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

August 6, 2023 updated by: Herui Yao, Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
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.

Study Overview

Status

Status

Indicates the current recruitment status or the expanded access status.
Completed

Conditions

Conditions

The disease, disorder, syndrome, illness, or injury that is being studied. On ClinicalTrials.gov, conditions may also include other health-related issues, such as lifespan, quality of life, and health risks.

Intervention / Treatment

Intervention / Treatment

A process or action that is the focus of a clinical study. Interventions include drugs, medical devices, procedures, vaccines, and other products that are either investigational or already available. Interventions can also include noninvasive approaches, such as education or modifying diet and exercise.

Detailed Description

A total of 16,056 eligible individuals were enrolled in this study, which consisted of a multicenter population-based study and a randomized controlled trial in China. In the initial exploring stage, a competition in cervical cancer screening between cytotechnicians and AI was held to preliminary exploration into the field in Guangzhou, China on August 04, 2019. 15 slides were randomly selected from 108 eligible individuals' WSIs from SYSMH for performance evaluation of the AI-based cervical cancer screening model and cytotechnicians. In the multicenter population-based study, 11,468 individuals' slides for the cervical cytology screening collected from the Sun Yat-sen Memorial Hospital (SYSMH, Guangzhou, China) between January, 2016 and January, 2020, were randomly assigned to the training dataset (n = 9,316) and the internal validation datasets (n = 2,152) in order to train the Cervical Cancer Artificial Intelligence Screening System (CAISS). To enhance the universality of the CAISS in clinical practice, slides from the other two participating hospitals were used as two independent external validation datasets: These included 600 slides from Guangzhou Women and Children Medical Center (GWCMC, Guangzhou, China) and 600 slides from The Third Affiliated Hospital of Guangzhou Medical University (TAHGMU, Guangzhou, China), which were obtained between January 2016 and January 2020. Further, a prospective validation dataset was conducted to distinguish the diagnostic performance of the cytotechnician, CAISS, and CAISS-assisted groups, in which 2,780 eligible slides from 2,780 individuals were obtained and prospectively labeled between August 28, 2020 and October 16, 2020 at SYSMH. In the third stage of this study, a prospective randomized controlled trial was conducted to compare the performance of the cytotechnician, CAISS, and CAISS-assisted groups in SYSMH. Here, 618 slides were collected between August 13, 2020, and December 14, 2020, to build the SYSMH randomized controlled trial. The remaining 608 slides after quality control were randomly assigned (1:1:1) to the CAISS group (n = 201), the cytotechnician group (n = 203), and the CAISS-assisted combination group (n = 204).

Study Type

Study Type

Describes the nature of a clinical study. Study types include interventional studies (also called clinical trials), observational studies (including patient registries), and expanded access.
Observational

Enrollment (Actual)

Enrollment

The number of participants in a clinical study. The "anticipated" enrollment is the target number of participants that the researchers need for the study.
16164

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • China
    • Guangdong
      • Guangzhou, Guangdong, China, 510000
        • Guangzhou Women And Children's Medical Center
      • Guangzhou, Guangdong, China, 510000
        • The Third Affiliated Hospital of Guangzhou Medical University
      • Guangzhou, Guangdong, China, 510120
        • Sun Yat-sen Memorial Hospital of Sun Yat-sen University

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Eligibility Criteria

The key requirements that people who want to participate in a clinical study must meet or the characteristics they must have. Eligibility criteria consist of both inclusion criteria (which are required for a person to participate in the study) and exclusion criteria (which prevent a person from participating). Types of eligibility criteria include whether a study accepts healthy volunteers, has age or age group requirements, or is limited by sex.

Ages Eligible for Study

25 years to 65 years (Adult, Older Adult)

Accepts Healthy Volunteers

Yes

Sampling Method

Non-Probability Sample

Study Population

Female patients who were 18 years or older with clear diagnostic results of cervical liquid-based cytological examination were included. All cases were collected from Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University.

Description

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.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Cohort
  • Time Perspectives: Other

Cohorts and Interventions

Group / Cohort

Group / Cohort

A group or subgroup of participants in an observational study that is assessed for biomedical or health outcomes.
Training dataset
11,468 eligible individuals' slides for the cervical cytology screening collected from the Sun Yat-sen Memorial Hospital (SYSMH, Guangzhou, China) between January 2016 and January 2020, were randomly assigned to the training dataset (n = 9,316) and the internal validation dataset (n = 2,152) in order to train and validate the Artificial Intelligence Cervical Cancer Screening (AICS).
SYSMH internal validation dataset
11,468 eligible individuals' slides for the cervical cytology screening collected from the Sun Yat-sen Memorial Hospital (SYSMH, Guangzhou, China) between January 2016 and January 2020, were randomly assigned to the training dataset (n = 9,316) and the internal validation dataset (n = 2,152) in order to train and validate the Artificial Intelligence Cervical Cancer Screening (AICS).
TAHGMU external validation dataset
600 slides from 600 eligible individuals were obtained in the Third Affiliated Hospital of Guangzhou Medical University (TAHGMU, Guangzhou, China) between January 2016 and January 2020, which was used to validate the Artificial Intelligence Cervical Cancer Screening (AICS).
GWCMC external validation dataset
600 slides from 600 eligible individuals were obtained in Guangzhou Women and Children Medical Center (GWCMC, Guangzhou, China) between January 2016 and January 2020, which was used to validate the Artificial Intelligence Cervical Cancer Screening (AICS).
Prospective validation dataset
A prospective validation dataset was conducted to distinguish the diagnostic performance of the cytopathologists, AICS, and AICS-assisted cytopathologists, in which 2,780 eligible slides from 2,780 individuals were obtained and prospectively labeled between August 28, 2020 and October 16, 2020 at SYSMH.
Randomized controlled trial
A prospective randomized controlled trial was conducted to compare the performance of the cytopathologists, AICS, and AICS-assisted cytopathologists in SYSMH. Here, 618 slides were collected between August 13, 2020, and December 14, 2020, to build the SYSMH randomized controlled trial. The remaining 608 slides after quality control were randomly assigned (1:1:1) to the AICS group (n = 201), the cytopathologists group (n = 203), and the AICS-assisted cytopathologists group (n = 204).

