This research is to determine the performance characteristics of a urine-based test for the detection of recurrent bladder cancer in low-grade patients who have been treated according to standard practice and are undergoing routine surveillance cystoscopy. The cystoscopy is regarded as the gold standard for determining recurrence of cancer. The Co-Principal Investigator at Tufts University has developed a urine-based monitoring test of bladder cancer, using imaging of the surface of cells extracted from the patients’ urine. The imaging is going to be done using an advanced sub resonance tapping mode of Atomic Force Microscopy (AFM). The collected images will be analyzed by means of machine learning methods. This may allow for faster, non-invasive, and more reliable detection of bladder cancer.
1. Confirmed positive diagnosis for primary or recurrent urinary tract UC over the past 2 years.
2. Patient is undergoing investigative cystoscopies for the monitoring of recurrence of UC at intervals prescribed by a clinical practitioner
3. Patient is 18 years of age or older.
1. Prior genitourinary manipulation (cystoscopy / catheterization / dilation) in the 14 days before urine collection, current urinary tract infection, current or known history of urinary tract inflammatory disorder, recent history of glomerulonephritis, nephrosis or other renal inflammatory disorders, recent history of pyelonephritis
2. Patient has undergone total bladder cystectomy as treatment for bladder UC
3. Patient who have metastatic bladder cancer
Patient will have routine cystoscopy as part of their standard surveillance for bladder cancer and urine collected at the time of this cystoscopy for cytology and the study.