Skip to content

IMAGENDO: Diagnosing Endometriosis with Imaging and Artificial Intelligence

Non-invasive endometriosis diagnosis in women using machine learning

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ANZCTR
Registry ID
ACTRN12623000646640
Acronym
IMAGENDO
Enrollment
1452
Registered
2023-06-15
Start date
2020-11-05
Completion date
2025-06-30
Last updated
2025-09-08

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

None listed

Brief summary

Endometriosis is a chronic, inflammatory condition which can lead to chronic pelvic pain and infertility. There is no cure for this condition and the gold standard for diagnosis is laparoscopy (keyhole surgery) which is costly, has long wait times and is associated with risks. This study (Imagendo) will use artificial intelligence to create a diagnostic algorithm by analysing ultrasound and MRI endometriosis scans, providing general practitioners with an earlier, easily accessed, non-invasive, diagnosis of endometriosis.

Interventions

There are two study arms: Stage 1 - retrospective study - Women who have had an MRI or MRI and TV-US in the last 5 years will be contacted directly by mail by administration staff from our partner radiology and ultrasound clinics (including Benson Radiology, Specialist Imaging Partners, OmniGynaecare, O &G ) to obtain consent for these images and to follow up on any operation notes to confirm diagnosis. It is anticipated that it will take approximately 25 – 35 mins for the participant to comple

There are two study arms: Stage 1 - retrospective study - Women who have had an MRI or MRI and TV-US in the last 5 years will be contacted directly by mail by administration staff from our partner radiology and ultrasound clinics (including Benson Radiology, Specialist Imaging Partners, OmniGynaecare, O &G ) to obtain consent for these images and to follow up on any operation notes to confirm diagnosis. It is anticipated that it will take approximately 25 – 35 mins for the participant to complete their baseline data collection. Baseline data collection includes date of birth, height and weight, any previous surgery, any previous diagnostic imaging, Treating Specialist Doctor / Gynaecologist, Surgeon name and Hospital. Images and operation notes are de identified by admin staff from the clinic before being sent to the computer analysts. Participants will only need to read information and provide consent, and supply baseline information including date of birth, height and weight, any previous surgery, any previous diagnostic imaging, Treating Specialist Doctor / Gynaecologist, Surgeon name and Hospital. Once imaging and operation notes are received there will be no further observation. Images and medical history details will be entered into a machine learning algorithm designed specifically for this study. We will then compare the results from the algorithm to the documented diagnosis. Stage 2: After being identified as eligible for the study, if they haven’t already had one, women will be invited to undertake a transvaginal endometriosis ultrasound scan and/or an MRI at one of the imaging partners. These scans take less than an hour to complete. They will then attend a follow up interview with their Gynaecologist at least one week prior to their surgery, for 15 minutes who will explain the findings of the scans. They will also attend a review appointment within one month after their surgery with their Gynaecologist. Operation notes will be accessed by the study team after surgery. When consenting for the study, women will also be asked if they are willing to have their contact details including their name, date of birth, address, phone number, email address and treating specialist doctor entered on a secure electronic database and be contacted about future research questions that might arise from this project. It is anticipated that it will take approximately 25 – 35 mins for the participant to complete their baseline data collection. Baseline data collection includes date of birth, height and weight, any previous surgery, any previous diagnostic imaging, Treating Specialist Doctor / Gynaecologist, Surgeon name and Hospital. The observation period will end at the follow up review appointment post surgery.

Sponsors

Robinson Research Institute, University of Adelaide
Lead SponsorUniversity

Eligibility

Sex/Gender
All
Age
18 Years to 45 Years
Healthy volunteers
No

Inclusion criteria

Women with symptoms of endometriosis including: o Period paid o Other chronic pelvic pain o Fatigue o Dysmenorrhoea, o Dyspareunia, o Difficulty conceiving • Women do not need to have regular menstrual cycles, and can be taking oral contraceptive or have a Mirena in place

Exclusion criteria

• Women with cancer • Women with bowel conditions such as Crohn’s Disease or Ulcerative Colitis • Postmenopausal women • Women with an intellectual disability/inability to give informed consent

Outcome results

None listed

Source: ANZCTR · Data processed: Aug 31, 2026