Aanei, C.M. (Carmen Mariana)

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    Automated identification of leukocyte subsets improves standardization of database-guided expert-supervised diagnostic orientation in acute leukemia: a EuroFlow study
    (2021) Fluxá, R. (Rafael); Montero, J. (Juan); Grigore, G. (Georgiana); Buracchi, C. (Chiara); Fernández, P. (Paula); Morf, D. (Daniela); Orfao, A. (Alberto); Nierkens, S. (Stefan); Mejstrikova, E. (Ester); Barrena, S. (Susana); Sedek, L. (Lukasz); Bie, M. (Maaike) de; Lhermitte, L. (Ludovic); Sobral-da-Costa, E. (Elaine); Szczepanski, T. (Tomasz); Barreau, S. (Sylvain); Aanei, C.M. (Carmen Mariana); Burgos, L. (Leire); Brüggemann, M. (Monika); Dongen, J.J.M. (Jacques J. M.) van; Caetano, J. (Joana); Gaipa, G. (Giuseppe); Hernández-Delgado, A. (Alejandro); Sluijs-Gelling, A. (Alita) van der; Lecrevisse, Q. (Quentin); Velden, V.H.J. (Vicent H. J.) van der; Pedreira, C.E. (Carlos E.)
    Precise classification of acute leukemia (AL) is crucial for adequate treatment. EuroFlow has previously designed an AL orientation tube (ALOT) to guide toward the relevant classification panel and final diagnosis. In this study, we designed and validated an algorithm for automated (database-supported) gating and identification (AGI tool) of cell subsets within samples stained with ALOT. A reference database of normal peripheral blood (PB,n = 41) and bone marrow (BM;n = 45) samples analyzed with the ALOT was constructed, and served as a reference for the AGI tool to automatically identify normal cells. Populations not unequivocally identified as normal cells were labeled as checks and were classified by an expert. Additional normal BM (n = 25) and PB (n = 43) and leukemic samples (n = 109), analyzed in parallel by experts and the AGI tool, were used to evaluate the AGI tool. Analysis of normal PB and BM samples showed low percentages of checks (<3% in PB, <10% in BM), with variations between different laboratories. Manual analysis and AGI analysis of normal and leukemic samples showed high levels of correlation between cell numbers (r(2) > 0.95 for all cell types in PB andr(2) > 0.75 in BM) and resulted in highly concordant classification of leukemic cells by our previously published automated database-guided expert-supervised orientation tool for immunophenotypic diagnosis and classification of acute leukemia (Compass tool).
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    Quality assessment of a large multi-center flow cytometric dataset of acute myeloid leukemia patients-a EuroFlow study
    (2022) Grigore, G. (Georgiana); Fernández, P. (Paula); Vieira-de-Mello, F. (Fabiana); Orfao, A. (Alberto); Nierkens, S. (Stefan); Bras, A.E. (Anne E.); Matarraz, S. (Sergio); Aanei, C.M. (Carmen Mariana); Burgos, L. (Leire); Dongen, J.J.M. (Jacques J. M.) van; Sluijs-Gelling, A. (Alita) van der; Philippé, J. (Jan); Velden, V.H.J. (Vicent H. J.) van der
    Simple Summary Flow cytometry allows detailed characterization of large numbers of cells and plays an important role in the diagnosis of acute myeloid leukemia. To facilitate analysis of flowcytometric data, reference databases of normal bone marrow samples and samples from acute myeloid leukemia patients, together with new software tools, are required. We here report on the building of a large database of acute myeloid leukemia patients (n = 1142) and 22 normal samples. We report on the quality assessment procedure used and its validation, discuss potential pitfalls, and provide possible solutions for avoiding such flaws in the construction of other databases. Our data show that obtaining and collecting reproducible flow cytometric data over time and across centers is feasible, but also that strict quality assessment remains crucial, even when standardized protocols for staining and instrument settings are being used in a multicenter setting. Flowcytometric analysis allows for detailed identification and characterization of large numbers of cells in blood, bone marrow, and other body fluids and tissue samples and therefore contributes to the diagnostics of hematological malignancies. Novel data analysis tools allow for multidimensional analysis and comparison of patient samples with reference databases of normal, reactive, and/or leukemia/lymphoma patient samples. Building such reference databases requires strict quality assessment (QA) procedures. Here, we compiled a datase