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Developing an US-MRI Biomarker Fusion Model for Endometriosis

Developing an US-MRI Biomarker Fusion Model for Endometriosis (DEFEND)

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT04974710
Acronym
DEFEND
Enrollment
100
Registered
2021-07-23
Start date
2022-03-18
Completion date
2023-03-31
Last updated
2026-05-28

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

Conditions

Endometriosis, Reproductive System Disorder

Keywords

Reproductive health, Diagnostics, Magnetic Resonance Imaging, Ultrasound, Biomarkers

Brief summary

Single centre, prospective, observational, cohort study looking to develop a database representing the variability of disease and imaging seen in women with clinically diagnosed endometriosis, awaiting laparoscopic surgery.

Detailed description

In the United Kingdom (UK), endometriosis is one of the most common gynaecological diseases needing treatment. The prevalence of disease is often underestimated, however it is believed to affect at least 1 in 10 women in the UK. Within the NHS, endometriosis costs the UK economy approximately £8.2 billion a year in treatment, loss of work and healthcare costs. Currently, the first diagnostic recommendation for endometriosis is and Ultrasound (US) scan or a MRI, followed by a diagnostic surgery called laparoscopy. Accurate diagnoses is usually limited to specialist tertiary centres, therefore a delayed diagnosis is a significant problem for women with endometriosis. Limited experience in the disease area can also lead to misdiagnosis and the latest report from the National Institute of Clinical Excellence (NICE) reports a time delay of around 7.5 years before a confirmed diagnosis of endometriosis. A model that could accurately predict surgical findings of endometriosis would be of significant clinical and economical benefit. The main aim of this study is to curate a database of patients with varying levels of endometriosis. This database will contain fully anonymised MR and US images alongside clinical data for further use in research. There will be no intervention outside of standard of care. US and clinical data will be collected during routine visits and patients will be offered an additional visit to have a MRI. The ultimate aim is to then use this data to develop a widely available diagnostic tool based on MRI and US imaging modalities using computer modelling. Validating the predictive model with surgical findings will increase confidence and access to advanced imaging for non-experts, allowing clinicians to accurately predict surgical findings as well as reduce time to diagnosis.

Interventions

DIAGNOSTIC_TESTOutpatient MRI

All participants will undergo a standardised imaging protocol in a MRI scanner. This will take place during the same visit or following the transvaginal ultrasound (TVUS) and in advance of any surgical procedure (laparoscopy).

Sponsors

Perspectum
Lead SponsorINDUSTRY
GE Healthcare
CollaboratorINDUSTRY

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
FEMALE
Age
18 Years to 40 Years
Healthy volunteers
No

Inclusion criteria

* Women aged between 18-40 years * Clinically diagnosed endometriosis and awaiting surgery * BMI 20-35 kg/m2 * No past abdominal surgical history * Participant willing and able to give informed consent for participation in the study

Exclusion criteria

* Previous surgery in 12 months prior to consent: * abdominal surgery * surgery for endometriosis * The participant may not enter the study if they have any contraindication to magnetic resonance imaging (standard MR

Design outcomes

Primary

MeasureTime frame
Build a database of 100 patients with endometriosis, awaiting confirmatory laparoscopic surgery on to an anonymised database for future use in algorithm development.12 months

Secondary

MeasureTime frameDescription
Evaluate inter-observer variability in diagnosing and staging endometriosis using both two and three dimensional ultrasound by computing inter-rater agreement statistics (e.g. Kappa statistic)12 months
Assess the utility multi-parametric MRI in diagnosing and staging endometriosis12 monthsUsing measurements such as cT1, PDFF and Diffusion Weighted Imaging (DWI) to the MR imaging variables with a clinical diagnosis.

Countries

United Kingdom

Contacts

PRINCIPAL_INVESTIGATORIppokratis Sarris, BM, BCh

King's Fertility

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: May 29, 2026