Noninvasive detection of bladder cancer using machine learning on urine samples
Noninvasive bladder cancer diagnostics via machine learning analysis of nanoscale surface images of epithelial cells extracted from voided urine samples
['FUNDING_R01'] · TUFTS UNIVERSITY MEDFORD · NIH-10895468
This study is working on a new, easy test for bladder cancer that looks at tiny images of cells from your urine, using smart computer technology to help find cancer without needing uncomfortable procedures like cystoscopy.
Quick facts
| Phase | ['FUNDING_R01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | TUFTS UNIVERSITY MEDFORD (nih funded) |
| Locations | 1 site (Boston, UNITED STATES) |
| Trial ID | NIH-10895468 on ClinicalTrials.gov |
What this research studies
This research aims to develop a noninvasive diagnostic test for bladder cancer by analyzing nanoscale images of epithelial cells extracted from urine samples. The approach utilizes machine learning techniques to identify the presence and aggressiveness of bladder cancer, potentially reducing the need for invasive procedures like cystoscopy. By leveraging existing urine cytology extraction technologies, the study seeks to create a rapid and accurate method for cancer detection that is easy for patients to undergo. This could significantly improve patient compliance and comfort during monitoring and screening.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals at risk for bladder cancer, including those with a history of bladder cancer or symptoms suggestive of the disease.
Not a fit: Patients who do not have bladder cancer or are not at risk for developing bladder cancer may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could provide a less invasive and more comfortable method for bladder cancer diagnosis and monitoring, reducing the frequency of cystoscopies.
How similar studies have performed: Other research has shown promise in using noninvasive methods for cancer detection, but this specific approach utilizing machine learning on urine samples is relatively novel.
Where this research is happening
Boston, UNITED STATES
- TUFTS UNIVERSITY MEDFORD — Boston, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: SOKOLOV, IGOR — TUFTS UNIVERSITY MEDFORD
- Study coordinator: SOKOLOV, IGOR
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.
Conditions: Bladder Cancer, Cancer Detection