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

Area of Science:

• Biomedical Engineering
• Cell Biology
• Microscopy

Background:

• Single-cell characterization is crucial for biology and medicine.
• Current methods often rely on complex labeling or systems, posing challenges.
• A simple, label-free approach for multimodal single-cell analysis is needed.

Purpose of the Study:

• To develop a label-free multimodal imaging microscope (MMIM) for comprehensive single-cell characterization.
• To extract morphological and intracellular features for cell analysis.
• To demonstrate the system's capability in detecting cell damage and classifying cell types.

Main Methods:

• The MMIM system simultaneously uses forward scattering, degree of circular polarization, and phase measurements.
• It quantifies cell volume and images intracellular refractive index distribution and morphology.
• A decision tree model was employed to verify classification accuracy.

Main Results:

• The MMIM system extracted four key features: volume, roughness average (Ra), root-mean-square, and refractive index.
• It detected a 39.7% higher surface roughness in lipid peroxidation-damaged HK-2 cells compared to normal cells.
• Multimodal features enhanced classification accuracy by over 21% for different cell types and damage detection.

Conclusions:

• The MMIM offers a simple, label-free method for multimodal single-cell characterization.
• It effectively detects cell membrane damage without staining or complex setups.
• The system shows significant potential for advancing biomedical research and diagnostics.