Comparison of multiplex immunofluorescence and H&E-based approaches for characterization of the tumor microenvironment

Predictive models applied to digital pathology images show promise for rapid, objective analysis of patient samples to identify tumor microenvironment (TME) features associated with treatment response.

Multiplex immunofluorescence (mIF) and deep learning models applied to H&E-stained slides are two approaches to interrogate the TME for tissue- and cell-level identification.