Guided-Mode-Resonant Dielectric Metasurfaces for Colorimetric Imaging of Material Anisotropy in Fibrous Biological Tissue

The structural arrangement of fibrous tissue is linked to the onset and progression of Alzheimer's disease, heart disease, fibrosis, and cancer, yet its visualization remains challenging with conventional optical microscopy. Here, we design a guided-mode-resonant dielectric metasurface to detect the presence and orientation of fibrous tissue, modeled as a linearly birefringent anisotropic medium, by colorimetric readout. The metasurface consists of nanoscale Si3N4 (215 nm) and SiO2 (75 nm) layers on a SiO2 substrate, acting as a broadband antireflection coating, patterned with subwavelength-periodic rhombohedral perturbations, which result in guided-mode resonances with sub-10 nm bandwidth. Using full-field simulations, we show how transition from air to tissue in the dielectric environment at the metasurface interface results in a red-to-green change in reflected structural color, while the birefringence and orientation of an anisotropic medium manifests as a green-to-blue change. Importantly, the birefringence-based tuning of the guided mode resonances is spectrally separated from refractive-index-based displacements, allowing quantitative discrimination between both the index and structural arrangement of anisotropic media. We numerically simulate the application of our metasurface to cancer tissue diagnostics, predicting how changes in reflected structural color at the tumor margin can distinguish localized, early stage from metastasized, late-stage cancers. The quantitative, colorimetric mapping of tissue orientation angle marks an improved performance in comparison to polarized light microscopy, where multiple orientation angles yield an identical response. Our guided-mode-resonant metasurface provides a foundation for all-optical, label-free, and quantitative colorimetric visualization of fibrous biological media on a single, clinically compatible chip, promising improvements in staging and treatment decisions.