Non-Invasive Identification of Endometrial Cancer/Endometrial Atypical Hyperplasia With an AI-Based Classifier Applied to Transvaginal Ultrasound in Patients With Post-Menopausal Bleeding

Non-Invasive Identification of Endometrial Cancer/Endometrial Atypical Hyperplasia With an AI-Based Classifier Applied to Transvaginal Ultrasound in Patients With Post-Menopausal Bleeding

This study evaluates if AI can be used with transvaginal ultrasound images for early detection of endometrial cancer or premalignant lesions.

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.

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)