Noninvasive Dynamic Cell Viability Monitoring Based on Diffraction Height Fingerprint Spectra

Dynamic, high-throughput monitoring of cell viability is essential for assessing pathological progression and pharmacological efficacy. However, techniques capable of noninvasive, real-time tracking throughout the entire cell life cycle remain scarce. Here, we report a label-free dynamic monitoring method based on cell diffraction fingerprint imaging. This approach leverages a cell height characteristic spectrum derived from diffraction patterns to visualize and quantify the evolution of the cell viability. The method successfully resolved the four distinct stages of apoptosis and demonstrated that texture parameters derived from the Gray-Level Co-occurrence Matrix (GLCM) effectively cluster cells according to their viability state. To validate its pharmacological applicability, we further employed the platform to assess the cytotoxicity of various drug combinations, including natural products (e.g., tea extracts) and conventional drugs. It successfully quantified their differential efficacy against cancer cells. This work presents a paradigm for continuous, noninvasive, single-cell-level viability monitoring, offering a robust analytical tool for mechanism-of-action studies, functional cellular assessment, and high-throughput drug screening. It also provides a theoretical and methodological foundation for advancing label-free optical imaging in cell pathology and biomedical engineering.