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Exploring dyserythropoiesis in patients with myelodysplastic syndrome by imaging flow cytometry and machine-learning assisted morphometrics
Cytometry Part B: Clinical Cytometry ( IF 2.3 ) Pub Date : 2020-12-07 , DOI: 10.1002/cyto.b.21975
Carina A Rosenberg 1 , Marie Bill 1 , Matthew A Rodrigues 2 , Mathias Hauerslev 1 , Gitte B Kerndrup 3 , Peter Hokland 4 , Maja Ludvigsen 1, 4
Affiliation  

The hallmark of myelodysplastic syndrome (MDS) remains dysplasia in the bone marrow (BM). However, diagnosing MDS may be challenging and subject to inter-observer variability. Thus, there is an unmet need for novel objective, standardized and reproducible methods for evaluating dysplasia. Imaging flow cytometry (IFC) offers combined analyses of phenotypic and image-based morphometric parameters, for example, cell size and nuclearity. Hence, we hypothesized IFC to be a useful tool in MDS diagnostics.

中文翻译:

通过成像流式细胞术和机器学习辅助形态计量学探索骨髓增生异常综合征患者的红细胞生成异常

骨髓增生异常综合征 (MDS) 的标志仍然是骨髓 (BM) 发育不良。然而,诊断 MDS 可能具有挑战性,并且受观察者间变异性的影响。因此,对于评估发育不良的新颖客观、标准化和可重复的方法存在未满足的需求。成像流式细胞术 (IFC) 提供对表型和基于图像的形态学参数的组合分析,例如细胞大小和核度。因此,我们假设 IFC 是 MDS 诊断中的有用工具。
更新日期:2020-12-07
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