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

Cervical Cancer Clinical Trial

Official title:

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

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT04551287
• Other study ID #: 2020-KY-114
• Status: Completed
• Start date: July 1, 2019
• Est. completion date: December 14, 2020

Study information

• Verified date: August 2023
• Source: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial 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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 16164
• Est. completion date: December 14, 2020
• Est. primary completion date: December 14, 2020
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: Female
• Age group: 25 Years to 65 Years

Eligibility

Inclusion Criteria:

1. Women Aged 25-65 years old.

2. 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:

1. 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.

2. Women diagnosed with other malignant tumors other than cervical cancer.

Related Conditions & MeSH terms

• Artificial Intelligence
• Cervical Cancer
• Diagnostic Platform
• Uterine Cervical Neoplasms

Locations

Country	Name	City	State
China	Guangzhou Women and Children's Medical Center	Guangzhou	Guangdong
China	Sun Yat-Sen Memorial Hospital of Sun Yat-sen University	Guangzhou	Guangdong
China	The Third Affiliated Hospital of Guangzhou Medical University	Guangzhou	Guangdong

Sponsors (3)

Lead Sponsor	Collaborator
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University	Guangzhou Women and Children's Medical Center, The Third Affiliated Hospital of Guangzhou Medical University

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Area under ROC curve (AUC)	Area under the curve	Diagnostic evaluation will be performed within 1 week when the smear pictures are obtained
Secondary	Specificity	The true negative rate (TNR) of the diagnostic platform, which is the ratio between the number of negative individuals correctly categorized by platform and the total number of actual negative individuals (%).	Diagnostic evaluation will be performed within 1 week when the smear pictures are obtained
Secondary	Sensitivity	The true positive rate (TPR) of the diagnostic platform, which is the ratio between the number of positive individuals correctly categorized by platform and the total number of actual positive individuals (%).	Diagnostic evaluation will be performed within 1 week when the smear pictures are obtained
Secondary	Accuracy	The quantity of true positive (TP) plus true negative (TN) over the quantity of (TP) plus true negative (TN) plus false positive (FP) plus false negative (FN).	Diagnostic evaluation will be performed within 1 week when the smear pictures are obtained