Bladder CancerRAISE02NCT06780358
Study of bladdeR Cancer Detection in Standard White Light Versus AI-Supported Endoscopy-02
A study testing AI supported detection of bladder cancer in people with Bladder Cancer, run by Cystotech at 1 site in Denmark.
Trial summary
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). Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Bladder Cancer
- What is being tested?
- AI supported detection of bladder cancer
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 64 participants
- Where
- 1 siteDenmark
- Study dates
- 20 Nov 2024to May 2025
- Phase
- Interventional
- 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
Who may be able to join
- 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)
Who cannot join
- Not able or willing to sign the Informed Consent Form
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
About this study
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.
Read the 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.
- Conditions
- Bladder Cancer
- Being tested
- AI supported detection of bladder cancer
- Medical subject headings
- Urinary Bladder Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI supported detection of bladder cancerDevice
AI-model-supported detection of bladder cancer during white light cystoscopy
| Study group | Role | What they receive |
|---|---|---|
| WLC detection | No intervention | Detection of bladder cancer is conducted according to state-of-the-art procedures in white light modality. |
| AI model - WLC supported detection | Experimental | Detection of bladder cancer in white light supported by a pre-market AI-support tool. Receives: Device: AI supported detection of bladder cancer |
What is being measured
The primary outcome is the main question the study is designed to answer.
Sensitivity of standard WLC compared to WLC assisted by the AI model evaluated with a non-inferiority margin of 5%.
To determine whether the AI model is non-inferior with regards to sensitivity compared to standard WLC in a randomized controlled trial.
Measured: 7 month
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 Jan 2025
- Study start20 Nov 2024
- Primary completionApr 2025 (estimated)
- Study completionMay 2025 (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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- Premarket Confirmatory, National, single-center, randomized, prospective, non-inferiority trial
- Masking
- None (open label)
- Enrolment
- 64 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Cystotech
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- Aarhus University Hospital
- Responsible party
- Sponsor
- Investigators
- Jakobsen, Principal investigator, Department of Urology, Aarhus University Hospital, denmark
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06780358
- Sponsor's protocol ID
- RAISE02-24-02
- Acronym
- RAISE02
- Status last verified
- Jan 2025
- First submitted
- 13 Jan 2025
- Last updated
- 17 Jan 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Sharing the IPD conflicts with the collaboration agreement.
Study at a glance
From the registry record, last updated by the sponsor on 17 Jan 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Study of bladdeR Cancer Detection in Standard White Light Versus AI-Supported Endoscopy-02
- ClinicalTrials.gov ID
- NCT06780358
- Acronym / sponsor ID
- RAISE02 / RAISE02-24-02
- Conditions
- Bladder Cancer
- Study type
- Interventional
- Recruitment status
- Enrolling by invitation
- Enrolment
- 64 participants (estimated)
- Lead sponsor
- CystotechIndustry (pharma, biotech, devices)
- Collaborators
- Aarhus University Hospital
- Study start
- 20 Nov 2024 (actual)
- Primary completion
- Apr 2025 (estimated)
- Study completion
- May 2025 (estimated)
- First posted
- 17 Jan 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.
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.
Study design
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- Premarket Confirmatory, National, single-center, randomized, prospective, non-inferiority trial
| Arm | Type | Receives |
|---|---|---|
| WLC detection | No intervention | –Detection of bladder cancer is conducted according to state-of-the-art procedures in white light modality. |
| AI model - WLC supported detection | Experimental | Device: AI supported detection of bladder cancerDetection of bladder cancer in white light supported by a pre-market AI-support tool. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- 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)
Key exclusion criteria (1 listed)
- Not able or willing to sign the Informed Consent Form
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI supported detection of bladder cancerAI-model-supported detection of bladder cancer during white light cystoscopy | Device | AI model - WLC supported detection |
Primary outcome
Sensitivity of standard WLC compared to WLC assisted by the AI model evaluated with a non-inferiority margin of 5%.
Time frame: 7 month
To determine whether the AI model is non-inferior with regards to sensitivity compared to standard WLC in a randomized controlled trial.
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 17 Jan 2025.
- Individual participant dataSharing planned: No. Sharing the IPD conflicts with the collaboration agreement.
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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.
Jakobsen principal investigator
Department of Urology, Aarhus University Hospital, denmark
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI supported detection of bladder cancer in people with Bladder Cancer, run by Cystotech at 1 site in Denmark.
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 4 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: enrolling by invitation, as of the sponsor's last update on 17 Jan 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Denmark. 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?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Sensitivity of standard WLC compared to WLC assisted by the AI model evaluated with a non-inferiority margin of 5%. (time frame: 7 month). 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 17 Jan 2025.