Can Staging Magnetic Resonance Imaging (MRI) Features Prognosticate Patients Presenting With Endometrial Cancer?

NCT03543215 | Unknown

• 1 other identifier: 16HH3687 Radiomics EC
• Study Type: observational
• Target: 500
• Locations: 1 country
• Sites: 1

Brief Summary

Aim: Assess the value of MRI features in predicting prognosis in patients with endometrial cancer This study will examine the MRI features of women with confirmed endometrial cancer to see if textural features can prognosticate patients.

Conditions

Endometrial Cancer; Endometrial Neoplasms

Keywords

MRI; Radiomics; Texture features; Prognostication; Endometrial cancer

Outcome Measures

Primary Outcomes (1)

• To assess the value of MRI features in predicting prognosis in patients with endometrial cancer using progression free survival (PFS) and overall survival (OS) as end points

  Assess features of pelvic MRIs (including (i) tumour image intensity, (II) shape, (III) texture and (IV) multiscale wavelet) and create a mathematical algorithm to predict prognostic outcome (5 year survival).

  8 years (3 year data collection and 5 year follow up).

Secondary Outcomes (1)

• Assess the correlation between imaging features and histopathological features.

  3 years

Interventions

Radiomics: Analysis of textural features of imaging (MRI and Ultrasound) OTHER

All patients with confirmed endometrial cancer will have received Ultrasound and MRI as part of routine standard of care. Textural features from this will be analysed to see if can predict prognosis.

Eligibility Criteria

• Age: 18 Years+
• Gender Eligibility Details: Study is on endometrial cancer
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

All patients reviewed at the Specialist Gynaecology Oncology MDT at ICHNT with a diagnosis of endometrial cancer

You may qualify if:

• All women presenting with a confirmed diagnosis of endometrial cancer
• Reviewed at the Specialist Gynaecology Oncology MDT
• Have MR Imaging and Hysterectomy specimens available for review.

You may not qualify if:

• Anyone lacking capacity.
• \<18years old.
• Pregnant.
• No MR Imaging available for review -- No pathology specimen available for review

Sponsors & Collaborators

• Imperial College London: lead

Study Sites (1)

Queen Charlotte and Hammersmith Hospital

London, W12 0HS, United Kingdom

RECRUITING

Related Publications (1)

• Li X, Marcus D, Russell J, Aboagye EO, Ellis LB, Sheeka A, Park WE, Bharwani N, Ghaem-Maghami S, Rockall AG. Weibull parametric model for survival analysis in women with endometrial cancer using clinical and T2-weighted MRI radiomic features. BMC Med Res Methodol. 2024 May 9;24(1):107. doi: 10.1186/s12874-024-02234-1.

  PMID: 38724889 DERIVED

MeSH Terms

Conditions

Endometrial Neoplasms

Interventions

Magnetic Resonance Spectroscopy; High-Energy Shock Waves

Condition Hierarchy (Ancestors)

Uterine Neoplasms; Genital Neoplasms, Female; Urogenital Neoplasms; Neoplasms by Site; Neoplasms; Uterine Diseases; Genital Diseases, Female; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Genital Diseases

Intervention Hierarchy (Ancestors)

Spectrum Analysis; Chemistry Techniques, Analytical; Investigative Techniques; Ultrasonic Waves; Sound; Radiation, Nonionizing; Radiation; Physical Phenomena

Central Study Contacts

Diana Marcus, MB BS

CONTACT

020 7589 5111; d.marcus16@imperial.ac.uk

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: June 30, 2017
• First Posted: June 1, 2018
• Study Start: July 13, 2017
• Primary Completion: December 10, 2021
• Study Completion: December 10, 2025
• Last Updated: February 12, 2021

Record last verified: 2021-02

Data Sharing

• IPD Sharing: Will not share

Locations

GB (1)