Optical Biopsy of Bladder Cancer Using Crowd-Sourced Assessment

Crowdsourcing and optical biopsy are emerging technologies with broad applications in clinical medicine and research. Crowdsourcing, an interactive digital platform that uses multiple individual contributions to efficiently perform a complex task, has been successfully used in diverse disciplines ranging from performance assessment in surgery to optimization of tertiary protein conformations.^1,2 Optical biopsy technologies provide real-time tissue imaging with histology-like resolution and the potential to guide intraoperative decision making.^3-5 An example is confocal laser endomicroscopy (CLE), which can be used for the diagnosis and grading of bladder cancer.⁶ To further assess the adoptability of optical biopsy as a diagnostic tool, we applied crowdsourcing to determine the barriers to learning how to diagnose cancer using CLE. We hypothesized that a nonmedically trained crowd could learn to rapidly and accurately distinguish between cancer and benign tissue.