Artificial Intelligence Enables Precision Diagnosis of Cervical Cytology Grades and Cervical Cancer

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University3 sites in 1 country16,164 target enrollmentJuly 1, 2019

ConditionsCervical Cancer Diagnostic Platform Diagnosing Cervical Cytology Grades and Cancer Artificial Intelligence

Overview

Phase: Not Applicable
Intervention: Not specified
Conditions: Cervical Cancer
Sponsor: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Enrollment: 16164
Locations: 3
Primary Endpoint: Area under ROC curve (AUC)
Status: Completed
Last Updated: 2 years ago

Overview Investigators Eligibility Criteria Outcomes Sites Similar Trials

Overview

Brief Summary

Cervical cancer, the fourth most common cancer globally and the fourth leading cause of cancer-related deaths, can be effectively prevented through early screening. Detecting precancerous cervical lesions and halting their progression in a timely manner is crucial. However, accurate screening platforms for early detection of cervical cancer are needed. Therefore, it is urgent to develop an Artificial Intelligence Cervical Cancer Screening (AICS) system for diagnosing cervical cytology grades and cancer.

Registry

clinicaltrials.gov

Start Date

July 1, 2019

End Date

December 14, 2020

Last Updated

2 years ago

Study Type

Observational

Sex

Female

Investigators

Sponsor

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Responsible Party

Principal Investigator

Herui Yao

Principal Investigator

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Eligibility Criteria

Inclusion Criteria

•Women Aged 25-65 years old.
•Availability of confirmed diagnostic results of the cervical liquid-based cytological examination, and satisfactory digital images from the liquid-based cytology pap test: at least 5000 uncovered and observable squamous epithelial cells, samples with abnormal cells (atypical squamous cells or atypical glandular cells and above).

Exclusion Criteria

•Unsatisfactory samples of cervical liquid-based cytological examination: less than 5000 uncovered, observable squamous epithelial cells, and more than 75% of squamous epithelial cells affected because of blood, inflammatory cells, epithelial cells over-overlapping, poor fixation, excessive drying, or contamination of unknown components.
•Women diagnosed with other malignant tumors other than cervical cancer.

Outcomes

Primary Outcomes

Area under ROC curve (AUC)

Time Frame: Diagnostic evaluation will be performed within 1 week when the smear pictures are obtained

Area under the curve

Secondary Outcomes

Specificity(Diagnostic evaluation will be performed within 1 week when the smear pictures are obtained)
Accuracy(Diagnostic evaluation will be performed within 1 week when the smear pictures are obtained)
Sensitivity(Diagnostic evaluation will be performed within 1 week when the smear pictures are obtained)