4.3 Article

Multi-wavelength multi-direction laser light scattering for cell characterization using machine learning-based methods

Journal

CYTOMETRY PART A
Volume -, Issue -, Pages -

Publisher

WILEY
DOI: 10.1002/cyto.a.24771

Keywords

angular light scattering; label-free cytometry; machine learning; numerical light-scattering simulations; single-cell analysis

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Cell identification and analysis are crucial in many biology- and health-related applications. Optical microscopy cannot provide clear images of the complex internal and surface structures of cells. This study investigates the effects of probing laser wavelength on label-free cell identification using single-cell angular laser-light scattering patterns (ALSP). Machine learning analysis reveals that the backward scattering direction is best for characterizing surface roughness, while the forward scattering direction is best for differentiating the number of mitochondria. Red or green laser light performs better than blue light in distinguishing surface roughness and the number of mitochondria.
Cell identification and analysis play a crucial role in many biology- and health-related applications. The internal and surface structures of a cell are complex and many of the features are sub-micron in scale. Well-resolved images of these features cannot be obtained using optical microscopy. Previous studies have reported that the single-cell angular laser-light scattering patterns (ALSP) can be used for label-free cell identification and analysis. The ALSP can be affected by cell properties and the wavelength of the probing laser. Two cell properties, cell surface roughness and the number of mitochondria, are investigated in this study. The effects of probing laser wavelengths (blue, green, and red) and the directions of scattered light collection (forward, side, and backward) are studied to determine the optimum conditions for distinguishing the two cell properties. Machine learning (ML) analysis has been applied to ALSP obtained from numerical simulations. The results of ML analysis show that the backward scattering is the best direction for characterizing the surface roughness, while the forward scattering is the best direction for differentiating the number of mitochondria. The laser light having red or green wavelength is found to perform better than that having the blue wavelength in differentiating the surface roughness and the number of mitochondria. This study provides important insights into the effects of probing laser wavelength on gaining information about cells from their ALSP.

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