Detection of Ovarian Cancer Using an Artificial Intelligence Enabled Transvaginal Ultrasound Imaging Algorithm
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Anticipated)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Contact
Study Contact
- Name: Qinglei Gao, MD, PhD
- Phone Number: 13871127473 13871127473
- Email: qingleigao@hotmail.com
Study Contact Backup
- Name: Ding Ma, MD, PhD
- Phone Number: 13886090620 13886090620
- Email: dingma424@126.com
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Description
Inclusion Criteria:
- Women scheduled for Transvaginal Ultrasound examination for adnexal lesions;
- Women aged over 18 years old;
- Women willing to participant in this study evidenced by signing the informed consent.
Exclusion Criteria:
- Women without adnexa for any reasons at the time of Transvaginal Ultrasound examination, including but not limited to receiving surgical removal for adnexa;
- Women with a pathologic diagnosis of ovarian cancer before the Transvaginal Ultrasound examination;
- Women with mental abnormal;
- Women did not cooperate or participate in other clinical trials;
- Pregnant or lactating women.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: Double
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
No Intervention: Transvaginal Ultrasound diagnosis
radiologists interpretTransvaginal Ultrasound images without the help of Artificial Intelligence (AI) algorithm
|
|
|
Experimental: AI enabled Transvaginal Ultrasound diagnosis
radiologists interpretTransvaginal Ultrasound images with the help of Artificial Intelligence algorithm
|
AI Enabled Transvaginal Ultrasound diagnosis for ovarian cancer
Other Names:
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
diagnostic accuracy
Time Frame: 2 years
|
diagnostic accuracy comparison between Transvaginal Ultrasound diagnosis with and without Artificial Intelligence algorithm for ovarian cancer
|
2 years
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
time cost for Transvaginal Ultrasound image interpretation
Time Frame: 2 years
|
time cost for radiologists to interpret Transvaginal Ultrasound images
|
2 years
|
Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Study Chair: Qinglei Gao, MD, PhD, Tongji Hospital
Study record dates
Study Major Dates
Study Start (Anticipated)
Study Start
Primary Completion (Anticipated)
Primary Completion
Study Completion (Anticipated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
- Neoplasms by Histologic Type
- Neoplasms
- Urogenital Neoplasms
- Neoplasms by Site
- Carcinoma
- Neoplasms, Glandular and Epithelial
- Genital Neoplasms, Female
- Endocrine System Diseases
- Ovarian Diseases
- Adnexal Diseases
- Gonadal Disorders
- Endocrine Gland Neoplasms
- Ovarian Neoplasms
- Carcinoma, Ovarian Epithelial
Other Study ID Numbers
Other Study ID Numbers
- 2019-TJ-OVAB
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
IPD Sharing Time Frame
IPD Sharing Access Criteria
IPD Sharing Supporting Information Type
- Study Protocol
- Statistical Analysis Plan (SAP)
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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.