Exploration of Novel AI-enabled Blue Light Enhanced Cystoscopy
Recruiting now NCT07144319
Run by Photocure · for 18 and older · All sexes
What this study is about
Blue light cystoscopy (BLC) is a diagnostic procedure in bladder cancer where the inside of the bladder is observed with a camera to detect bladder lesions. Unlike regular white light cystoscopy, blue light cystoscopy makes use of a drug that induces fluorescence under blue light preferentially in neoplastic and malignant cells that helps visualize bladder lesions during the cystoscopic procedure. Blue light cystoscopy has shown to improve detection of bladder cancer. Cystoscopy, including blue light cystoscopy, is a procedure involving assessment of the visual appearance of the bladder surface, leading to decisions of taking biopsies, remove suspicious areas and assign treatment options. The assessment is subjective and has a large operator variability. These shortcomings show an opportunity for computer aided detection (CADe) medical device to add value to both clinicians and patients. The objective of this data collection study is to build a high-quality, diverse data set of video, image recordings and relevant clinical data from BLC procedures performed as part of routine clinical practice to train a computer-aided detection (CADe) algorithm for real- time lesion detection during cystoscopy. The data will be used to support the training, non-clinical technical development and testing of such AI algorithms for use during cystoscopy and to provide documentation needed for training of such algorithms and to assist in guiding future validation of such algorithms. Exploratory purposes of the study is to use data to explore future AI algorithms in bladder cancer, such as computer-aided diagnosis (CADx) AI algorithms, image enhancement and cystoscopy improvement algorithms, including bladder mapping, tumor visualization, cystoscopy documentation, and combination models of image and clinical data including risk assessment, clinical outcomes, and disease modeling
Who can join (things the study team will check)
✅ You may be able to join if…
- Age 18 or older
- Written informed consent, approved by relevant IRB/IEC, signed
- Hexvix/Cysview has been prescribed in the usual manner in accordance with the terms of the marketing authorization (see Appendix B)
- Physician has planned to do a blue light cystoscopy on the patient and to obtain biopsies, if clinically indicated, of suspicious lesions with video confirmation.
- Patient has not previously taken part in this study
🚫 You may not be able to join if…
- None
Where this trial is running
- Moffitt Cancer Center, Tampa, Florida, United States
- Regents of the University of Michigan, Ann Arbor, Michigan, United States
- Rutgers Cancer Institute, New Brunswick, New Jersey, United States
- UZ Leuven, Leuven, Belgium
- Vancouver Prostate Centre at Vancouver General Hospital, Vancouver, Canada
- Department of Urology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Marien Hospital Herne, Universitätsklinikum der Ruhr-Universität Bochum, Herne, Germany
- Oslo University Hospital, Oslo, Norway
Who to contact
Kristine Young-Halvorsen, PhD · 004722062210 · research@photocure.com
It's completely normal to call and ask questions before deciding anything. Mention the study ID: NCT07144319.
Verify everything on the official ClinicalTrials.gov record. Page updated September 2026.