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

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

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.

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.

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