Non-Invasive Identification of Endometrial Cancer/Endometrial Atypical Hyperplasia With an AI-Based Classifier Applied to Transvaginal Ultrasound in Patients With Post-Menopausal Bleeding
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.
Arms & interventions
- OtherNon-Interventional Study
Non-Interventional Study
Outcome measures
Primary
Accuracy of artificial intelligence (AI) algorithm applied to transvaginal ultrasound (TVUS)
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.
Time frame: Baseline
Eligibility criteria
Study locations (3)
Mayo Clinic in Arizona
Scottsdale, Arizona, 85259
Mayo Clinic in Florida
Jacksonville, Florida, 32224-9980
Mayo Clinic in Rochester
Rochester, Minnesota, 55905