Pirone Daniele, Lim Joowon, Merola Francesco, Miccio Lisa, Mugnano Martina, Bianco Vittorio, Cimmino Flora, Visconte Feliciano, Montella Annalaura, Capasso Mario, Iolascon Achille, Memmolo Pasquale, Psaltis Demetri, Ferraro Pietro
CNR-ISASI, Institute of Applied Sciences and Intelligent Systems "E. Caianiello", Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy.
DIETI, Department of Electrical Engineering and Information Technologies, University of Naples "Federico II", Via Claudio 21, 80125 Napoli, Italy.
Nat Photonics. 2022 Dec;16(12):851-859. doi: 10.1038/s41566-022-01096-7. Epub 2022 Nov 10.
Quantitative Phase Imaging (QPI) has gained popularity in bioimaging because it can avoid the need for cell staining, which in some cases is difficult or impossible. However, as a result, QPI does not provide labelling of various specific intracellular structures. Here we show a novel computational segmentation method based on statistical inference that makes it possible for QPI techniques to identify the cell nucleus. We demonstrate the approach with refractive index tomograms of stain-free cells reconstructed through the tomographic phase microscopy in flow cytometry mode. In particular, by means of numerical simulations and two cancer cell lines, we demonstrate that the nucleus can be accurately distinguished within the stain-free tomograms. We show that our experimental results are consistent with confocal fluorescence microscopy (FM) data and microfluidic cytofluorimeter outputs. This is a significant step towards extracting specific three-dimensional intracellular structures directly from the phase-contrast data in a typical flow cytometry configuration.
定量相成像（QPI）在生物成像领域已颇受欢迎，因为它无需进行细胞染色，而在某些情况下，细胞染色操作困难甚至无法进行。然而，其结果是，QPI无法对各种特定的细胞内结构进行标记。在此，我们展示了一种基于统计推断的新型计算分割方法，该方法使QPI技术能够识别细胞核成为可能。我们通过流式细胞术模式下的层析相显微镜重建的无染色细胞的折射率断层图来演示该方法。特别是，通过数值模拟和两种癌细胞系，我们证明了在无染色断层图中可以准确区分细胞核。我们表明，我们的实验结果与共聚焦荧光显微镜（FM）数据和微流控细胞荧光计输出结果一致。这是朝着在典型的流式细胞术配置中直接从相衬数据提取特定三维细胞内结构迈出的重要一步。
