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Clinical evaluation of an artificial intelligence-assisted cytological system among screening strategies for a cervical cancer high-risk population.
Yang, Wen; Jin, Xiangshu; Huang, Liying; Jiang, Shufang; Xu, Jia; Fu, Yurong; Song, Yaoyao; Wang, Xueyan; Wang, Xueqing; Yang, Zhiming; Meng, Yuanguang.
Affiliation
  • Yang W; Department of Obstetrics and Gynecology, the Seventh Medical Center of Chinese PLA General Hospital, Beijing, China.
  • Jin X; Department of Obstetrics and Gynecology, the Seventh Medical Center of Chinese PLA General Hospital, Beijing, China.
  • Huang L; Tianjin Central Hospital of Gynecology Obstetrics, Tianjin, China.
  • Jiang S; Department of Obstetrics and Gynecology, the First Medical Center of Chinese PLA General Hospital, Beijing, China.
  • Xu J; Department of Obstetrics and Gynecology, the Seventh Medical Center of Chinese PLA General Hospital, Beijing, China.
  • Fu Y; School of Medicine, Nankai University, Tianjin, China.
  • Song Y; Department of Obstetrics and Gynecology, the First Medical Center of Chinese PLA General Hospital, Beijing, China.
  • Wang X; iDeepWise Artificial Intelligence Robot Technology (Beijing) Co., LTD, 12 Shangdi Xinxin Road, Beijing, China.
  • Wang X; iDeepWise Artificial Intelligence Robot Technology (Beijing) Co., LTD, 12 Shangdi Xinxin Road, Beijing, China.
  • Yang Z; iDeepWise Artificial Intelligence Robot Technology (Beijing) Co., LTD, 12 Shangdi Xinxin Road, Beijing, China.
  • Meng Y; iDeepWise Artificial Intelligence Robot Technology (Beijing) Co., LTD, 12 Shangdi Xinxin Road, Beijing, China. yzm@ideepwise.ai.
BMC Cancer ; 24(1): 776, 2024 Jun 27.
Article in En | MEDLINE | ID: mdl-38937664
ABSTRACT

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 the LBC + HPV cotesting strategy. Among the screening strategies, the YIs of the AI strategy at the LSIL + threshold and HSIL + threshold were the highest. At the HSIL + threshold, the AI strategy achieved the best result, with an AUC value of 0.621 (95% CI, 0.587-0.654), whereas HPV testing achieved the worst result, with an AUC value of 0.521 (95% CI, 0.484-0.559). Similarly, at the LSIL + threshold, the LBC-based strategy achieved the best result, with an AUC of 0.637 (95% CI, 0.606-0.668), whereas HPV testing achieved the worst result, with an AUC of 0.524 (95% CI, 0.491-0.557). Moreover, the AUCs of the AI and LBC strategies at this threshold were similar (0.631 and 0.637, respectively).

CONCLUSIONS:

These results confirmed that AI-only screening was the most authoritative method for diagnosing HSILs and LSILs, improving the accuracy of colposcopy diagnosis, and was more beneficial for patients than traditional LBC + HPV cotesting.
Subject(s)
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Full text: 1 Database: MEDLINE Main subject: Artificial Intelligence / Uterine Cervical Neoplasms / Papillomavirus Infections / Early Detection of Cancer Limits: Adult / Female / Humans / Middle aged Country/Region as subject: Asia Language: En Journal: BMC Cancer Journal subject: NEOPLASIAS Year: 2024 Type: Article Affiliation country: China

Full text: 1 Database: MEDLINE Main subject: Artificial Intelligence / Uterine Cervical Neoplasms / Papillomavirus Infections / Early Detection of Cancer Limits: Adult / Female / Humans / Middle aged Country/Region as subject: Asia Language: En Journal: BMC Cancer Journal subject: NEOPLASIAS Year: 2024 Type: Article Affiliation country: China