Study of bladdeR Cancer Detection in Standard White Light Versus AI-Supported Endoscopy-02

NCT06780358 | Enrolling By Invitation DMC

• 1 other identifier: RAISE02-24-02
• Study Type: interventional
• Target: 64
• Locations: 1 country
• Sites: 1

Brief 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). The researchers will compare how well the artificial intelligence tool and WLC perform in detecting bladder cancer through a controlled, organized testing process.

Conditions

Bladder Cancer

Outcome Measures

Primary Outcomes (1)

• 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.

  7 month

Study Arms (2)

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.

Device: AI supported detection of bladder cancer

Interventions

AI supported detection of bladder cancer DEVICE

AI-model-supported detection of bladder cancer during white light cystoscopy

AI model - WLC supported detection

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• 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)

You may not qualify if:

• Not able or willing to sign the Informed Consent Form

Sponsors & Collaborators

• Cystotech: lead
• Aarhus University Hospital: collaborator

Study Sites (1)

Department of Urology, Aarhus University Hospital

Aarhus, 8200, Denmark

Location

MeSH Terms

Conditions

Urinary Bladder Neoplasms

Condition Hierarchy (Ancestors)

Urologic Neoplasms; Urogenital Neoplasms; Neoplasms by Site; Neoplasms; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Urinary Bladder Diseases; Urologic Diseases; Male Urogenital Diseases

Study Officials

• Jakobsen

  Department of Urology, Aarhus University Hospital, denmark

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: OTHER
• Intervention Model: PARALLEL
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Model Details: Premarket Confirmatory, National, single-center, randomized, prospective, non-inferiority trial

Study Record Dates

• First Submitted: January 13, 2025
• First Posted: January 17, 2025
• Study Start: November 20, 2024
• Primary Completion: April 1, 2025
• Study Completion: May 1, 2025
• Last Updated: January 17, 2025

Record last verified: 2025-01

Data Sharing

• IPD Sharing: Will not share

Locations

DK (1)