytological system among screening strategies for a cervical cancer high-risk population

作者：Wen Yang, Xiangshu Jin, Liying Huang, Shufang Jiang, Jia Xu, Yurong Fu, Yaoyao Song, Xueyan Wang, Xueqing Wang, Zhiming Yang, Yuanguang Meng · 发表于：BMC Cancer · 年份：2024 · DOI：10.1186/s12885-024-12532-y · 被引用次数：25 · 研究领域：Cervical Cancer and HPV Research、AI in cancer detection、Endometrial and Cervical Cancer Treatments

BACKGROUND: Primary cervical cancer screening and treating precancerous lesions are effective ways to prevent cervical cancer. However, the coverage rates of human papillomavirus (HPV) vaccines and routine screening are low in most developing countries and even some developed countries. This study aimed to explore the benefit of an artificial intelligence-assisted cytology (AI) system in a screening program for a cervical cancer high-risk population in China. METHODS: A total of 1231 liquid-based cytology (LBC) slides from women who underwent colposcopy at the Chinese PLA General Hospital from 2018 to 2020 were collected. All women had received a histological diagnosis based on the results of colposcopy and biopsy. The sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV), false-positive rate (FPR), false-negative rate (FNR), overall accuracy (OA), positive likelihood ratio (PLR), negative likelihood ratio (NLR) and Youden index (YI) of the AI, LBC, HPV, LBC + HPV, AI + LBC, AI + HPV and HPV Seq LBC screening strategies at low-grade squamous intraepithelial lesion (LSIL) and high-grade squamous intraepithelial lesion (HSIL) thresholds were calculated to assess their effectiveness. Receiver operating characteristic (ROC) curve analysis was conducted to assess the diagnostic values of the different screening strategies. RESULTS: The Se and Sp of the primary AI-alone strategy at the LSIL and HSIL thresholds were superior to those of...