What is the study measuring?

Primary Outcome Measures

Primary Outcome Measures

In a clinical study's protocol, the planned outcome measure that is the most important for evaluating the effect of an intervention/treatment. Most clinical studies have one primary outcome measure, but some have more than one.
Outcome Measure
Measure Description
Time Frame
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
Diagnostic evaluation will be performed within 1 week when the smear pictures are obtained

Secondary Outcome Measures

Secondary Outcome Measures

In a clinical study's protocol, a planned outcome measure that is not as important as the primary outcome measure for evaluating the effect of an intervention but is still of interest. Most clinical studies have more than one secondary outcome measure.
Outcome Measure
Measure Description
Time Frame
Sensitivity
Time Frame: Diagnostic evaluation will be performed within 1 week when the smear pictures are obtained
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
Specificity
Time Frame: Diagnostic evaluation will be performed within 1 week when the smear pictures are obtained
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
Accuracy
Time Frame: Diagnostic evaluation will be performed within 1 week when the smear pictures are obtained
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

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sponsor

The organization or person who initiates the study and who has authority and control over the study.
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Collaborators

Collaborators

An organization other than the sponsor that provides support for a clinical study. This support may include activities related to funding, design, implementation, data analysis, or reporting.
The Third Affiliated Hospital of Guangzhou Medical University
Guangzhou Women and Children's Medical Center

Investigators

Investigators

A researcher involved in a clinical study. Related terms include site principal investigator, site sub-investigator, study chair, study director, and study principal investigator.
  • Principal Investigator: Herui Yao, PHD, Sun Yat-sen Memorial Hospital of Sun Yat-sen University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

Study Start

The actual date on which the first participant was enrolled in a clinical study. The "anticipated" study start date is the date that the researchers think will be the study start date.
July 1, 2019

Primary Completion (Actual)

Primary Completion

The date on which the last participant in a clinical study was examined or received an intervention to collect final data for the primary outcome measure. Whether the clinical study ended according to the protocol or was terminated does not affect this date. For clinical studies with more than one primary outcome measure with different completion dates, this term refers to the date on which data collection is completed for all the primary outcome measures. The "anticipated" primary completion date is the date that the researchers think will be the primary completion date for the study.
December 14, 2020

Study Completion (Actual)

Study Completion

The date on which the last participant in a clinical study was examined or received an intervention/treatment to collect final data for the primary outcome measures, secondary outcome measures, and adverse events (that is, the last participant's last visit). The "anticipated" study completion date is the date that the researchers think will be the study completion date.
December 14, 2020

Study Registration Dates

First Submitted

First Submitted

The date on which the study sponsor or investigator first submitted a study record to ClinicalTrials.gov. There is typically a delay of a few days between the first submitted date and the record's availability on ClinicalTrials.gov (the first posted date).
September 6, 2020

First Submitted That Met QC Criteria

First Submitted That Met QC Criteria

The date on which the study sponsor or investigator first submits a study record that is consistent with National Library of Medicine (NLM) quality control (QC) review criteria. The sponsor or investigator may need to revise and submit a study record one or more times before NLM's QC review criteria are met. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
September 10, 2020

First Posted (Actual)

First Posted

The date on which the study record was first available on ClinicalTrials.gov after National Library of Medicine (NLM) quality control (QC) review has concluded. There is typically a delay of a few days between the date the study sponsor or investigator submitted the study record and the first posted date.
September 16, 2020

Study Record Updates

Last Update Posted (Actual)

Last Update Posted

The most recent date on which changes to a study record were made available on ClinicalTrials.gov. There may be a delay between when the changes were submitted to ClinicalTrials.gov by the study's sponsor or investigator (the last update submitted date) and the last update posted date.
August 8, 2023

Last Update Submitted That Met QC Criteria

Last Update Submitted That Met QC Criteria

The most recent date on which the study sponsor or investigator submitted changes to a study record that are consistent with National Library of Medicine (NLM) quality control (QC) review criteria. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
August 6, 2023

Last Verified

Last Verified

The most recent date on which the study sponsor or investigator confirmed the information about a clinical study on ClinicalTrials.gov as accurate and current. If a study with a recruitment status of recruiting; not yet recruiting; or active, not recruiting has not been confirmed within the past 2 years, the study's recruitment status is shown as unknown.
August 1, 2023

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

Other Study ID Numbers

Identifiers or ID numbers other than the NCT number that are assigned to a clinical study by the study's sponsor, funders, or others. These numbers may include unique identifiers from other trial registries and National Institutes of Health grant numbers.
  • 2020-KY-114

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

Requests for the data collected and analyzed in this study will be considered if the application is in line with public benefits and the applicant is willing to sign a data access agreement. Contact can be through the corresponding author.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Cookie Settings

We use cookies to ensure that we give you the best experience on our website. For more details carefully read our Privacy and Cookies Policy. ...>>>You can change your preferences or withdraw your consent at any time by deleting the cookies from your website or computer as described in the policy. Please accept it and choose your preferences by ticking the corresponding boxes in the "Manage Settings" section below. Please carefully read our Terms of Service before you proceed with using any part of this website.
«Manage Settings