Sacchetti Sara, Bellia Matteo, Vidali Matteo, Zanotti Valentina, Giacomini Luca, Gaidano Gianluca, Patriarca Andrea, Dianzani Umberto, Rolla Roberta
Clinical Biochemistry Laboratory, "Maggiore della Carità" University Hospital, Department of Health Sciences, University of Eastern Piedmont, Novara, Italy.
Division of Hematology, "Maggiore della Carità" University Hospital, Department of Translational Medicine, University of Eastern Piedmont, Novara, Italy.
Int J Lab Hematol. 2025 Aug;47(4):643-650. doi: 10.1111/ijlh.14470. Epub 2025 Mar 27.
The use of artificial intelligence in hematology laboratories has improved the diagnostic evaluation of peripheral blood cells. The aim of this study is to compare the performance of two automated digital cell morphology analyzers, the Mindray MC-80 and the West Medical Vision Hema Pro, with manual microscopy, the gold standard, for leukocyte differentiation in patients with hematologic malignancies and infections.
Peripheral blood smears from 75 patients were analyzed, including cases of acute lymphoblastic leukemia (ALL, 4), chronic lymphocytic leukemia (CLL, 20), acute myeloid leukemia (AML, 20), chronic myeloid leukemia (CML, 5), other lymphoproliferative disorders (LPD, 20), and infections (6). The agreement between microscopy, Vision Hema, and MC-80 was assessed by Bland-Altman analysis for eight leukocyte populations (neutrophils, lymphocytes, monocytes, eosinophils, basophils, band cells, myelocytes, and metamyelocytes).
Vision Hema demonstrated better agreement with manual microscopy for eight normally expected leukocyte populations (neutrophils, lymphocytes, monocytes, eosinophils, basophils, band cells, myelocytes, and metamyelocytes), whereas MC-80 exhibited greater biases, particularly in lymphocytes, basophils, and immature granulocytes. For pathologic cells, VH significantly overestimated blasts, while MC-80 classified them more accurately, showing better agreement with manual microscopy in acute leukemias. Additionally, MC-80 showed potential clinical value in detecting abnormal lymphocytes and promyelocytes, which may be relevant for hematologic malignancies.
Vision Hema provides more reliable classification of normally expected leukocyte populations, while MC-80 shows advantages in detecting abnormal cells, particularly in hematologic malignancies.
人工智能在血液学实验室的应用改善了外周血细胞的诊断评估。本研究的目的是比较两款自动数字细胞形态分析仪(迈瑞MC - 80和维世医疗Vision Hema Pro)与作为金标准的手工显微镜检查在血液系统恶性肿瘤和感染患者白细胞分类中的性能。
分析了75例患者的外周血涂片,包括急性淋巴细胞白血病(ALL,4例)、慢性淋巴细胞白血病(CLL,20例)、急性髓系白血病(AML,20例)、慢性髓系白血病(CML,5例)、其他淋巴增殖性疾病(LPD,20例)和感染(6例)。通过Bland - Altman分析评估显微镜检查、Vision Hema和MC - 80在8种白细胞群体(中性粒细胞、淋巴细胞、单核细胞、嗜酸性粒细胞、嗜碱性粒细胞、杆状核细胞、早幼粒细胞和中幼粒细胞)之间的一致性。
对于8种正常预期的白细胞群体(中性粒细胞、淋巴细胞、单核细胞、嗜酸性粒细胞、嗜碱性粒细胞、杆状核细胞、早幼粒细胞和中幼粒细胞)而言,Vision Hema与手工显微镜检查显示出更好的一致性,而MC - 80表现出更大的偏差,尤其是在淋巴细胞、嗜碱性粒细胞和未成熟粒细胞方面。对于病理细胞,VH显著高估了原始细胞,而MC - 80对其分类更准确,在急性白血病中与手工显微镜检查显示出更好的一致性。此外,MC - 80在检测异常淋巴细胞和早幼粒细胞方面显示出潜在的临床价值,这可能与血液系统恶性肿瘤相关。
Vision Hema为正常预期的白细胞群体提供了更可靠分类,而MC - 80在检测异常细胞方面显示出优势, 尤其是在血液系统恶性肿瘤中。