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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

Recruiting
55 years and older
Female
Phase N/A
  • Technical (Original)
  • Simplified (AI rewritten)

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Overview

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

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.

Eligibility

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)

Study details
    Endometrial Carcinoma

NCT06365905

Mayo Clinic

14 May 2026

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