摘要
目的探讨细胞形态检测系统对外周血细胞的认知和分辨能力。方法描述性研究分析自动化细胞形态检测系统CellaVision DM96的临床效能，（2013年6月至10月）2267份EDTA-K2抗凝的新鲜血样本选自北京协和医院门诊及住院患者（男1235名，女1034名，平均年龄46岁），用于对检测系统的精密度、敏感度、特异度及检测系统错误分类进行评估。在评估符合率时，首先分析了人工审核后分类计数与金标准法即人工显微镜镜检分类计数的符合率，在此符合率良好的基础上评估了检测系统对中性分叶核粒细胞、中性杆状核粒细胞、淋巴细胞、单核细胞、嗜酸性粒细胞、嗜碱性粒细胞、原始细胞、早幼粒细胞、中性中幼粒细胞、中性晚幼粒细胞、浆细胞及异型淋巴细胞的自动分类计数（又称预分类）与人工审核后分类计数的符合率。结果检测系统对各类细胞预分类检测的敏感度为46％～100％，特异度为24％～92％；从细胞水平分析，检测系统预分类的总符合率为88％；上述各类细胞人工审核后分类的符合率（25％～100％）高于预分类的符合率（6％～95％）；从样本水平分析，各类细胞人工审核后分类的符合率（84％-100％）也高于预分类的符合率（64％-98％）。对各类细胞，检测系统的预分类和人工审核后分类结果的相关性由高到低依次为淋巴细胞、分叶核粒细胞、嗜酸性粒细胞、杆状核粒细胞、单核细胞、嗜碱性粒细胞，r分别为0．9439、0．9152、0．7854、0．7756、0．6762、0．2891；检测系统的人工审核后分类和显微镜镜检法结果的相关性较前提高，由高到低依次为嗜酸性粒细胞、分叶核粒细胞、淋巴细胞、单核细胞、杆状核粒细胞、嗜碱性粒细胞，r分别为0．9721、0．9685、0．9570、0．8319、0．8006、0．6487。检测系统预分类对中性杆状核粒细胞与中性分叶核粒�
Objective To evaluate the clinical performance of an automated image analysis systems named CellaVision DM96 in classifying White Blood Cells. Methods A total of 2267 peripheral blood samples （ male 1 235, female l 034, average age 46） were obtained from outpatient and inpatient in Peking Union Medical College Hospital （PUMCH） . These samples were selected to evaluate the precision, sensitivity, specificity and the analytical error of the system. We first evaluated the coincidence rate of reclassification and manual microscopy. On the base of favourable coincidence rate, we then evaluated the correlations between the pre-classification and reclassification of segmented neutrophil, band neutrophil, lymphocyte, monocyte, eosinophile, basophile, blast cell, promyelocyte, myelocyte, metamyelocyte, plasma cell and reactive lymphocyte. Results The sensitivity and specificity of pre-classification of White Blood Cell were 46% - 100% and 24%-92%, respectively. When studied on the cell level, the total coincidence rate of pre-classification was 88%. And the coincidence rates of pre-classification and reclassification of White Blood Cell were 6%-95% and 25%-100%, respectively. When assessed on the sample level, the coincidence rates of pre-classification and reclassification of leukocytes were 64%-98% and 84%-100% , respectively. The correlations of pre-classification and reclassification of leukocytes in order from high to low were： lymphocyte, segmented neutrophil, eosinophile, band neutrophil, monocyte, basophile, when r were 0. 943 9, O. 915 2, 0. 785 4, 0. 775 6, 0. 676 2 and 0. 289 1, respectively. The correlations between reclassification and manual microscopy of White Blood Cell were higher than those between pre-classification and manual microscopy. Order from high to low was： eosinophile, segmented neutrophil, lymphocyte, monocyte, band neutrophil, basophile. And r were 0. 972 1, 0. 968 5, 0. 957 0, 0. 831 9, 0. 800 6 and 0. 648 7, respectively. The ability of this automated image analysis systems at
出处
《中华检验医学杂志》
CAS
CSCD
北大核心
2015年第3期168-172,共5页
Chinese Journal of Laboratory Medicine
