Study may see end of need for invasive endometriosis diagnosis surgery
pharmafile | March 8, 2022 | News story | Manufacturing and Production |
A new study of women living with endometriosis is underway, exploring the potential of Artificial intelligence (AI), and cutting-edge medical scanning techniques, in order to diagnose women earlier without invasive surgery.
The study is funded by the National Consortium of Intelligent Medical Imaging (NCIMI) and is being carried out by a partnership between King’s Fertility, Perspectum, and GE Healthcare. The DEFEND study is now recruiting patients, with researchers aiming to recruit up to 100 patients who are experiencing the condition at King’s Fertility clinic.
“I’m really excited that the first Defend patients have been recruited. Endometriosis is such a poorly diagnosed condition, affecting 10-33% of women of reproductive age in the UK,” commented Chief Investigator Dr Ippokratis Sarris, Consultant in Reproductive Medicine and Director of King’s Fertility. “Despite endometriosis being such a common condition, delayed diagnosis is a significant problem as symptoms often overlap with other conditions and can lead to infertility.”
Endometriosis affects one in 10 women in the UK of childbearing age. Those living with the condition may experience significant pelvic and abdominal pain menstruation, painful intercourse, and spontaneous pain outside of menstruation. This collection of symptoms means that a definitive diagnosis involves invasive surgery, called laparoscopy, a keyhole surgery into the abdomen under general anaesthetic.
“Currently, diagnosis using conventional imaging techniques isn’t always possible, with key-hole surgery (known as a laparoscopy) being the present ‘gold standard’ way to reach a definitive diagnosis,” elaborated Dr Ippokratis Sarris. “However, this is an invasive procedure, meaning that it can either lead to years of uncertainty for those that have endometriosis but are reluctant to have surgery, or unnecessary surgery for those that are eventually shown not to have endometriosis. Our sincere hope is that this study will bring about the development of an algorithm to enable diagnosis through minimally invasive approaches; this would be a huge step forward for women with endometriosis symptoms.”
The DEFEND study will explore the effectiveness of using 2D and 3D ultrasound and MRI scanning to diagnose the condition, aiming to create a database of ultrasound and MRI images, along with clinical symptoms and medical history, for those with a diagnosis or symptoms of endometriosis.
These images will then be analysed for the potential development of computer algorithms, to read images and harness the power of AI, so that endometriosis might be better diagnosed and managed.
Ana Ovey
