Collecting Bladder Camera Recordings to Train AI Detection Tools
Records blue light bladder camera exams in adults with bladder cancer to help train AI.
Plain-language title generated from the registry record
Registry title: Exploration of Novel AI-enabled Blue Light Enhanced Cystoscopy
Key facts
- Where
- Hamburg, Herne, München, and Ulm, GermanySee the 4 sites
AI summary: who the study is looking for
From the trial's eligibility criteria. Machine-read from the registry text on this page, so it can be wrong. The registry text below and the trial team decide who can take part.
The trial is looking for adults who are planned to have a blue light cystoscopy of the bladder in routine care. Video of the procedure is recorded to train a computer program that spots bladder lesions.
- Age
- 18 years or older
- Sex
- All sexes can join.
- Earlier treatment
- Hexvix/Cysview has been prescribed in the usual way. The patient has not taken part in this study before.
Main reasons for not taking part
- Has already taken part in this study
Read by machine on 9 November 2026.
Where in Germany
- Department of Urology, University Medical Center Hamburg-Eppendorf (UKE)Hamburg, GermanyTaking people
- Marien Hospital Herne Universitatsklinikum Der Ruhr-Universitat BochumHerne, GermanyTaking people
- Klinik und Poliklinik für Urologie, TUM KlinikumMünchen, GermanyTaking people
- Universitätsklinikum Ulm, Klinik für Urologie und KinderurologieUlm, GermanyTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- Photocure
- Trial code
- NCT07144319
- Record updated
- 29 October 2026
- Original description
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.Read full original descriptionShow less
Exploration of Novel AI-enabled Blue Light Enhanced Cystoscopy
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
Inclusion: 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.
Exclusion: None.