Hyperspectral retinal imaging for micro- and nanoplastics detection: a conceptual and methodological framework

This manuscript presents a conceptual and methodological framework rather than empirical results, outlining a pathway for applying hyperspectral retinal imaging (HSRI) to detect micro- and nanoplastics (MNPs). The retina, with its transparent optical media, layered architecture, and vascularization, offers an ideal biomedical model for adapting spectroscopic techniques that have been widely used in environmental and materials sciences. The framework consists of four staged phases: i) construction of a spectral library of common synthetic polymers; ii) phantom experiments that replicate retinal optical properties and are spiked with defined MNPs; iii) ex vivo validation in ocular tissues with Raman and Fourier-transform infrared spectroscopy as chemical ground truth; and iv) pilot in vivo studies in small-animal models to assess HSRI sensitivity, specificity, and safety. Machine-learning classifiers and spectral unmixing algorithms are incorporated to separate polymer-specific signals from endogenous chromophores such as hemoglobin, melanin, and lipofuscin. While no experimental data are presented, the framework anticipates the establishment of polymer spectral libraries, demonstration of separable spectral signatures, and translational feasibility for detecting polymer deposits under safe irradiance conditions. If validated, HSRI could enable the retina to serve as a sentinel organ for systemic pollutant exposure, bridging ophthalmology, toxicology, and environmental health with spectroscopy.______________________________________________________________________________________________________________________________________________________ Graphical Abstract