NCT06780358

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

• Status: Enrolling By Invitation
• Phase: N/A
• Study type: Interventional
• Enrollment: 64 (estimated)
• Sponsor: Cystotech · Industry
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

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.

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.

Conditions

• Bladder Cancer

Interventions

Type	Name	Description
DEVICE	AI supported detection of bladder cancer	AI-model-supported detection of bladder cancer during white light cystoscopy

Timeline

• Start date: 2024-11-20
• Primary completion: 2025-04-01
• Completion: 2025-05-01
• First posted: 2025-01-17
• Last updated: 2025-01-17

Locations

1 site across 1 country: Denmark