Caetano, J. (Joana)

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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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    Expert-independent classification of mature B-cell neoplasms using standardized flow cytometry: a multicentric study
    (2022) Böttcher, S. (Sebastian); Fluxá, R. (Rafael); Verde, J. (Javier); Montero, J. (Juan); Grigore, G. (Georgiana); Novakova, M. (Michaela); Fernández, P. (Paula); Orfao, A. (Alberto); Kalina, T. (Tomas); Engelmann, R. (Robby); Ritgen, M. (Matthias); Burgos, L. (Leire); Lange, S. (Sandra); Dongen, J.J.M. (Jacques J. M.) van; Caetano, J. (Joana); Lecrevisse, Q. (Quentin); Philippé, J. (Jan); Velden, V.H.J. (Vicent H. J.) van der; Pedreira, C.E. (Carlos E.)
    Reproducible expert-independent flow-cytometric criteria for the differential diagnoses between mature B-cell neoplasms are lacking. We developed an algorithm-driven classification for these lymphomas by flow cytometry and compared it to the WHO gold standard diagnosis. Overall, 662 samples from 662 patients representing 9 disease categories were analyzed at 9 laboratories using the previously published EuroFlow 5-tube-8-color B-cell chronic lymphoproliferative disease antibody panel. Expression levels of all 26 markers from the panel were plotted by B-cell entity to construct a univariate, fully standardized diagnostic reference library. For multivariate data analysis, we subsequently used canonical correlation analysis of 176 training cases to project the multidimensional space of all 26 immunophenotypic parameters into 36 2-dimensional plots for each possible pairwise differential diagnosis. Diagnostic boundaries were fitted according to the distribution of the immunophenotypes of a given differential diagnosis. A diagnostic algorithm based on these projections was developed and subsequently validated using 486 independent cases. Negative predictive values exceeding 92.1% were observed for all disease categories except for follicular lymphoma. Particularly high positive predictive values were returned in chronic lymphocytic leukemia (99.1%), hairy cell leukemia (97.2%), follicular lymphoma (97.2%), and mantle cell lymphoma (95.4%). Burkitt and CD101 diffuse large B-cell lymphomas were difficult to distinguish by the algorithm. A similar ambiguity was observed between marginal zone, lymphoplasmacytic, and CD102 diffuse large B-cell lymphomas. The specificity of the approach exceeded 98% for all entities. The univariate immunophenotypic library and the multivariate expert-independent diagnostic algorithm might contribute to increased reproducibility of future diagnostics in mature B-cell neoplasms.