Utility of High-Throughput Imaging Mass Cytometry for Cancer Research: A feasibility study

The Hyperion^TM Imaging System is a novel technology that uses imaging mass cytometry (IMC) to improve upon current methods of tissue imaging, enabling sub-cellular spatial resolution and acquisition of up to 37 proteins on a single tissue slide. The technology is fairly new, and thus we want to explore the types of analysis possible with these data. Here, we introduce an analysis pipeline to utilize machine learning-based analysis for IMC data using data from a muscle invasive bladder cancer patient cohort. We also propose a novel augmentation method to handle the challenge of low number of tissue samples from IMC studies. Our augmentation method was validated and shown to perform better than when only using the original data. Both our pipeline and augmentation method show promise for applications in future research studies and clinical evaluation of this technology. Our results indicate the feasibility of using the proposed framework with a more robust data set to identify prognostic features, which is an important foundation for further clinical research.