Maximizing throughput in label-free microspectroscopy with hybrid Raman imaging.

ABSTRACT

Raman spectroscopy is an optical method providing sample molecular composition, which can be analyzed (by point measurements) or spatially mapped by Raman imaging. These provide different information, signal-to-noise ratios, and require different acquisition times. Here, we quantitatively assess Raman spectral features and compare the two measurement methods by multivariate analysis. We also propose a hybrid method: scanning the beam through the sample but optically binning the signal at one location on the detector. This approach generates significantly more useful spectral signals in terms of peak visibility and statistical information. Additionally, by combination with a complementary imaging mode such as quantitative phase microscopy, hybrid imaging allows high throughput and robust spectral analysis while retaining sample spatial information. We demonstrate the improved ability to discriminate between cell lines when using hybrid scanning compared to typical point mode measurements, by quantitatively evaluating spectra taken from two macrophage-like cell lines. Hybrid scanning also provides better classification capability than the full Raman imaging mode, while providing higher signal-to-noise signals with shorter acquisition times. This hybrid imaging approach is suited for various applications including cytometry, cancer versus noncancer detection, and label-free discrimination of cell types or tissues.