Automatic label-free image-based system for cell viability monitoring on-a-chip
Emanuela Cutuli, Giovanna Stella, Francesca Guarino, Maide Bucolo
Abstract
Monitoring and assessing cell viability is essential in biochemical systems analysis and medical diagnostics. Currently, several methodologies are available, broadly classified into label-based and label-free viability assays. This work presents a novel, label-free cell viability characterization technique that leverages on-a-chip hydrodynamical stimulations. As a proof-of-concept, the collective behavior of healthy and unhealthy eukaryotic yeast cells, suspended in a PBS (phosphate-buffered saline) solution and subjected to an oscillatory input flow within a microchannel , was studied and compared to that of inert silica beads. To enable long-term real-time measurements, a Digital Particle Image Velocimetry (DPIV)-based algorithm was extended in this work, incorporating a Time-Slot implementation for continuous monitoring. This is crucial for drug investigations and in-vitro diagnostics, enabling deeper insights into dynamic biological processes and therapeutic responses. This method analyzes the hydrodynamic response of micro-particles, automatically extracting parameters in both the time and frequency domains within predefined time windows, named Time-Slot , overcoming the limitations of traditional offline analysis. These parameters were successfully used in this study to accurately classify the different nature of micro-particles. This work demonstrates, for the first time, the feasibility of using label-free, low-frequency, oscillating stimulations to assess cell viability on-a-chip. The parameters extracted from the hydrodynamic cell response provide an automated, non-invasive solution for classifying cell viability, while avoiding data overload and allowing for extended monitoring times. The developed system, simple to implement and versatile, offers a powerful tool for long-term, on-a-chip viability monitoring and introduces a new paradigm for label-free cell viability assessment in microfluidic devices .