AI-assisted detection and removal of bladder tumors during cystoscopy
Intraoperative integration of artificial intelligence during cystoscopic surgery
Using artificial intelligence to help doctors spot and remove bladder tumors during cystoscopy for people with or suspected of bladder cancer.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Stanford University NIH-funded |
| Lab location | 1 site (Stanford, United States) |
| Project ID | NIH-11299481 on NIH RePORTER |
What this research studies
This project adds a deep-learning AI tool to routine cystoscopy to highlight suspicious areas that might be missed with standard white-light imaging. The AI will be used both in clinic cystoscopy to flag lesions and in the operating room during transurethral resection to guide more complete tumor removal. Researchers will compare how often lesions are detected and how complete resections are when surgeons use the AI versus standard practice, and they will follow patients to see if recurrence rates change. The work builds on pilot data and will be carried out at Stanford and its clinical sites.
Who could benefit from this research
Good fit: People with known bladder cancer, those with suspicious findings on prior tests, or patients scheduled for diagnostic cystoscopy or transurethral resection of bladder tumor are the best candidates.
Not a fit: People without bladder lesions, those not undergoing cystoscopy, or patients with widely metastatic disease unlikely to be helped by improved local detection may not benefit.
Why it matters
Potential benefit: If successful, the AI could help find more tumors and improve surgical removal, lowering the chance the cancer comes back.
How similar studies have performed: Image-based AI tools have shown promise in detecting lesions in other endoscopic settings and early work in cystoscopy is promising but AI-guided bladder tumor resection is still relatively new.
Where this research is happening
Stanford, United States
- Stanford University — Stanford, United States (Active)
Researchers
- Principal investigator: Liao, Joseph C — Stanford University
- Study coordinator: Liao, Joseph C
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.