Label-Free Multimodal Imaging Microscope for Damaged Cell Membrane Detection and Single-Cell Characterization

Multimodal characterization of single cells offers unprecedented resolution and depth for research in fundamental biology, pathology, and drug development. However, limited by labeling techniques or complex systems, developing a simple, label-free multimodal detection system remains challenging. In this work, a label-free multimodal imaging microscope (MMIM) is proposed for single-cell characterization. The MMIM system simultaneously performs forward scattering, degree of circular polarization, and phase measurements to quantify the volume and to image intracellular refractive index distribution and morphology. Four features, from external morphology (volume, roughness average (Ra), and root-mean-square) to intracellular substance (refractive index), are extracted for characterization. Moreover, the potential high classification accuracy of multimodal characterization is verified by a decision tree model. The MMIM system detected that surface roughness of damaged human kidney-2 (HK-2) cells induced by lipid peroxidation was 39.7% higher than normal HK-2 cells. Scanning electron microscopy images of the control group confirmed that MMIM can directly detect cell membrane damage, without the need for fluorescent staining or complex systems. Multimodal features improved accuracy by 21.5 and 22.4% for classifying different cancer cell types and normal versus damaged HK-2 cells compared to single features. Overall, the MMIM system provides a simple method of multimodal characterization and cell membrane damage detection for single cells, demonstrating great potential in biomedical research.