Ovarian Cancer
Conditions
Keywords
Ovarian cancer, Radiomics, CT, Prognosis, Epithelial ovarian cancer, Biomarkers
Brief summary
When patients have suspected or confirmed ovarian cancer standard treatment will involve surgery and chemotherapy. However, as with any treatment, it is challenging to predict treatment response in advance. Before treatment, all patients have a CT scan to describe where the cancer is in order to guide the treatment. There is now a new way to analyse routine scans using advanced computing methods, which may give more information about the ovarian cancer. This is called radiomics which analyses features in scans that are not visible to the naked eye. Our group at Imperial College London has worked on developing radiomic models to better understand ovarian cancer. This study aims to determine whether the information gained from this new approach would help us to tailor patient treatment plans to better meet the patient's individual needs, even more than done already. Furthermore, the aim is to understand how different types of ovarian cancer can correlate with the radiomic findings, which may help develop potential treatments in the future.
Interventions
None listed
Sponsors
National Cancer Center, Korea
Imperial College Healthcare NHS Trust
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
FEMALE
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Written (signed and dated) informed consent * Age 18 years or over * Suspected or confirmed advanced epithelial ovarian cancer (FIGO stage 3B or more) * Being considered for active anticancer treatment i.e. primary cytoreductive surgery followed by chemotherapy or neoadjuvant chemotherapy followed by interval cytoreductive surgery * Evaluable baseline portal venous phase CT scan prior to surgical or medical treatment for ovarian cancer * Disease visible on pre-treatment portal venous phase baseline CT scan (≥2cm)
Exclusion criteria
* Known contra-indication to CT with IV contrast (e.g. contrast allergy, renal failure, inability to lie flat); * Unable to give informed consent; * Known pregnancy; * No visible disease \<2cm on portal venous phase baseline CT scan; * Previous surgery for resection of an adnexal mass; * Significant artefact on CT image for example from metal prostheses that precluded meaningful segmentation of visible disease * Only fit for palliative care at initial presentation
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Comparison of CT-based Radiomics Models and Clinical Model in Predicting Progression-Free Survival Post-Cytoreductive Surgery in Ovarian Cancer | From enrolment to approximately 5 years after the last patient is enrolled, based on the final data capture at the end of follow-up. | Comparison of each CT-based radiomics model concordance index to predict progression free survival against the clinical model following cytoreductive surgery in the primary or interval setting. Comparisons: i. Manual CT radiomics model to the clinical model alone ii. Automated CT radiomics model to the clinical model alone |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Comparison of CT-Radiomics Models and Clinical Model in Predicting Overall Survival Post-Cytoreductive Surgery in Ovarian Cancer | From enrolment to approximately 5 years after the last patient is enrolled, based on the final data capture at the end of follow-up. | Comparison of each CT-based radiomics model concordance index to predict overall survival against the clinical model following cytoreductive surgery in the primary or interval setting. Comparisons: i. Manual CT radiomics model to the clinical model alone ii. Automated CT radiomics model to the clinical model alone |
Other
| Measure | Time frame | Description |
|---|---|---|
| Correlating radiomics model with BRCA and HRD | From enrolment to approximately 5 years after the last patient is enrolled, based on the final data capture at the end of follow-up. | Correlation of each radiomics model with clinically approved biomarkers BRCA and HRD status in advanced epithelial ovarian cancer. |
| Radiogenomic evaluation | From enrolment to approximately 5 years after the last patient is enrolled, based on the final data capture at the end of follow-up. | Evaluate the biological basis for different thresholds of radiomic scores (manual and automated) using molecular analysis of fresh tumour specimens and blood samples. |
Countries
United Kingdom
Contacts
Primary ContactChristina Fotopoulou, MD, PhD
Outcome results
None listed