Augmented Bladder Tumor Detection Using Real Time Based Artificial Intelligence

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.

Recruiting

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Key information

Conditions

Bladder Cancer Artificial Intelligence Cystoscopy Female Urogenital Diseases Female Urogenital Diseases and Pregnancy Complications Male Urogenital Diseases Neoplasms Neoplasms by Site Urinary Bladder Diseases Urinary Bladder Neoplasms Urogenital Diseases Urogenital Neoplasms Urologic Diseases Urologic Neoplasms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Amiens University Hospital

Amiens, 80054, France

Location status: Recruiting

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

Primary outcomes

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

Interested in participating?

Recruiting

Interested in participating?

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Sponsors and collaborators

Lead sponsor

Centre Hospitalier Universitaire, Amiens

Other

Registry information

Official study title

Augmented Bladder Tumor Detection Using the Bladder-Portable Artifact Detection System: A Multicentric Prospective Analytic Study Using Real Time Based Artificial Intelligence (IA).

Acronym: Bladder-PAD

Important dates

Study start: 2022
Primary completion: 2027
Study completion: 2029
First posted: Jun 13, 2022
Registry last updated: Jul 15, 2022

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

Recruiting