Clinical trial · Interventional
Detection of Ovarian Cancer Using an Artificial Intelligence Enabled Transvaginal Ultrasound Imaging Algorithm
NCT04214782CI-TRIAL-00054339unknownN/AClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
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
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Ovarian Cancer | Malignant Ovarian Neoplasm | CURATED_EXACT | 0.92 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Artificial Intelligence Enabled Transvaginal Ultrasound Imaging algorithm | Diagnostic Test | — | UNRESOLVED |
Design
Arms and outcomes
Arms (2)
- type
- NO_INTERVENTION
- label
- Transvaginal Ultrasound diagnosis
- description
- radiologists interpretTransvaginal Ultrasound images without the help of Artificial Intelligence (AI) algorithm
- type
- EXPERIMENTAL
- label
- AI enabled Transvaginal Ultrasound diagnosis
- description
- radiologists interpretTransvaginal Ultrasound images with the help of Artificial Intelligence algorithm
- interventionNames
- Diagnostic Test: Artificial Intelligence Enabled Transvaginal Ultrasound Imaging algorithm
Primary outcomes (1)
- measure
- diagnostic accuracy
- timeFrame
- 2 years
- description
- diagnostic accuracy comparison between Transvaginal Ultrasound diagnosis with and without Artificial Intelligence algorithm for ovarian cancer
Eligibility
Eligibility (as posted)
- Sex
- Female
- Minimum age
- 18 Years
- Maximum age
- 80 Years
Show eligibility criteria text
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.
References
Publications (0)
Data not yet available
No reference posted for this study.