Detection of Ovarian Cancer Using an Artificial Intelligence Enabled Transvaginal Ultrasound Imaging Algorithm
Primary Purpose
Ovarian Cancer
Status
Not yet recruiting
Phase
Not Applicable
Locations
Study Type
Interventional
Intervention
Artificial Intelligence Enabled Transvaginal Ultrasound Imaging algorithm
Sponsored by
About this trial
This is an interventional diagnostic trial for Ovarian Cancer
Eligibility Criteria
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.
Sites / Locations
Arms of the Study
Arm 1
Arm 2
Arm Type
No Intervention
Experimental
Arm Label
Transvaginal Ultrasound diagnosis
AI enabled Transvaginal Ultrasound diagnosis
Arm Description
radiologists interpretTransvaginal Ultrasound images without the help of Artificial Intelligence (AI) algorithm
radiologists interpretTransvaginal Ultrasound images with the help of Artificial Intelligence algorithm
Outcomes
Primary Outcome Measures
diagnostic accuracy
diagnostic accuracy comparison between Transvaginal Ultrasound diagnosis with and without Artificial Intelligence algorithm for ovarian cancer
Secondary Outcome Measures
time cost for Transvaginal Ultrasound image interpretation
time cost for radiologists to interpret Transvaginal Ultrasound images
Full Information
NCT ID
NCT04214782
First Posted
December 28, 2019
Last Updated
October 6, 2021
Sponsor
Tongji Hospital
Collaborators
Hubei Cancer Hospital, Qilu Hospital of Shandong University, Henan Cancer Hospital, Xiangyang Central Hospital, The First People's Hospital of Jingzhou, First Affiliated Hospital, Sun Yat-Sen University
1. Study Identification
Unique Protocol Identification Number
NCT04214782
Brief Title
Detection of Ovarian Cancer Using an Artificial Intelligence Enabled Transvaginal Ultrasound Imaging Algorithm
Official Title
Detection of Ovarian Cancer Using an Artificial Intelligence Enabled Transvaginal Ultrasound Imaging Algorithm
Study Type
Interventional
2. Study Status
Record Verification Date
October 2021
Overall Recruitment Status
Not yet recruiting
Study Start Date
October 1, 2022 (Anticipated)
Primary Completion Date
October 1, 2023 (Anticipated)
Study Completion Date
October 1, 2024 (Anticipated)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Principal Investigator
Name of the Sponsor
Tongji Hospital
Collaborators
Hubei Cancer Hospital, Qilu Hospital of Shandong University, Henan Cancer Hospital, Xiangyang Central Hospital, The First People's Hospital of Jingzhou, First Affiliated Hospital, Sun Yat-Sen University
4. Oversight
Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
5. Study Description
Brief Summary
Ovarian cancer is relatively rare but fatal with an annual incidence rate of 11.8 per 100 000 and a high mortality-to-incidence ratio of >0.6. The modest diagnostic accuracy of TVU has risen some concerns about the over-treatment.Now, with the development of artificial intelligence (AI), we may have a better chance to interpret TVU imagines with high efficiency, reproducibility and accuracy.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Ovarian Cancer
7. Study Design
Primary Purpose
Diagnostic
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Masking
ParticipantOutcomes Assessor
Allocation
Randomized
Enrollment
10000 (Anticipated)
8. Arms, Groups, and Interventions
Arm Title
Transvaginal Ultrasound diagnosis
Arm Type
No Intervention
Arm Description
radiologists interpretTransvaginal Ultrasound images without the help of Artificial Intelligence (AI) algorithm
Arm Title
AI enabled Transvaginal Ultrasound diagnosis
Arm Type
Experimental
Arm Description
radiologists interpretTransvaginal Ultrasound images with the help of Artificial Intelligence algorithm
Intervention Type
Diagnostic Test
Intervention Name(s)
Artificial Intelligence Enabled Transvaginal Ultrasound Imaging algorithm
Other Intervention Name(s)
AI Enabled Transvaginal Ultrasound diagnosis
Intervention Description
AI Enabled Transvaginal Ultrasound diagnosis for ovarian cancer
Primary Outcome Measure Information:
Title
diagnostic accuracy
Description
diagnostic accuracy comparison between Transvaginal Ultrasound diagnosis with and without Artificial Intelligence algorithm for ovarian cancer
Time Frame
2 years
Secondary Outcome Measure Information:
Title
time cost for Transvaginal Ultrasound image interpretation
Description
time cost for radiologists to interpret Transvaginal Ultrasound images
Time Frame
2 years
10. Eligibility
Sex
Female
Minimum Age & Unit of Time
18 Years
Maximum Age & Unit of Time
80 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
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.
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
Qinglei Gao, MD, PhD
Phone
13871127473
Ext
13871127473
Email
qingleigao@hotmail.com
First Name & Middle Initial & Last Name or Official Title & Degree
Ding Ma, MD, PhD
Phone
13886090620
Ext
13886090620
Email
dingma424@126.com
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Qinglei Gao, MD, PhD
Organizational Affiliation
Tongji Hospital
Official's Role
Study Chair
12. IPD Sharing Statement
Plan to Share IPD
Yes
IPD Sharing Plan Description
contact Prof. Gao for detailed study protocol or data after the study completed by e-mail
IPD Sharing Time Frame
6 months after the study completed
IPD Sharing Access Criteria
all investigators in this study field can contact Prof. Gao for access by e-mail
Learn more about this trial
Detection of Ovarian Cancer Using an Artificial Intelligence Enabled Transvaginal Ultrasound Imaging Algorithm
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