Clinical trial · Observational
Assessment of Ovarian Cysts Using Machine Learning
Prediction of Malignant Potential of Ovarian Cysts Using Machine Learning Models
NCT05342298CI-TRIAL-00060488OCIDunknownClinicalTrials.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)
The study aims at creating a prediction model using machine learning algorithms that is capable of predicting malignant potential of ovarian cysts/masses based on patient characteristics, sonographic findings, and biochemical markers
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 Cyst | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| prediction model | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (1)
- measure
- Final diagnosis of ovarian cyst type
- timeFrame
- Within 3 years of diagnosis of ovarian cyst
- description
- Diagnosis of whether the cyst is benign or malignant based on histopathology, or cyst resolution or shrinkage on follow-up
Secondary outcomes (1)
- measure
- Incidence of acute events during follow-up and prior to final diagnosis.
- timeFrame
- Within 3 years of diagnosis of ovarian cyst
- description
- Incidence of ovarian torsion, cyst rupture and intra-abdominal hemorrhage requiring surgical intervention
Eligibility
Eligibility (as posted)
- Sex
- Female
- Minimum age
- 15 Years
- Maximum age
- 80 Years
Show eligibility criteria text
Inclusion Criteria: Females who are postmenarchal, have documented follow-up for at least 1 year following initial presentation unless surgically managed, and provide authorization to use their medical records for research purposes. They should have received their care in the receptive centers Exclusion Criteria: Women will be excluded from the study if they were admitted for an acute event including cyst torsion, rupture or hemorrhage with no prior documentation of ovarian cysts. Women with cysts smaller than 3 cm will not be eligible.
References
Publications (6)
- BACKGROUNDRoss EK, Kebria M. Incidental ovarian cysts: When to reassure, when to reassess, when to refer. Cleve Clin J Med. 2013 Aug;80(8):503-14. doi: 10.3949/ccjm.80a.12155. PMID 23908107
- BACKGROUNDMobeen S, Apostol R. Ovarian Cyst. 2023 Jun 5. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2026 Jan-. Available from http://www.ncbi.nlm.nih.gov/books/NBK560541/ PMID 32809376
- BACKGROUNDBoos J, Brook OR, Fang J, Brook A, Levine D. Ovarian Cancer: Prevalence in Incidental Simple Adnexal Cysts Initially Identified in CT Examinations of the Abdomen and Pelvis. Radiology. 2018 Jan;286(1):196-204. doi: 10.1148/radiol.2017162139. Epub 2017 Sep 14. PMID 28914598
- BACKGROUNDFarghaly SA. Current diagnosis and management of ovarian cysts. Clin Exp Obstet Gynecol. 2014;41(6):609-12. PMID 25551948
- BACKGROUNDShazly, S.; Laughlin-Tommaso, S.K. Ovarian Tumors. In Gynecology: A CREOG and Board Exam Review; Springer International Publishing: Cham, Switzerland, 2020; pp. 489-519.
- BACKGROUNDMehasseb MK, Siddiqui NA, Bryden F. The Management of Ovarian Cysts in Postmenopausal Women. Royal College of Obstetricians and Gynaecologist. RCOG Green-top Guideline. 2016;34:1-31.