The IMAGENDO® Study
Reducing the diagnostic delay of endometriosis through imaging
Endometriosis is a common condition. By the age of 44, 1 in 9 Australian women are diagnosed with endometriosis, a condition that caused 34,000 hospitalisations in 2016/17. Diagnosis is often delayed, with most women waiting an average of 7-12 years for diagnosis.
Currently, the recommendation for obtaining a diagnosis is to perform keyhole (laparoscopic) surgery to visualise endometrial deposits inside the abdomen, and then confirmed via microscopic examination. Surgery, however, can be problematic, difficult to access and is often associated with delays.
The IMAGENDO® study aims to reduce the need for surgery and the time it takes to receive a diagnosis. It will use machine learning to automatically digitally combine the diagnostic capabilities of pelvic scans and magnetic resonance imaging (MRI) to identify endometriosis lesions. Machine learning is an application of artificial intelligence (AI) that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed.