Shandong Medical Imaging Research Institute, Shandong Provincial Key Laboratory of Diagnosis and Treatment of Cardio-Cerebral Vascular Disease, Shandong University, Jinan, 250021, China.
Institute of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan, 250061, China.
Cytometry A. 2019 Mar;95(3):302-308. doi: 10.1002/cyto.a.23671. Epub 2018 Dec 3.
Small cell lung cancer (SCLC) needs to be classified from poorly differentiated lung adenocarcinoma (PDLAC) for appropriate treatment of lung cancer patients. Currently, the classification is achieved by experienced clinicians, radiologists and pathologists based on subjective and qualitative analysis of imaging, cytological and immunohistochemical (IHC) features. Label-free classification of lung cancer cell lines is developed here by using two-dimensional (2D) light scattering static cytometric technique. Measurements of scattered light at forward scattering (FSC) and side scattering (SSC) by using conventional cytometry show that SCLC cells are overlapped with PDLAC cells. However, our 2D light scattering static cytometer reveals remarkable differences between the 2D light scattering patterns of SCLC cell lines (H209 and H69) and PDLAC cell line (SK-LU-1). By adopting support vector machine (SVM) classifier with leave-one-out cross-validation (LOO-CV), SCLC and PDLAC cells are automatically classified with an accuracy of 99.87%. Our label-free 2D light scattering static cytometer may serve as a new, accurate, and easy-to-use method for the automatic classification of SCLC and PDLAC cells. © 2018 International Society for Advancement of Cytometry.
小细胞肺癌（SCLC）需要与低分化肺腺癌（PDLAC）区分，以便为肺癌患者提供适当的治疗。目前，该分类由经验丰富的临床医生、放射科医生和病理学家根据影像学、细胞学和免疫组织化学（IHC）特征的主观和定性分析来实现。本文使用二维（2D）光散射静态细胞术开发了一种非标记的肺癌细胞系分类方法。使用常规细胞术测量前向散射（FSC）和侧向散射（SSC）的散射光，结果显示 SCLC 细胞与 PDLAC 细胞重叠。然而，我们的 2D 光散射静态细胞仪揭示了 SCLC 细胞系（H209 和 H69）和 PDLAC 细胞系（SK-LU-1）的 2D 光散射模式之间存在显著差异。采用带有留一法交叉验证（LOO-CV）的支持向量机（SVM）分类器，SCLC 和 PDLAC 细胞的自动分类准确率达到 99.87%。我们的无标记 2D 光散射静态细胞仪可以作为一种新的、准确的、易于使用的方法，用于 SCLC 和 PDLAC 细胞的自动分类。 © 2018 国际细胞分析学会。
