Chief Investigator: Dr Ippokratis Sarris, Consultant in Reproductive Medicine and Director of King’s Fertility.
Research fellow in charge: Dr Laura Ismail
Funding: The study is funded by the National Consortium of Intelligent Medical Imaging (NCIMI)and is being executed by a partnership between King’s Fertility, Perspectum and GE Healthcare.
DEFEND (Developing an US-MRI-biomarker fusion model for Endometriosis) is a study of women with endometriosis to explore the potential of Artificial Intelligence (AI) and cutting-edge medical scanning techniques in diagnosing women earlier without going through invasive surgery.
Endometriosis is a common condition affecting one in ten women in the UK of childbearing age. Women living with endometriosis may have to put up with significant pelvic and abdominal pain during menstruation, painful intercourse and pain outside menstruation.In some cases, it can lead to problems with fertility. Between 30-50% of women seeking help for infertility are diagnosed with endometriosis.
An All Party Parliamentary Group Report on Endometriosis revealed that women with endometriosis are facing serious delays to diagnosis with nearly two thirds visiting their GP over ten times, a quarter visiting doctors in hospitals ten times or more and over half ending up in A&E due to their pain. According to the report, it takes eight years on average from onset of symptoms to receiving a diagnosis, the same length of time as it did a decade ago, highlighting an urgent need for investment in research to drive down this time and ensure appropriate access to care when women need it.3
Endometriosis is a clinical condition, initially diagnosed based on a collection of symptoms. A definitive diagnosis of endometriosis involves invasive surgery called laparoscopy (keyhole surgery into the abdomen under general anaesthetic). Ultrasound and magnetic resonance imaging (MRI) can be used to help diagnose the condition. However, ultrasound is not always reliable for all types of endometriosis and MRI is reserved for severe disease where bowel and bladder symptoms are present – added to which there is no single standardised MRI scanning protocol that currently provides all the information required for a definitive diagnosis.,The Defend study will explore the effectiveness of using 2D and 3D ultrasound and MRI scanning. It aims to create a database of ultrasound and MRI images, along with clinical symptoms and medical history, for women with a diagnosis or symptoms of endometriosis. These images will be analysed to enable the potential development of computer algorithms to read images and harness the power of AI to better diagnose and manage women with endometriosis in the future.4