- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT05281939
Multi-center Application of an AI System for Diagnosis of Cervical Lesions Based on Colposcopy Images
November 15, 2023 updated by: Binhua Dong, Fujian Maternity and Child Health Hospital
Multi-center Application of an Artificial Intelligence System for Automatic Real-time Diagnosis of Cervical Lesions Based on Colposcopy Images
The application of artificial intelligence in image recognition of cervical lesions diagnosis has become a research hotspot in recent years.
The analysis and interpretation of colposcopy images play an important role in the diagnosis,prevention and treatment of cervical precancerous lesions and cervical cancer.
At present, the accuracy of colposcopy detection is still affected by many factors.
The research on the diagnosis system of cervical lesions based on multimodal deep learning of colposcopy images is a new and significant research topic.
Based on the large database of cervical lesions diagnosis images and non-images, the research group established a multi-source heterogeneous cervical lesion diagnosis big data platform of non-image and image data.
Research the lesions segmentation and classification model of colposcopy image based on convolutional neural network, explore the relevant medical data fusion network model that affects the diagnosis of cervical lesions, and realize a multi-modal self-learning artificial intelligence cervical lesion diagnosis system based on colposcopy images.
The application efficiency of the artificial intelligence system in the real world was explored through the cohort, and the intelligent teaching model and method of cervical lesion diagnosis were further established based on the above intelligent system.
Study Overview
Status
Recruiting
Conditions
Intervention / Treatment
Detailed Description
Based on previous studies and clinical practice, this study carried out a multi center application in Fujian Province, China.
In this study, Fujian Maternity and Child Health Hospital and Mindong Hospital of Ningde City were included, with a total of 10000 participants who have undergone colposcopy examination were enrolled.
In the first place, the investigators will build a multimodal artificial intelligence diagnostic system by combining colposcopy images with other non-image data, such as the results of HPV tests and Thinprep cytologic test (TCT) and so on.
And then, use standardized colposcopy images and non-image medical data of cervical lesions in different medical institutions to verify the efficacy of the multimodal intelligent diagnostic system for cervical lesions.
What's, more, the investigators will establish artificial intelligence cohorts (assisted by intelligent systems) and traditional physician cohorts (assisted by expert, senior and primary physicians) to contrast the diagnosis results of the multimodal artificial intelligence diagnostic system and different levels of colposcopy doctors.
And can also bidirectionally analyse the diagnostic efficacy and differences of the system and colposcopy physicians of different levels, and evaluate the performance of this diagnostic system for real-world applications.
Study Type
Interventional
Enrollment (Estimated)
10000
Phase
- Not Applicable
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Contact
- Name: Binhua Dong
- Phone Number: +8613599071900
- Email: dbh18-jy@126.com
Study Locations
-
-
-
Nanping, China
- Recruiting
- Jianou Maternal and child Health Care Hospital
-
Contact:
- Huihua Ge
-
Ningde, China
- Recruiting
- Ningde Hospital affiliated to Ningde Normal University
-
Contact:
- Wenfang Jin
-
Quanzhou, China
- Recruiting
- Quanzhou First Hospital
-
Contact:
- Yuchun Lv
-
-
Fujian
-
Fuzhou, Fujian, China, 350001
- Recruiting
- Fujian Maternity and Child Health Hospital
-
Contact:
- Binhua Dong
- Phone Number: +8613599071900
- Email: dbh18-jy@126.com
-
Ningde, Fujian, China, 352000
- Recruiting
- MinDong Hospital of Ningde City
-
Contact:
- Fang Xie, M.D
- Phone Number: +8613860388999
-
-
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
Ages Eligible for Study
18 years and older (Adult, Older Adult)
Accepts Healthy Volunteers
Yes
Description
Inclusion Criteria:
- Married woman
- Woman aged 18 and over
- Woman with an intact cervix
- Patients with abnormal results in cervical cancer screening
- Be able to understand this study and have signed a written informed consent
Exclusion Criteria:
- Woman with acute reproductive tract inflammation
- History of pelvic radiotherapy surgery
- Woman with mental disorder
- Patients with history of other malignant tumors
- Refuse to participate in this study
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
- Primary Purpose: Diagnostic
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: Triple
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
---|---|
Active Comparator: Artificial intelligence diagnostic group
Women who show abnormalities in cervical cancer screening and require referral for colposcopy.
Colposcopy was performed with the aid of an Artificial intelligence (AI) system.
|
Participants were divided into the intervention group and the control group using a random number table.
The intervention group participants' cervical colposcopic image data and non-image data as follow:age, the infection of high-risk human papillomavirus (HR-HPV),the type of HR-HPV infection,the duration of HR-HPV infection, cervical cytology (TCT) results, HIV/sexually transmitted infection history, marriage and childbearing history,first sexual life history, sexual partner history, smoking history,oral contraceptives history,the use of immune drug and possible clinical symptoms of cervical lesions such as postcoital bleeding, abnormal vaginal secretions, vaginal bleeding symptoms, etc.
|
No Intervention: Gynecologist diagnostic Group
Women who show abnormalities in cervical cancer screening and require referral for colposcopy.
Colposcopy is performed independently by a gynecologist without any external assistance.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
HPV testing
Time Frame: o month
|
Cervical exfoliated cells were collected for HPV testing
|
o month
|
Cervical cytology testing
Time Frame: 0 month
|
Cervical exfoliated cells were collected for cytological and pathological examination.
|
0 month
|
Cervical histopathological examination
Time Frame: 0 month
|
Cervical tissue was collected for histopathological examination
|
0 month
|
Accuracy of CIN2+ diagnosis
Time Frame: 0 month
|
Accuracy in the diagnosis of cervical intraepithelial neoplasia grade 2 or worse.
|
0 month
|
Accuracy of CIN3+ diagnosis
Time Frame: 0 month
|
Accuracy in the diagnosis of cervical intraepithelial neoplasia grade 3 or worse.
|
0 month
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Investigators
- Study Chair: Pengming Sun, PhD, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical 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)
August 1, 2021
Primary Completion (Estimated)
August 1, 2024
Study Completion (Estimated)
September 1, 2024
Study Registration Dates
First Submitted
March 7, 2022
First Submitted That Met QC Criteria
March 7, 2022
First Posted (Actual)
March 16, 2022
Study Record Updates
Last Update Posted (Estimated)
November 16, 2023
Last Update Submitted That Met QC Criteria
November 15, 2023
Last Verified
November 1, 2023
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- AICC2203
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
product manufactured in and exported from the U.S.
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.
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