Ovarian CancerNCT04214782
Detection of Ovarian Cancer Using an Artificial Intelligence Enabled Transvaginal Ultrasound Imaging Algorithm
A study testing Artificial Intelligence Enabled Transvaginal Ultrasound Imaging algorithm in people with Ovarian Cancer, run by Tongji Hospital.
Trial 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… Read more about this study
- Who is it for?
- Ages 18 to 80 years, women only
- Conditions the study is for
- Ovarian Cancer
- What is being tested?
- Artificial Intelligence Enabled Transvaginal Ultrasound Imaging algorithm
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 10,000 participants
- Where
- No sites listed yet
- Study dates
- 1 Oct 2022to 1 Oct 2024
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 80 years
- Women only
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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.
Who cannot join
- 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.
Trial locations and contacts
No sites are listed yet.
About this study
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.
- Conditions
- Ovarian Cancer
- Being tested
- Artificial Intelligence Enabled Transvaginal Ultrasound Imaging algorithm
- Medical subject headings
- Ovarian Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial Intelligence Enabled Transvaginal Ultrasound Imaging algorithmDiagnostic test
Also called AI Enabled Transvaginal Ultrasound diagnosis
AI Enabled Transvaginal Ultrasound diagnosis for ovarian cancer
| Study group | Role | What they receive |
|---|---|---|
| Transvaginal Ultrasound diagnosis | No intervention | radiologists interpretTransvaginal Ultrasound images without the help of Artificial Intelligence (AI) algorithm |
| AI enabled Transvaginal Ultrasound diagnosis | Experimental | radiologists interpretTransvaginal Ultrasound images with the help of Artificial Intelligence algorithm Receives: Diagnostic Test: Artificial Intelligence Enabled Transvaginal Ultrasound Imaging algorithm |
What is being measured
The primary outcome is the main question the study is designed to answer.
diagnostic accuracy
diagnostic accuracy comparison between Transvaginal Ultrasound diagnosis with and without Artificial Intelligence algorithm for ovarian cancer
Measured: 2 years
Secondary outcomes (1)
time cost for Transvaginal Ultrasound image interpretation
time cost for radiologists to interpret Transvaginal Ultrasound images
Measured: 2 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted2 Jan 2020
- Study start1 Oct 2022 (estimated)
- Primary completion1 Oct 2023 (estimated)
- Study completion1 Oct 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Ovarian CancerStudies of the same condition, open and under way.
- More trials run by Tongji HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind
- Who is masked
- Participant, Outcomes assessor
- Enrolment
- 10,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Tongji Hospital
- Sponsor type
- University, hospital or other
- 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
- Responsible party
- Principal investigator, Qinglei Gao, Tongji Hospital
- Investigators
- Qinglei Gao, MD, PhD, Study chair, Tongji Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04214782
- Sponsor's protocol ID
- 2019-TJ-OVAB
- Status last verified
- Oct 2021
- First submitted
- 28 Dec 2019
- Last updated
- 7 Oct 2021
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: contact Prof. Gao for detailed study protocol or data after the study completed by e-mail
Study at a glance
From the registry record, last updated by the sponsor on 7 Oct 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Detection of Ovarian Cancer Using an Artificial Intelligence Enabled Transvaginal Ultrasound Imaging Algorithm
- ClinicalTrials.gov ID
- NCT04214782
- Acronym / sponsor ID
- 2019-TJ-OVAB
- Conditions
- Ovarian Cancer
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 10,000 participants (estimated)
- Lead sponsor
- Tongji HospitalUniversity, hospital or other
- 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
- Study start
- 1 Oct 2022 (estimated)
- Primary completion
- 1 Oct 2023 (estimated)
- Study completion
- 1 Oct 2024 (estimated)
- First posted
- 2 Jan 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (participant, outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Transvaginal Ultrasound diagnosis | No intervention | –radiologists interpretTransvaginal Ultrasound images without the help of Artificial Intelligence (AI) algorithm |
| AI enabled Transvaginal Ultrasound diagnosis | Experimental | Diagnostic Test: Artificial Intelligence Enabled Transvaginal Ultrasound Imaging algorithmradiologists interpretTransvaginal Ultrasound images with the help of Artificial Intelligence algorithm |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- 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.
Key exclusion criteria (5 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Artificial Intelligence Enabled Transvaginal Ultrasound Imaging algorithmAlso: AI Enabled Transvaginal Ultrasound diagnosisAI Enabled Transvaginal Ultrasound diagnosis for ovarian cancer | Diagnostic test | AI enabled Transvaginal Ultrasound diagnosis |
Primary outcome
diagnostic accuracy
Time frame: 2 years
diagnostic accuracy comparison between Transvaginal Ultrasound diagnosis with and without Artificial Intelligence algorithm for ovarian cancer
1 secondary outcome
time cost for Transvaginal Ultrasound image interpretation
Time frame: 2 years
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 7 Oct 2021.
- Individual participant dataSharing planned: Yes. contact Prof. Gao for detailed study protocol or data after the study completed by e-mail
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Qinglei Gao, MD, PhD study chair
Tongji Hospital
Questions about this trial
What is this clinical trial studying?
A study testing Artificial Intelligence Enabled Transvaginal Ultrasound Imaging algorithm in people with Ovarian Cancer, run by Tongji Hospital.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 7 Oct 2021. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Qinglei Gao, MD, PhD (13871127473 ext. 13871127473, qingleigao@hotmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
diagnostic accuracy (time frame: 2 years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 7 Oct 2021.