Bladder CancerENAiBLENCT07144319
Exploration of Novel AI-enabled Blue Light Enhanced Cystoscopy
An observational study of Bladder Cancer and Non-muscle Invasive Bladder Cancer, run by Photocure at 12 sites in 5 countries.
Trial summary
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… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Bladder Cancer, Non-muscle Invasive Bladder Cancer
- How many people
- 500 participants
- Where
- 12 sitesin 5 countries
- Study dates
- 25 Mar 2026to Dec 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Routine clinical practice patients scheduled for BLC
Who may be able to join
- 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
Who cannot join
- None
Trial locations and contacts
12 sites in 5 countries. Contact the study team or a site near you to ask about taking part.
12 sites in 5 countries
United States5 sites, 5 recruiting
- Recruiting
Regents of the University of Michigan
Ann Arbor, Michigan, 48108
Todd Morgan, MD, 734-936-1902, urology_morganlab_studies@med.umich.edu
- Recruiting
University of Iowa Health Care
Iowa City, Iowa, 52242
Michael O'Donnell, MD, 319-356-2421, michael-odonnell@uiowa.edu
- Recruiting
Vanderbilt University Medical Center
Nashville, Tennessee, 37232
Kristen Scarpato, MD, 615-875-2395, brianne.duncan@vumc.org
- Recruiting
Rutgers Cancer Institute
New Brunswick, New Jersey, 08901
Vignesh Packiam, MD, 732-235-2465, cinj-rlc@cinj.ru
- Recruiting
Moffitt Cancer Center
Tampa, Florida, 33612
Roger Li, MD, 813-745-8343, roger.li@moffitt.org
Germany4 sites, 4 recruiting
- Recruiting
Department of Urology, University Medical Center Hamburg-Eppendorf (UKE)
Hamburg
Victor Schüttfort, MD, +49 (0) 40 7410 - 53445, urologie-studien@uke.de
- Recruiting
Marien Hospital Herne, Universitätsklinikum der Ruhr-Universität Bochum
Herne
Karl Heinrich Tully, MD, + 49 2323 499 5252, studienkoordination@elisabethgruppe.de
- Recruiting
Klinik und Poliklinik für Urologie, TUM Klinikum
München
Florian Kirchhoff, Dr. med., +49 89/4140-2507/2508, urologie@mri.tum.de
- Recruiting
Universitätsklinikum Ulm, Klinik für Urologie und Kinderurologie
Ulm, 89081
Christian Bolenz, Prof. Dr. med., +49 731/500-58183, studien.urologie@uniklinik-ulm.de
Belgium1 site, 1 recruiting
- Recruiting
UZ Leuven
Leuven
Ben Van Cleynenbreugel, +3216346930, urologie@uzleuven.be
Canada1 site, 1 recruiting
- Recruiting
Vancouver Prostate Centre at Vancouver General Hospital
Vancouver
Marie-Pier St-Laurent, +1 604-875-5003, clinicaltrials@prostatecentre.com
Norway1 site, 1 recruiting
- Recruiting
Oslo University Hospital
Oslo
Recep Øzeke, MD, +4791502770, post@oslo-universitetssykehus.no
About this study
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.
Read more
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
- Conditions
- Bladder Cancer, Non-muscle Invasive Bladder Cancer
- Keywords
- bladder cancer, artificial intelligence, cystoscopy
- Medical subject headings
- Urinary Bladder Neoplasms, Non-Muscle Invasive Bladder Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| BLC patients | Adult, consenting patients scheduled for BLC as part of clinical practice. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Video and image collection
To collect videos, images and relevant clinical data from BLC procedures performed as part of clinical practice. The data will be used to explore the potential of a BLC-enabled AI algorithm for lesion detection of bladder cancer.
Measured: 1 day
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Aug 2025
- Study start25 Mar 2026
- Primary completionDec 2027 (estimated)
- Study completionDec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Bladder CancerStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Photocure
- Sponsor type
- Industry (pharma, biotech, devices)
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07144319
- Sponsor's protocol ID
- PCAIX01/25
- Acronym
- ENAiBLE
- Status last verified
- Jun 2026
- First submitted
- 20 Aug 2025
- Last updated
- 29 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 29 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Exploration of Novel AI-enabled Blue Light Enhanced Cystoscopy
- ClinicalTrials.gov ID
- NCT07144319
- Acronym / sponsor ID
- ENAiBLE / PCAIX01/25
- Conditions
- Bladder Cancer, Non-muscle Invasive Bladder Cancer
- Keywords
- bladder cancer, artificial intelligence, cystoscopy
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 500 participants (estimated)
- Lead sponsor
- PhotocureIndustry (pharma, biotech, devices)
- Study start
- 25 Mar 2026 (actual)
- Primary completion
- Dec 2027 (estimated)
- Study completion
- Dec 2027 (estimated)
- First posted
- 27 Aug 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| BLC patients | – | –Adult, consenting patients scheduled for BLC as part of clinical practice. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Routine clinical practice patients scheduled for BLC
Key inclusion criteria (5 listed)
- 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
Key exclusion criteria (1 listed)
- None
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Video and image collection
Time frame: 1 day
To collect videos, images and relevant clinical data from BLC procedures performed as part of clinical practice. The data will be used to explore the potential of a BLC-enabled AI algorithm for lesion detection of bladder cancer.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 29 Oct 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
12 sites in 5 countries: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Bladder Cancer and Non-muscle Invasive Bladder Cancer, run by Photocure at 12 sites in 5 countries.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 29 Oct 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 12 sites in United States, Germany, Belgium, Canada, Norway. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Kristine Young-Halvorsen, PhD (004722062210, research@photocure.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Video and image collection (time frame: 1 day). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 29 Oct 2026.