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ePoster Display

1136P - A clinically applicable cervical cancer artificial intelligence screening system for accurate cytopathological diagnosis: A multicenter population-based study and randomized controlled trial

Date

16 Sep 2021

Session

ePoster Display

Topics

Tumour Site

Cervical Cancer

Presenters

Yunfang Yu

Citation

Annals of Oncology (2021) 32 (suppl_5): S921-S930. 10.1016/annonc/annonc707

Authors

Y. Yu1, J. Wang2, Y. Tan1, H. Wan2, N. Zheng2, Z. He1, L. Mao1, W. Ren1, Z. Lin3, G. He2, Y. Chen4, J. Wang3, N. ouyang1, H. Yao1

Author affiliations

  • 1 Department Of Medical Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 510308 - Guangzhou/CN
  • 2 Department Of Cellular And Molecular Diagnostics Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 510308 - Guangzhou/CN
  • 3 Department Of Technology, Cell Vision (Guangzhou) Medical Technology Inc., 510200 - Guangzhou/CN
  • 4 Department Of Medical Oncology, 3nd Affiliated Hospital of Sun Yat-sen University, 510000 - Guangzhou/CN

Resources

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Abstract 1136P

Background

Clinical application of artificial intelligence in cervical cancer cytology screening is still limited, so a Cervical Cancer Artificial Intelligence Screening System (CAISS) was aimed to established in this study.

Methods

The study consisted of a multicenter population-based study and randomized controlled trial (RCT) performed in China, enrolling 16,056 individuals aged over 18 who had liquid-based cytology pap test with eligible cervical cytological WSIs. 11,468 individuals’ WSIs from Sun Yat-sen Memorial Hospital (SYSMH) were randomly assigned (4:1) into training and internal validation dataset to train CAISS, and validated in SYSMH internal, Guangzhou Women and Children Medical Center (GWCMC), The Third Affiliated Hospital of Guangzhou Medical University (TAHGMU) validation datasets, and SYSMH prospective validation dataset. The RCT was conducted to compare the performance between CAISS, cytotechnicians, and CAISS-assisted. The sensitivity, specificity, accuracy, and AUC were used to assess CAISS's performance.

Results

The sensitivity of CAISS in identifying patients with abnormal cytology grades was 0.906, 0.902, 0.918 in the SYSMH internal, GWCMC external and TAHGMU external validation datasets, respectively. In prospective validation dataset, the CAISS showed similar sensitivity (0.946 vs 0.909, p= 0.304) and AUC (0.947 vs 0.948, p=0.952) to cytotechnician, and CAISS-assisted achieved better sensitivity, than cytotechnician alone (p= 0.024; p= 0.0006). In randomized controlled dataset, the specificity and accuracy of CAISS-assisted were significantly outperformed CAISS (0.989 vs 0.854, p< 0.001; 0.990 vs 0.861, p< 0.001), and no statistical difference in sensitivity between CAISS and cytotechnician (p= 0.552).

Conclusions

In this study, CAISS achieved high sensitivity for diagnosing cervical cytology grade that rivals cytotechnicians’ performance, and help cytotechnicians improve diagnostic sensitivity and accuracy to a higher level, which could improve the effectiveness of cervical cancer screening.

Clinical trial identification

NCT04551287.

Editorial acknowledgement

Legal entity responsible for the study

Yufang Yu.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

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