Ovarian CancerORACLENCT06817174
Ovarian Cancer Radiomics Approach in CT Led Evaluation
An observational study of Ovarian Cancer, run by Imperial College Healthcare NHS Trust at 1 site in United Kingdom.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and older, women only
- Conditions the study is for
- Ovarian Cancer
- How many people
- 168 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 10 Feb 2025to Jan 2032
- How long will I take part?
- 5 Years
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- Women only
- No healthy volunteers
- Adult, Older adult
Study population: The study population will consist of patients from Imperial College Healthcare Trust, London, UK and National Cancer Centre, Korea, diagnosed with ovarian masses suspected or confirmed as advanced epithelial ovarian cancer. Participants must be medically fit to undergo the combination of cytoreductive surgery and platinum-based chemotherapy, as part of their standard anticancer treatment.
Who may be able to join
- 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)
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United Kingdom1 site, 1 recruiting
- Recruiting
Imperial College NHS Healthcare Trust
London
Christina Fotopoulou, MD, PhD, +44 (0)20 3313 3274, c.fotopoulou@imperial.ac.uk
About this study
Official title: Prospective Validation of CT Based Radiomic Models to Predict Surgical and Clinical Outcomes in Advanced Epithelial Ovarian Cancer
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.
- Conditions
- Ovarian Cancer
- Keywords
- Ovarian cancer, Radiomics, CT, Prognosis, Epithelial ovarian cancer, Biomarkers
- Medical subject headings
- Ovarian Neoplasms, Carcinoma, Ovarian Epithelial
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Suspected / confirmed advanced epithelial ovarian cancer | Not described |
What is being measured
The primary outcome is the main question the study is designed to answer.
Comparison of CT-based Radiomics Models and Clinical Model in Predicting Progression-Free Survival Post-Cytoreductive Surgery in Ovarian Cancer
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:
- Manual CT radiomics model to the clinical model alone ii. Automated CT radiomics model to the clinical model alone
Measured: From enrolment to approximately 5 years after the last patient is enrolled, based on the final data capture at the end of follow-up.
Secondary outcomes (1)
Comparison of CT-Radiomics Models and Clinical Model in Predicting Overall Survival Post-Cytoreductive Surgery in Ovarian Cancer
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:
- Manual CT radiomics model to the clinical model alone ii. Automated CT radiomics model to the clinical model alone
Measured: From enrolment to approximately 5 years after the last patient is enrolled, based on the final data capture at the end of follow-up.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted10 Feb 2025
- Study start10 Feb 2025
- Primary completionJan 2032 (estimated)
- Study completionJan 2032 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for Ovarian CancerStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 168 participants (estimated)
- Target duration
- 5 Years
Sponsor and investigators
- Lead sponsor
- Imperial College Healthcare NHS Trust
- Sponsor type
- University, hospital or other
- Collaborators
- National Cancer Center, Korea
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06817174
- Sponsor's protocol ID
- 25/SC/0032
- Acronym
- ORACLE
- Status last verified
- Jun 2025
- First submitted
- 4 Feb 2025
- Last updated
- 27 Jun 2025
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Kristofer Linton-Reid, Georg Wengert, Haonan Lu, Christina Fotopoulou, Philippa Lee, Federica Petta, Luca Russo, Giacomo Avensani, Murbarik Arshard, Philipp Harter, Mitch Chen, Marc Boubnovski, Sumeet Hindocha, Ben Hunter, Sonia Prader, Joram M. Posma, Andrea Rockall, Eric O. Aboagye. End-to-End Integrative Segmentation and Radiomics Prognostic Models Improve Risk Stratification of High-Grade Serous Ovarian Cancer: A Retrospective Multi-Cohort Study. medRxiv 2023.04.26.23289155; doi: https://doi.org/10.1101/2023.04.26.23289155
Fotopoulou C, Rockall A, Lu H, Lee P, Avesani G, Russo L, Petta F, Ataseven B, Waltering KU, Koch JA, Crum WR, Cunnea P, Heitz F, Harter P, Aboagye EO, du Bois A, Prader S. Validation analysis of the novel imaging-based prognostic radiomic signature in patients undergoing primary surgery for advanced high-grade serous ovarian cancer (HGSOC). Br J Cancer. 2022 Apr;126(7):1047-1054. doi: 10.1038/s41416-021-01662-w. Epub 2021 Dec 18.
PubMed 34923575Lu H, Arshad M, Thornton A, Avesani G, Cunnea P, Curry E, Kanavati F, Liang J, Nixon K, Williams ST, Hassan MA, Bowtell DDL, Gabra H, Fotopoulou C, Rockall A, Aboagye EO. A mathematical-descriptor of tumor-mesoscopic-structure from computed-tomography images annotates prognostic- and molecular-phenotypes of epithelial ovarian cancer. Nat Commun. 2019 Feb 15;10(1):764. doi: 10.1038/s41467-019-08718-9.
