Augmented Bladder Tumor Detection Using Real Time Based Artificial Intelligence

Launched by CENTRE HOSPITALIER UNIVERSITAIRE, AMIENS · Jun 9, 2022

Keywords

ClinConnect Summary

This clinical trial is investigating a new way to improve the detection of bladder tumors using artificial intelligence (AI) during bladder examinations, known as cystoscopy. The goal is to make diagnosing bladder cancer more accurate, helping doctors identify tumors more reliably and reducing mistakes. By combining traditional methods with AI technology, researchers hope to provide clearer information about the tumors, including their size and risk of returning or worsening. This could lead to better treatment plans for patients with bladder cancer.

To join the trial, participants should be between the ages of 65 and 74 and have either a single bladder tumor (3 cm or smaller) or multiple tumors (up to 5, each 3 cm or smaller). However, people with more advanced cancer or those who have recently received certain treatments may not be eligible. If you participate, you can expect to undergo a cystoscopy procedure where the AI will assist in analyzing the images to help doctors make more informed decisions about your care. This study is currently welcoming new participants and aims to create a more standardized approach to managing bladder cancer for everyone involved.

Gender

ALL

Eligibility criteria

• Inclusion Criteria:
• • 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.
• Exclusion Criteria:
• • 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.