Exploring dyserythropoiesis in patients with myelodysplastic syndrome by imaging flow cytometry and machine-learning assisted morphometrics
| Autor: | Carina A. Rosenberg, Mathias Hauerslev, Matthew A. Rodrigues, Marie Bill, G. Kerndrup, Maja Ludvigsen, Peter Hokland |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Male
0301 basic medicine Imaging flow cytometry Erythroblasts Cell computer.software_genre RECOMMENDATIONS Machine Learning ERYTHROID DYSPLASIA 0302 clinical medicine hemic and lymphatic diseases IMPLEMENTATION MDS Erythropoiesis Aged 80 and over Middle Aged imaging flow cytometry Flow Cytometry medicine.anatomical_structure 030220 oncology & carcinogenesis Female Adult EXPRESSION Histology high-throughput morphometric quantification Biology Machine learning CLASSIFICATION Pathology and Forensic Medicine 03 medical and health sciences Erythroblast medicine Humans ANEMIA Aged Morphometrics Cytopenia business.industry ERYTHROBLASTS Cell Biology medicine.disease myelodysplastic syndrome dyserythropoiesis 030104 developmental biology Dysplasia Myelodysplastic Syndromes CELLS DIAGNOSTIC UTILITY Artificial intelligence Bone marrow business computer |
| Zdroj: | Rosenberg, C A, Bill, M, Rodrigues, M A, Hauerslev, M, Kerndrup, G B, Hokland, P & Ludvigsen, M 2021, ' Exploring dyserythropoiesis in patients with myelodysplastic syndrome by imaging flow cytometry and machine-learning assisted morphometrics ', Cytometry. Part B: Clinical Cytometry, vol. 100, no. 5, pp. 554-567 . https://doi.org/10.1002/cyto.b.21975 |
| DOI: | 10.1002/cyto.b.21975 |
| Popis: | BACKGROUND: 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.METHODS: Using a different-from-normal approach, we investigated dyserythropoiesis by quantifying morphometric features in a median of 5953 erythroblasts (range: 489-68,503) from 14 MDS patients, 11 healthy donors, 6 non-MDS controls with increased erythropoiesis, and 6 patients with cytopenia.RESULTS: First, we morphometrically confirmed normal erythroid maturation, as immunophenotypically defined erythroid precursors could be sequenced by significantly decreasing cell-, nuclear- and cytoplasm area. In MDS samples, we demonstrated cell size enlargement and increased fractions of macronormoblasts in late-stage erythroblasts (both p CONCLUSION: We demonstrate proof-of-concept results of the applicability of automated IFC-based techniques to study and quantify morphometric changes in dyserythropoietic BM cells. We propose that IFC holds great promise as a powerful and objective tool in the complex setting of MDS diagnostics with the potential for minimizing inter-observer variability. |
| Databáze: | OpenAIRE |
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