Department of Pathology and Cell Regulation, Graduate School of Medical Sciences , Kyoto Prefectural University of Medicine , 465 Kajiicho, Kawaramachi-Hirokoji , Kamigyo, Kyoto , Kyoto 6028566 , Japan.
J Phys Chem B. 2019 Mar 28;123(12):2654-2661. doi: 10.1021/acs.jpcb.8b11295. Epub 2019 Mar 14.
We investigated the use of narrowband Raman spectra for rapid label-free molecular imaging aimed at cell classification using principal component regression and linear discriminant analysis. In the classification of breast nontumorigenic epithelial and cancer cell lines, the classification accuracies using a spectral range of 100 cm were equivalent to or better than that with using the fingerprint and high-wavenumber regions. Narrowing the Raman spectral range for analysis allows reduction of the charge-coupled device (CCD) pixels required for spectrum detection, resulting in the improvement of image acquisition speed with adequate classification accuracy. Our measurements revealed that the wavenumber region at 1397-1501 cm can provide molecular information sufficient for cell classification without causing notable errors in the baseline-correction. A spectral resolution of ∼9 cm was found to be sufficient to provide high accuracy in cell classification, which allowed us to apply pixel binning at the CCD readout for further acceleration of the imaging speed. As a result, the acquisition time for a 1200 × 1500 pixels Raman hyperspectral image at 1397-1501 cm was reduced to 21 min. Under this condition, different cell lines were classified at accuracies higher than 90%. The presented approach will improve throughput of cell and tissue analysis and classification using Raman spectroscopy and extend practical uses of Raman imaging in biology and medicine.
我们研究了使用窄带 Raman 光谱进行快速无标记分子成像，旨在使用主成分回归和线性判别分析对细胞进行分类。在对非肿瘤性乳腺上皮细胞和癌细胞系的分类中，使用光谱范围为 100 cm 的分类准确率与使用指纹和高波数区域的分类准确率相当或更好。缩小 Raman 光谱范围进行分析可以减少电荷耦合器件 (CCD) 检测光谱所需的像素数，从而在保持足够分类准确性的同时提高图像采集速度。我们的测量结果表明，在 1397-1501 cm 的波数区域可以提供足够的分子信息用于细胞分类，而不会导致基线校正出现明显误差。发现光谱分辨率约为 9 cm 即可在细胞分类中提供高精度，这允许我们在 CCD 读出时进行像素合并，以进一步加速成像速度。结果，在 1397-1501 cm 处获得 1200×1500 像素 Raman 高光谱图像的采集时间缩短至 21 分钟。在这种情况下，不同的细胞系的分类准确率高于 90%。本研究方法将提高使用 Raman 光谱进行细胞和组织分析和分类的通量，并扩展 Raman 成像在生物学和医学中的实际应用。
