Ugele Matthias, Weniger Markus, Stanzel Manfred, Bassler Michael, Krause Stefan W, Friedrich Oliver, Hayden Oliver, Richter Lukas
In-Vitro DX and Bioscience Department of Strategy and Innovation Siemens Healthcare GmbH Günther-Scharowsky-Str. 1 91058 Erlangen Germany.
Department of Chemical and Biological Engineering Institute of Medical Biotechnology Friedrich-Alexander-University Erlangen-Nuremberg Paul-Gordan-Str. 3 91052 Erlangen Germany.
Adv Sci (Weinh). 2018 Oct 11;5(12):1800761. doi: 10.1002/advs.201800761. eCollection 2018 Dec.
Complete blood count and differentiation of leukocytes (DIFF) belong to the most frequently performed laboratory diagnostic tests. Here, a flow cytometry-based method for label-free DIFF of untouched leukocytes by digital holographic microscopy on the rich phase contrast of peripheral leukocyte images, using highly controlled 2D hydrodynamic focusing conditions is reported. Principal component analysis of morphological characteristics of the reconstructed images allows classification of nine leukocyte types, in addition to different types of leukemia and demonstrates disappearance of acute myeloid leukemia cells in remission. To exclude confounding effects, the classification strategy is tested by the analysis of 20 blinded clinical samples. Here, 70% of the specimens are correctly classified with further 20% classifications close to a correct diagnosis. Taken together, the findings indicate a broad clinical applicability of the cytometry method for automated and reagent-free diagnosis of hematological disorders.
全血细胞计数和白细胞分类(DIFF)属于最常进行的实验室诊断测试。在此,报告了一种基于流式细胞术的方法,该方法通过数字全息显微镜在周围白细胞图像的丰富相差上,利用高度可控的二维流体动力学聚焦条件,对未处理的白细胞进行无标记分类。对重建图像的形态特征进行主成分分析,除了不同类型的白血病外,还能对九种白细胞类型进行分类,并证明缓解期急性髓性白血病细胞消失。为排除混杂效应,通过对20个盲法临床样本的分析来测试分类策略。在此,70%的标本被正确分类,另有20%的分类接近正确诊断。综上所述,这些发现表明该细胞术方法在血液系统疾病的自动化和无试剂诊断方面具有广泛的临床适用性。