Bladder CancerBladder-PADNCT05415631
Augmented Bladder Tumor Detection Using Real Time Based Artificial Intelligence
An observational study of Bladder Cancer and Cystoscopy, run by Centre Hospitalier Universitaire, Amiens at 1 site in France.
Trial summary
Today the standard for the diagnosis and monitoring of bladder tumors is bladder endoscopy. The performance of this exam is not perfect. With this work, based on artificial intelligence, the investigators wish to combine endoscopy with a complementary diagnostic tool in order to improve patient care. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Bladder Cancer, Cystoscopy, Artificial Intelligence
- How many people
- 500 participants
- Where
- 1 siteFrance
- Study dates
- 13 May 2022to May 2029
- 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: patients treated for bladder cancer, and prospectively collected at the time of cancer diagnosis, from 01 February 2022 to 01 February 2027
Who may be able to join
- unifocal primary or recurrent suspected bladder cancer with tumor size less or equal than 3 cm
- multifocal primary or recurrent suspected bladder cancer less or equal than 5 lesions and with tumor size less or equal than 3 cm.
Who cannot join
- Evidence of more than 5 tumors or more than 3 cm
- computed tomography/cystoscopy suspect of muscle-invasive bladder cancer (cT2 or higher)
- computed tomography/magnetic resonance evidence of distant metastases (lymphatic or organic)
- Exclusion criteria will include gross hematuria and bacillus Calmette-Guerin (BCG) treatment or chemotherapy within 3 months of inclusion
- An exception will be made if patients had received only a single course of chemotherapy immediately following TUR
- Patients objecting to the use of their data in the context of research.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
France1 site, 1 recruiting
- Recruiting
Amiens University Hospital
Amiens, 80054
Fabien Saint, Pr, 03 22 45 59 45, saint.fabien@chu-amiens.fr
Pierre COLIN, MD
About this study
Official title: Augmented Bladder Tumor Detection Using the Bladder-Portable Artifact Detection System: A Multicentric Prospective Analytic Study Using Real Time Based Artificial Intelligence (IA).
Today the standard for the diagnosis and monitoring of bladder tumors is bladder endoscopy. The performance of this exam is not perfect. With this work, based on artificial intelligence, the investigators wish to combine endoscopy with a complementary diagnostic tool in order to improve patient care. The main objective will be to reduce diagnostic errors / wanderings in patients treated or followed for bladder tumors, by imposing a new standard of diagnostic bladder mapping (high PPV and VPN, high precision)(primary purpose diagnostic). The secondary objective will be to homogenize and systematize the descriptive part of the lesions, and to use AI to better characterize tumor aggressiveness. The final objective being to validate a new precision tool (diagnostic companion) essential for developing and standardizing the therapeutic management of bladder tumors (correcting inter-observer heterogeneity).
In this project, video frame will be first extracted from our dataset of cystoscopy videos hosted in in the Next Cloud Recherche. Selected medical image will be segmented and analyzed using our pre-trained CNN model with a feature detection algorithm to obtain features.
Data will be analyzed on both patient and lesion levels. The study will assess the Bladder-PAD accuracy on the detection of bladder tumors, and its ability to predict tumor risk of recurrence and progression.
- Conditions
- Bladder Cancer, Cystoscopy, Artificial Intelligence
- Keywords
- Bladder Cancer, cystoscopy, Artificial Intelligence
- Medical subject headings
- Urinary Bladder Neoplasms
What is being measured
The primary outcome is the main question the study is designed to answer.
Tumor detection rate of white light cystoscopy
Measured: one day
Tumor detection rate of Bladder-PAD cystoscopy
Measured: one day
Tumor false detection rate of white light cystoscopy
Measured: one day
Tumor false detection rate of Bladder-PAD cystoscopy
Measured: one day
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Jun 2022
- Study start13 May 2022
- Primary completionMay 2027 (estimated)
- Study completionMay 2029 (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.
- More trials run by Centre Hospitalier Universitaire, AmiensThe sponsor's other registered studies.
