Skip to main content Health professionals need an accessible, effective diagnostic tool for endometriosis to reduce the mental and physical burden experienced by those it affects. Endometriosis is currently poorly reported on through standard transvaginal gynaecological ultrasound (TVUS) and magnetic resonance imaging (MRI) scans, because specialist skills are required to perform adequate endometriosis imaging.
These skills are in limited supply in Australia and in many developing countries. Consequently, the major barrier in accessing an endometriosis diagnosis is the current need for visualisation of endometriosis lesions at laparoscopic surgery. However, laparoscopy is expensive, geographically dependent, and poorly accessed in lower socioeconomic (SES) demographics.
IMAGENDO, led by the University of Adelaide aims to remove this surgical diagnostic barrier by developing a novel, accessible, cost-effective, non-invasive diagnostic tool for endometriosis. An Artificial Intelligence (AI) algorithm, combining the diagnostic capacity of specialist endometriosis TVUS (eTVUS) and endometriosis MRI (eMRI) scans, will:
- Reduce diagnostic delay
- Instigate prevention for infertility and chronic pain
- Reduce hospital admissions and laparoscopic surgery
- Improve mental health by validating patient’s pain experience
- Promote development of timely, targeted, effective treatments
The IMAGENDO project’s endometriosis imaging data will strengthen capabilities to deliver optimised endometriosis diagnostic and treatment pathways to primary healthcare workers. IMAGENDO combines globally recognised expertise in endometriosis, ultrasound, MRI, AI, epidemiology and clinical trials, with exclusive access to specialist eTVUS and eMRI scans from established partners in sonography, radiology and gynaecology. Australian surgeons, primary care practitioners, endometriosis community groups, researchers and clinicians have given their support to this study, ensuring national validation and uptake. IMAGENDO has the expertise and partnerships to deliver a new diagnostic tool for endometriosis to Australia.
We are designing a cloud-based diagnostic platform where diagnostic images are uploaded, interrogated, and reported using our AI-algorithm.
In addition, software embedded in ultrasound machines will provide immediate diagnostic risk assessment and assess imaging quality in real-time, improving performance and uptake of eTVUS.
There is potential for all Australian women with endometriosis to access this service, and health professionals to directly upload eTVUS and eMRI images to obtain a risk assessment for endometriosis from any global location. There is considerable community need and commercial potential for an AI-based diagnostic tool for endometriosis.
Get your patients involved
We are looking for women, 18 to 45 years, who are planning to have surgery for pelvic pain in the near future. We can then explore which diagnostic procedure you have undergone, and supplement your pre-diagnostic workup.
Participation may involve:
- Having an MRI scan (approx. 1 hour)
- Having a transvaginal ultrasound (approx. 1 hour)
- Completing two online questionnaires (approx. 10 mins)
This project has received Ethics approval from the University of Adelaide Human Research Ethics Committee (H-2020-051)
For further information, contact
Dr Jodie Avery
endostudy@adelaide.edu.au
0450 534 950
https://imagendo.org.au/