Study of bladdeR Cancer Detection in Standard White Light Versus AI-Supported Endoscopy-02 (RAISE02)

January 13, 2025 updated by: Cystotech
This study is being conducted to investigate if an artificial intelligence support tool is non-inferior in detecting bladder cancer compared to the traditional method, standard white light cystoscopy (WLC). The researchers will compare how well the artificial intelligence tool and WLC perform in detecting bladder cancer through a controlled, organized testing process.

Study Overview

Status

Enrolling by invitation

Conditions

Intervention / Treatment

Detailed Description

This clinical investigation aims to confirm that an artificial intelligence model utilizing a Convolutional Neural Network (CNN) can achieve sensitivity in detecting bladder cancer that is non-inferior to traditional white light cystoscopy (WLC) in a randomized controlled trial. The investigational artificial intelligence device leverages the advanced capabilities of CNNs, a type of deep learning model designed to analyze visual imagery with high precision.

Study Type

Interventional

Enrollment (Estimated)

64

Phase

  • Not Applicable

Contacts and Locations

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

Study Locations

  • Denmark
      • Aarhus, Denmark, 8200
        • Department of Urology, Aarhus University Hospital

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

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • Men and women adults, age >18 years old

Suspicion of primary or recurrent bladder cancer

Willingness to sign the Informed Consent Form (ICF) for the CI

Ability to comprehend the oral and written Patient Information Leaflet (PIL)

Exclusion Criteria:

  • Not able or willing to sign the Informed Consent Form

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

  • Primary Purpose: Other
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
No Intervention: WLC detection
Detection of bladder cancer is conducted according to state-of-the-art procedures in white light modality.
Experimental: AI model - WLC supported detection
Detection of bladder cancer in white light supported by a pre-market AI-support tool.
Device: AI supported detection of bladder cancer
AI-model-supported detection of bladder cancer during white light cystoscopy

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Sensitivity of standard WLC compared to WLC assisted by the AI model evaluated with a non-inferiority margin of 5%.
Time Frame: 7 month
To determine whether the AI model is non-inferior with regards to sensitivity compared to standard WLC in a randomized controlled trial.
7 month

Collaborators and Investigators

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

Sponsor

Cystotech

Collaborators

Aarhus University Hospital

Investigators

  • Principal Investigator: Jakobsen, Department of Urology, Aarhus University Hospital, denmark

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)

November 20, 2024

Primary Completion (Estimated)

April 1, 2025

Study Completion (Estimated)

May 1, 2025

Study Registration Dates

First Submitted

January 13, 2025

First Submitted That Met QC Criteria

January 13, 2025

First Posted (Actual)

March 25, 2025

Study Record Updates

Last Update Posted (Actual)

March 25, 2025

Last Update Submitted That Met QC Criteria

January 13, 2025

Last Verified

January 1, 2025

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • RAISE02-24-02

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

Sharing the IPD conflicts with the collaboration agreement.

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.

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