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NCT07144319 · ClinicalTrials.gov registry record
Exploration of Novel AI-enabled Blue Light Enhanced Cystoscopy
A clinical trial, sponsored by Photocure.
- Recruiting
- Registry status
- 500
- Enrollment target
NCT07144319: Recruiting study, sponsored by Photocure.
NCT07144319 is a clinical trial that is actively recruiting participants, run by Photocure. The registered enrollment target is 500 participants. According to ClinicalTrials.gov, the official US trial registry.
The verdict
NCT07144319 is actively recruiting participants, sponsored by Photocure.
- RECRUITING
- Registry status
- 500 participants
- Enrollment target
Study Summary
Blue light cystoscopy (BLC) is a diagnostic procedure in bladder cancer where the inside of the bladder is observed with a camera to detect bladder lesions. Unlike regular white light cystoscopy, blue light cystoscopy makes use of a drug that induces fluorescence under blue light preferentially in neoplastic and malignant cells that helps visualize bladder lesions during the cystoscopic procedure. Blue light cystoscopy has shown to improve detection of bladder cancer. Cystoscopy, including blue light cystoscopy, is a procedure involving assessment of the visual appearance of the bladder surface, leading to decisions of taking biopsies, remove suspicious areas and assign treatment options. The assessment is subjective and has a large operator variability. These shortcomings show an opportunity for computer aided detection (CADe) medical device to add value to both clinicians and patients. The objective of this data collection study is to build a high-quality, diverse data set of video, image recordings and relevant clinical data from BLC procedures performed as part of routine clinical practice to train a computer-aided detection (CADe) algorithm for real- time lesion detection during cystoscopy. The data will be used to support the training, non-clinical technical development and testing of such AI algorithms for use during cystoscopy and to provide documentation needed for training of such algorithms and to assist in guiding future validation of such algorithms. Exploratory purposes of the study is to use data to explore future AI algorithms in bladder cancer, such as computer-aided diagnosis (CADx) AI algorithms, image enhancement and cystoscopy improvement algorithms, including bladder mapping, tumor visualization, cystoscopy documentation, and combination models of image and clinical data including risk assessment, clinical outcomes, and disease modeling
Primary Outcome
To collect videos, images and relevant clinical data from BLC procedures performed as part of clinical practice. The data will be used to explore the potential of a BLC-enabled AI algorithm for lesion detection of bladder cancer.
Trial Details
| Field | Value |
|---|---|
| Enrollment Target | 500 participants |
| Start Date | 2026-03-25 |
| Est. Completion | 2027-12 |
What NCT07144319 shows while recruiting
NCT07144319 is an observational study that tracks outcomes without assigning an intervention. The registered 500 participants enrollment target is mid-sized for trials with a published cap.
The record links to 0 conditions, and to 0 interventions.
NCT07144319 does not publish any study locations in the registry export this page uses.
Frequently Asked Questions
What is clinical trial NCT07144319 about?
NCT07144319 is a clinical study titled "Exploration of Novel AI-enabled Blue Light Enhanced Cystoscopy". Blue light cystoscopy (BLC) is a diagnostic procedure in bladder cancer where the inside of the bladder is observed with a camera to detect bladder lesions. Unlike regular white light cystoscopy, blue light cystoscopy makes use of a drug that induces fluorescence under blue light preferentially in n...
What is the current status of trial NCT07144319?
This trial is currently recruiting. The enrollment target is 500 participants. The study started on 2026-03-25. Estimated completion is 2027-12.
Who is sponsoring clinical trial NCT07144319?
This trial is sponsored by Photocure, which has 11 total clinical trials registered on ClinicalTrials.gov.
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