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AI Tool to Help Detect Bladder Tumors During Cystoscopy

Tests an artificial intelligence tool that assists bladder camera exams in adults with bladder cancer.

Key facts

Who runs it
Centre Hospitalier Universitaire, Amiens
Where
Amiens, FranceSee the site
Trial code
Registry title
Augmented Bladder Tumor Detection Using Real Time Based Artificial Intelligence
Status
Recruiting
People taking part
500 people, planned
Started
13 May 2022
Expected to end
May 2029
Type of study
Observational
Record updated
15 July 2022

Who can take part

AI summary

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 with a suspected new or returning bladder tumor that is small and limited in number. It tests an artificial intelligence tool used during bladder endoscopy.

Age
18 Years and older
Sex
All sexes can join.
Disease stage
Suspected bladder cancer, new or returning. One tumor of 3 cm (1.2 in) or less, or up to 5 tumors each 3 cm (1.2 in) or less.
Earlier treatment
No BCG treatment or chemotherapy in the 3 months before joining. One course of chemotherapy right after TUR is the exception.

Main reasons for not taking part

  • More than 5 tumors, or a tumor larger than 3 cm (1.2 in)
  • Scan or cystoscopy suspects cancer growing into the bladder muscle (cT2 or higher)
  • Scan shows spread to distant sites (lymph nodes or organs)
  • Gross hematuria (visible blood in the urine)
  • Objects to the use of their data for research

The registry criteria, word for word

Show all 8 criteriaShow less

Who can take part

  • 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 take part

  • 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
  • computed tomography/cystoscopy suspect of muscle-invasive bladder cancer (cT2 or higher)
  • Evidence of more than 5 tumors or more than 3 cm
  • computed tomography/magnetic resonance evidence of distant metastases (lymphatic or organic)
  • Patients objecting to the use of their data in the context of research

Where in France

  • Amiens University HospitalAmiens, FranceContact: Fabien Saint, PrTaking people

About the trial

What the trial wants to find out

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).

Read full original descriptionShow less

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.

Questions to ask the study team

  1. How often do I need to come in, and for how long each time?
  2. Are travel costs paid?
  3. Can I keep my own doctor?
  4. What happens if I want to stop?

Contact the study team: see the registry record → Contacts and Locations

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Data and sources

Registry record
Listed on ClinicalTrials.gov.
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).
Plain-language title
AI Tool to Help Detect Bladder Tumors During CystoscopyGenerated from the registry record. The registry title is the official one.
AI summary
From the trial's eligibility criteria. Read by machine on 12 November 2026.
Record updated
15 July 2022