Study of bladdeR Cancer Detection in Standard White Light Versus AI-Supported Endoscopy-02
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: AI supported detection of bladder cancer.
- Who it may be relevant to
- Registry conditions: Bladder Cancer. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Denmark
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Overview
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.
Interventions
- Device AI supported detection of bladder cancer
AI-model-supported detection of bladder cancer during white light cystoscopy
Primary outcome measures
- Sensitivity of standard WLC compared to WLC assisted by the AI model evaluated with a non-inferiority margin of 5%. [Time frame: 7 month]
Eligibility criteria
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
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Allocation
- Randomized
- Model
- Parallel assignment
- Masking
- Open label
- Primary purpose
- Other
Study locations
Denmark · 1 center
- Department of Urology, Aarhus University Hospital — Aarhus
Identifiers
NCT: NCT06780358 · RAISE02-24-02