Harnessing AI to revolutionise endometriosis diagnosis

A doctor analysing an ultrasound image

An interdisciplinary research team are using ground-breaking AI technologies to make the historically fraught process of endometriosis diagnosis faster, more cost-effective, and less invasive with IMAGENDO®

Endometriosis affects hundreds of millions of people globally and nearly a million Australians. The condition, which occurs when tissues similar to the lining of the uterus grow outside the womb, can cause pelvic inflammation, headaches, fatigue, and even infertility. The debilitating pain can affect ability to work, relationships, fitness, education and mental health. And yet, despite its undeniable toll, pathways to diagnosis and treatment remain slow, expensive, and invasive. University of Adelaide researchers are working to improve endometriosis care with a new technology called IMAGENDO®

Currently, the wait time for diagnosis averages more than six years from symptom onset. Painful symptoms are often overlooked or normalized, and the most common diagnostic tool, a keyhole surgery, is costly and intrusive. 

Two University of Adelaide research institutes – the Robinson Research Institute and the Australian Institute for Machine Learning – are harnessing the emergent power of artificial intelligence (AI) to revolutionise endometriosis diagnosis. By combining ultrasound, magnetic resonance imaging (MRI), and AI, the researchers aim to make IMAGENDO® a cost-effective, accessible, and accurate new way to diagnose the condition without surgery.

Professor Louise Hull, a gynaecologist and fertility specialist at the Robinson Research Institute leads the IMAGENDO® project. She saw an opportunity to do better for patients by using less invasive specialist scans such as transvaginal ultrasounds and gynaecological MRIs, which have the potential to detect diagnostic markers of endometriosis.

“A non-invasive imaging diagnosis means people can explore different treatment options for best care, including non-invasive options such as physiotherapy and medications,” she says.

Program manager Dr Jodie Avery predicts IMAGENDO® will lead to earlier endometriosis diagnosis and timely treatment that improves outcomes for patients. 

“Endometriosis symptoms can have a devastating impact on women’s lives, but an earlier diagnosis enabled by the IMAGENDO® technology will lead to prompt treatment and better quality of life by avoiding unnecessary hospitalizations and repetitive surgery.” Dr Jodie Avery, Program manager

“[Earlier diagnosis] provides an opportunity to manage and treat pain appropriately to prevent complications and to preserve fertility via egg freezing and fertility planning.” 

Interpreting images from IMAGENDO® takes a niche skillset, so Hull and her team are collaborating with the University of Adelaide’s Australian Institute for Machine Learning to overcome this potential workforce challenge. 

“Endometriosis scanning is a specialist skill and not all sonographers, radiologists and gynaecologists will have the opportunity to receive training to perform specialist endometriosis scans or MRIs,” says Professor Hull.

“Fortunately, we have a solution to this potential obstacle.”

Using a diagnostic dataset of ultrasounds provided by endometriosis expert Associate Professor George Condous, and MRIs from Benson Radiology and South Australian Medical Imaging (SAMI) as a training sample, the researchers built a program that uses AI to read specialist scans. After learning from a large number of ultrasounds and MRIs, the program’s algorithm is able to recognise certain endometriosis imaging markers. 

Initial tests show the software’s diagnostic accuracy is similar to that of a specialist endometriosis doctor, and the IMAGENDO® team expect it to improve even further as the machine learning training continues. 

The IMAGENDO® team is aiming to make the algorithm available for clinical use in the next two to five years after thorough testing and approval.

What’s next? 

IMAGENDO® is increasingly recognised globally for its use of AI in analysing data from ultrasound and MRI scans to diagnose endometriosis. The program is expanding across Australia and internationally with collaborations in North America, South America, Southeast Asia, the United Kingdom, and Europe.

The breakthrough at the University of Adelaide is part of a rapidly evolving global movement in which AI is being used in conjunction with medical imaging technologies to transform patient outcomes. With these innovations accelerating, IMAGENDO® is just the beginning of a new healthcare frontier. 

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