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Predicting Outcome of Cytoreduction in Advanced Ovarian Cancer

NCT06017557 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 151

Last updated 2025-12-19

No results posted yet for this study

Summary

PREDAtOOR is a pilot study and this study aims at improving the selection of the best treatment strategy for patients with advanced ovarian cancer by using Camera Vision (CV) to predict outcomes of cyto reduction at the time of Diagnostic laparoscopy.

Conditions

  • Ovarian Cancer Stage III
  • Ovarian Cancer Stage IV

Interventions

DIAGNOSTIC_TEST

Artificial Intelligence

With the introduction of artificial intelligence and machine learning, there is a possibility to create more precise prediction models using images from these diagnostic laparoscopy videos. In particular, it would like to use images from the diagnostic laparoscopy to create machine-learning models to help predict if the tumors can be successfully taken out at primary surgery, or if chemotherapy before surgery would be needed. During surgery time the surgical team takes images however, what makes this different is that these images will be used to help create an algorithm to predict surgical outcomes. These images will be stored in a secure database with an anonymous number not linking these pictures to any of the participants.

Sponsors & Collaborators

  • Fondazione Policlinico Universitario Agostino Gemelli IRCCS

    lead OTHER

Principal Investigators

  • Anna Fagotti, Prof · Fondazione Policlinico Universitario A. Gemelli, IRCCS

Study Design

Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
18 Years
Sex
FEMALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-01-02
Primary Completion
2025-12-15
Completion
2026-09-01

Countries

  • Italy

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06017557 on ClinicalTrials.gov