Feasibility of a new method for non-invasive monitoring of low-grade bladder cancer

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.