CADx - Radiomics to Distinguish the Origin of Ovarian Tumors (CADx)

January 10, 2022 updated by: Jurgen M.J. Piek, Gynaecologisch Oncologisch Centrum Zuid

Computer-aided Radiology for Cancer Detection and Therapy Stratification - Benign or Malignant Ovarian Tumors.

In women with an ovarian tumor, it is often unclear whether the tumor is benign or malignant. To differentiate, tumor markers (CA125 and CEA), a transvaginal ultrasound and, depending on the ultrasound image and the CA125 concentration, a CT scan are performed. The quality of radiological imaging in diagnosing abdominal pathology is often not accurate enough, making additional interventions no-dig for proper classification and interpretation of the tumor.

Objective: To improve accuracy for distinguishing benign from malignant disease in patients presenting with an ovarian mass by using a computer aided detection algorithm.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Detailed Description

This research focuses on improving the accuracy of the determination of the nature (benign or malignant) of ovarian tumors by making use of artificial intelligence by creating a CT-scan algorithm. This because a correct preoperative classification of ovarian tumors is essential for appropriate treatment. Existing prediction models often lead to unnecessary referrals to gynecological oncology hospitals, resulting in higher costs and increased stress for the patient. It is therefore important to evaluate other strategies to differentiate between benign and malignant ovarian tumors.

Artificial Intelligence (AI) for radiology is currently being developed by the Eindhoven University of Technology (TU/e) and Philips Research Europe and may provide a potential solution to this problem.

The currently developed algorithm (CADx), using a support vector machine (SVM), showed within a small population of about 100 patients a sensitivity of 74% and specificity of 74%. These are promising results to train this algorithm even further with more CT-scans images and the addition of clinical variables and even liquid biopsies.

Type of study: Retrospective study cohort This is a retrospective analysis on known data in which definitive patients diagnosis has already been established and current analysis will not affect treatment plan.

No products for patients are used, only computer aided diagnosis is used on existing radiological imaging, namely CT-scans.

This study is linked to two other Dutch trials in which ovarian tumor biomarkers are assessed in order to find out the origin of ovarian tumors preoperatively.

The first is the HE4-prediction study, with local protocol ID NL58253.031.16. The second is the OVI-DETECT study, with clinicaltrial.gov number NCT04971421.

Study Type

Observational

Enrollment (Anticipated)

600

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

  • Name: Anna Koch, MD
  • Phone Number: 020-512 4303
  • Email: a.koch@nki.nl

Study Locations

  • Netherlands
      • Amsterdam, Netherlands
        • Not yet recruiting
        • Amsterdam Medical Center
        • Contact:
      • Breda, Netherlands
        • Recruiting
        • Amphia Hospital
        • Contact:
        • Sub-Investigator:
          • Dineke Smedts, MD-PhD
    • Brabant
      • Eindhoven, Brabant, Netherlands, 5623EJ
    • Noord Holland
      • Amsterdam, Noord Holland, Netherlands, 1066 CX
        • Recruiting
        • Netherlands Cancer Institute
        • Contact:
          • Christianne Lok, MD; PhD
          • Phone Number: 020 512 2957
          • Email: c.lok@nki.nl
      • Leiden, Noord Holland, Netherlands, 2333 ZA
        • Recruiting
        • Leiden University Medical Center
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

N/A

Genders Eligible for Study

Female

Sampling Method

Non-Probability Sample

Study Population

Patients with an ovarian tumor of which it is unknown whether it is benign or malignant referred for staging laparotomy.

Description

Inclusion Criteria:

  • patients with an ovarian tumor of which it is unknown whether it is benign or malignant (Risk of Malignancy Index (RMI) >200)
  • underwent surgery
  • histological proof of tumor

Exclusion Criteria:

  • indefinite pathology report
  • lack of correct description of staging in OR report when applicable

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Sensitivity and specificity of CADx algorithm
Time Frame: 3 - 4 years
Percentage of correct determination of malignancy by the Risk of Malignancy Index (RMI) compared to exact determination by CAD assessment in patients with an ovarian tumor
3 - 4 years

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Sensitivity and specificity of CADx algorithm with additional variables
Time Frame: 3 - 4 years
Correlation of the findings from CAD analysis in some patients with analysis of circulating tumor (ct) DNA and protein tumor markers or other additional clinical variables
3 - 4 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Gynaecologisch Oncologisch Centrum Zuid

Collaborators

Amsterdam UMC, location VUmc
The Netherlands Cancer Institute
Leiden University Medical Center
Eindhoven University of Technology
Amphia Hospital

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Helpful Links

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

April 5, 2021

Primary Completion (Anticipated)

August 1, 2024

Study Completion (Anticipated)

August 1, 2025

Study Registration Dates

First Submitted

December 13, 2021

First Submitted That Met QC Criteria

December 13, 2021

First Posted (Actual)

December 30, 2021

Study Record Updates

Last Update Posted (Actual)

January 25, 2022

Last Update Submitted That Met QC Criteria

January 10, 2022

Last Verified

January 1, 2022

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • RADIOMICS

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Clinical Trials on Ovarian Cancer

Clinical Trials on CT-scan algorithm

Search Similar Trials

Sponsors and Collaborators

Medical Conditions

Drug Interventions

CROs by country

CROs in United States

Conditions

Rare Diseases

Drug Interventions

Dietary Supplements

Sponsor/Collaborators

Locations

Subscribe