Endometrial Carcinoma
Conditions
Brief summary
This study evaluates if AI can be used with transvaginal ultrasound images for early detection of endometrial cancer or premalignant lesions.
Detailed description
PRIMARY OBJECTIVE: I. Prospective validation of an artificial intelligence (AI) algorithm applied to transvaginal ultrasound (TVUS) to identify patients with premalignant/malignant in a population of women with postmenopausal bleeding (PMB). OUTLINE: This is an observational study. Patients undergo a transvaginal ultrasound examination and endometrial sampling per standard of care and have their medical records reviewed on study.
Interventions
OTHERNon-Interventional Study
Non-Interventional Study
Sponsors
Mayo Clinic
Study design
Observational model
CASE_ONLY
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
FEMALE
Age
55 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Age ≥ 55 years * At least one episode of postmenopausal bleeding (PMB) * Endometrial biopsy available from at Mayo Clinic (MN, AZ, FL), Mayo Clinic Health System (MCHS), or an external institution * Acceptance to participate in the study
Exclusion criteria
* Diagnostic tests performed more than 90 days apart * Physical impediment/refusal to undergo transvaginal ultrasound (TVUS)
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Accuracy of artificial intelligence (AI) algorithm applied to transvaginal ultrasound (TVUS) | Baseline | Two static TVUS images (one longitudinal, one transversal) will be independently validated and compared to results of endometrial sampling. Outcomes from these will be compared with predictions made by the AI models for accuracy of assessing premalignant/malignant disease. |
Countries
United States
Contacts
CONTACTClinical Trials Referral Office
PRINCIPAL_INVESTIGATORGretchen E Glaser, MD
Mayo Clinic in Rochester
Outcome results
None listed