- 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
- Case only
- Time perspective
- Prospective
- Enrolment
- 500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Centre Hospitalier Universitaire, Amiens
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05415631
- Sponsor's protocol ID
- PI2022_843_0014
- Acronym
- Bladder-PAD
- Status last verified
- May 2022
- First submitted
- 9 Jun 2022
- Last updated
- 15 Jul 2022
- 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 15 Jul 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Augmented Bladder Tumor Detection Using the Bladder-Portable Artifact Detection System: A Multicentric Prospective Analytic Study Using Real Time Based Artificial Intelligence (IA).
- ClinicalTrials.gov ID
- NCT05415631
- Acronym / sponsor ID
- Bladder-PAD / PI2022_843_0014
- Conditions
- Bladder Cancer, Cystoscopy, Artificial Intelligence
- Keywords
- Bladder Cancer, cystoscopy, Artificial Intelligence
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 500 participants (estimated)
- Lead sponsor
- Centre Hospitalier Universitaire, AmiensUniversity, hospital or other
- Study start
- 13 May 2022 (actual)
- Primary completion
- May 2027 (estimated)
- Study completion
- May 2029 (estimated)
- First posted
- 13 Jun 2022 (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.
Today the standard for the diagnosis and monitoring of bladder tumors is bladder endoscopy. The performance of this exam is not perfect. With this work, based on artificial intelligence, the investigators wish to combine endoscopy with a complementary diagnostic tool in order to improve patient care. The main objective will be to reduce diagnostic errors / wanderings in patients treated or followed for bladder tumors, by imposing a new standard of diagnostic bladder mapping (high PPV and VPN, high precision)(primary purpose diagnostic). The secondary objective will be to homogenize and systematize the descriptive part of the lesions, and to use AI to better characterize tumor aggressiveness. The final objective being to validate a new precision tool (diagnostic companion) essential for developing and standardizing the therapeutic management of bladder tumors (correcting inter-observer heterogeneity).
In this project, video frame will be first extracted from our dataset of cystoscopy videos hosted in in the Next Cloud Recherche. Selected medical image will be segmented and analyzed using our pre-trained CNN model with a feature detection algorithm to obtain features.
Data will be analyzed on both patient and lesion levels. The study will assess the Bladder-PAD accuracy on the detection of bladder tumors, and its ability to predict tumor risk of recurrence and progression.
Study design
- Observational model
- Case only
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- patients treated for bladder cancer, and prospectively collected at the time of cancer diagnosis, from 01 February 2022 to 01 February 2027
Key inclusion criteria (2 listed)
- unifocal primary or recurrent suspected bladder cancer with tumor size less or equal than 3 cm
- multifocal primary or recurrent suspected bladder cancer less or equal than 5 lesions and with tumor size less or equal than 3 cm.
Key exclusion criteria (6 listed)
- Evidence of more than 5 tumors or more than 3 cm
- computed tomography/cystoscopy suspect of muscle-invasive bladder cancer (cT2 or higher)
- computed tomography/magnetic resonance evidence of distant metastases (lymphatic or organic)
- Exclusion criteria will include gross hematuria and bacillus Calmette-Guerin (BCG) treatment or chemotherapy within 3 months of inclusion
- An exception will be made if patients had received only a single course of chemotherapy immediately following TUR
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
Tumor detection rate of white light cystoscopy
Time frame: one day
Tumor detection rate of Bladder-PAD cystoscopy
Time frame: one day
Tumor false detection rate of white light cystoscopy
Time frame: one day
Tumor false detection rate of Bladder-PAD cystoscopy
Time frame: one day
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 15 Jul 2022.
- 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.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Bladder Cancer and Cystoscopy, run by Centre Hospitalier Universitaire, Amiens at 1 site in France.
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 2 inclusion and 6 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 15 Jul 2022. 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 France. 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 Fabien SAINT, Pr (03 22 45 59 45, saint.fabien@chu-amiens.fr), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Tumor detection rate of white light cystoscopy (time frame: one day). The study lists 4 primary outcomes in all. 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 15 Jul 2022.