PubMed 30770825
Study at a glance
From the registry record, last updated by the sponsor on 27 Jun 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prospective Validation of CT Based Radiomic Models to Predict Surgical and Clinical Outcomes in Advanced Epithelial Ovarian Cancer
- ClinicalTrials.gov ID
- NCT06817174
- Acronym / sponsor ID
- ORACLE / 25/SC/0032
- Conditions
- Ovarian Cancer
- Keywords
- Ovarian cancer, Radiomics, CT, Prognosis, Epithelial ovarian cancer, Biomarkers
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 168 participants (estimated)
- Lead sponsor
- Imperial College Healthcare NHS TrustUniversity, hospital or other
- Collaborators
- National Cancer Center, Korea
- Study start
- 10 Feb 2025 (actual)
- Primary completion
- Jan 2032 (estimated)
- Study completion
- Jan 2032 (estimated)
- First posted
- 10 Feb 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 5 Years
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Suspected / confirmed advanced epithelial ovarian cancer | – | – |
Who may qualify
- Ages
- 18 years and older
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The study population will consist of patients from Imperial College Healthcare Trust, London, UK and National Cancer Centre, Korea, diagnosed with ovarian masses suspected or confirmed as advanced epithelial ovarian cancer. Participants must be medically fit to undergo the combination of cytoreductive surgery and platinum-based chemotherapy, as part of their standard anticancer treatment.
Key inclusion criteria (6 listed)
- 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
Key exclusion criteria (7 listed)
- 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;
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Comparison of CT-based Radiomics Models and Clinical Model in Predicting Progression-Free Survival Post-Cytoreductive Surgery in Ovarian Cancer
Time frame: 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
1 secondary outcome
Comparison of CT-Radiomics Models and Clinical Model in Predicting Overall Survival Post-Cytoreductive Surgery in Ovarian Cancer
Time frame: From enrolment to approximately 5 years after the last patient is enrolled, based on the final data capture at the end of follow-up.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 27 Jun 2025.
- BackgroundKristofer Linton-Reid, Georg Wengert, Haonan Lu, Christina Fotopoulou, Philippa Lee, Federica Petta, Luca Russo, Giacomo Avensani, Murbarik Arshard, Philipp Harter, Mitch Chen, Marc Boubnovski, Sumeet Hindocha, Ben Hunter, Sonia Prader, Joram M. Posma, Andrea Rockall, Eric O. Aboagye. End-to-End Integrative Segmentation and Radiomics Prognostic Models Improve Risk Stratification of High-Grade Serous Ovarian Cancer: A Retrospective Multi-Cohort Study. medRxiv 2023.04.26.23289155; doi: https://doi.org/10.1101/2023.04.26.23289155
- Background: PubMed 34923575Fotopoulou C, Rockall A, Lu H, Lee P, Avesani G, Russo L, Petta F, Ataseven B, Waltering KU, Koch JA, Crum WR, Cunnea P, Heitz F, Harter P, Aboagye EO, du Bois A, Prader S. Validation analysis of the novel imaging-based prognostic radiomic signature in patients undergoing primary surgery for advanced high-grade serous ovarian cancer (HGSOC). Br J Cancer. 2022 Apr;126(7):1047-1054. doi: 10.1038/s41416-021-01662-w. Epub 2021 Dec 18.
- Background: PubMed 30770825Lu H, Arshad M, Thornton A, Avesani G, Cunnea P, Curry E, Kanavati F, Liang J, Nixon K, Williams ST, Hassan MA, Bowtell DDL, Gabra H, Fotopoulou C, Rockall A, Aboagye EO. A mathematical-descriptor of tumor-mesoscopic-structure from computed-tomography images annotates prognostic- and molecular-phenotypes of epithelial ovarian cancer. Nat Commun. 2019 Feb 15;10(1):764. doi: 10.1038/s41467-019-08718-9.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Ovarian Cancer, run by Imperial College Healthcare NHS Trust at 1 site in United Kingdom.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 7 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 27 Jun 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United Kingdom. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Christina Fotopoulou, MD, PhD ((+44) +44 (0)20 3313 3274, c.fotopoulou@imperial.ac.uk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Comparison of CT-based Radiomics Models and Clinical Model in Predicting Progression-Free Survival Post-Cytoreductive Surgery in Ovarian Cancer (time frame: From enrolment to approximately 5 years after the last patient is enrolled, based on the final data capture at the end of follow-up.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06817174, which also lists 3 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 27 Jun 2025.