TY - JOUR
T1 - Automated identification of leukocyte subsets improves standardization of database-guided expert-supervised diagnostic orientation in acute leukemia
T2 - a EuroFlow study
AU - EuroFlow Consortium
AU - Lhermitte, Ludovic
AU - Barreau, Sylvain
AU - Morf, Daniela
AU - Fernandez, Paula
AU - Grigore, Georgiana
AU - Barrena, Susana
AU - de Bie, Maaike
AU - Flores-Montero, Juan
AU - Brüggemann, Monika
AU - Mejstrikova, Ester
AU - Nierkens, Stefan
AU - Burgos, Leire
AU - Caetano, Joana
AU - Gaipa, Giuseppe
AU - Buracchi, Chiara
AU - da Costa, Elaine Sobral
AU - Sedek, Lukasz
AU - Szczepański, Tomasz
AU - Aanei, Carmen Mariana
AU - van der Sluijs-Gelling, Alita
AU - Delgado, Alejandro Hernández
AU - Fluxa, Rafael
AU - Lecrevisse, Quentin
AU - Pedreira, Carlos E.
AU - van Dongen, Jacques J.M.
AU - Orfao, Alberto
AU - van der Velden, Vincent H.J.
AU - van Dongen, J. J.M.
AU - Bitter, W. M.
AU - Lubbers, B. R.
AU - Teodosio, C. I.
AU - Zlei, M.
AU - van der Sluijs-Gelling, A. J.
AU - de Bie, F.
AU - de Bruin-Versteeg, S.
AU - van der Burg, M.
AU - Schilham, M. W.
AU - van der Velden, V. H.J.
AU - Langerak, A. W.
AU - te Marvelde, J.
AU - Bras, A. E.
AU - Schilperoord-Vermeulen, J.
AU - Jugooa, R.
AU - Heezen, K. C.
AU - Orfao, A.
AU - Almeida, J.
AU - Vidriales, M. B.
AU - Pérez-Andrés, M.
AU - Matarraz, S.
AU - Nierkens, S.
N1 - Publisher Copyright:
© 2020, The Author(s).
PY - 2021/1
Y1 - 2021/1
N2 - 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 (r2 > 0.95 for all cell types in PB and r2 > 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). Similar data were obtained using alternative, commercially available tubes, confirming the robustness of the developed tools. The AGI tool represents an innovative step in minimizing human intervention and requirements in expertise, toward a “sample-in and result-out” approach which may result in more objective and reproducible data analysis and diagnostics. The AGI tool may improve quality of immunophenotyping in individual laboratories, since high percentages of checks in normal samples are an alert on the quality of the internal procedures.
AB - 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 (r2 > 0.95 for all cell types in PB and r2 > 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). Similar data were obtained using alternative, commercially available tubes, confirming the robustness of the developed tools. The AGI tool represents an innovative step in minimizing human intervention and requirements in expertise, toward a “sample-in and result-out” approach which may result in more objective and reproducible data analysis and diagnostics. The AGI tool may improve quality of immunophenotyping in individual laboratories, since high percentages of checks in normal samples are an alert on the quality of the internal procedures.
UR - http://www.scopus.com/inward/record.url?scp=85091753367&partnerID=8YFLogxK
U2 - 10.1038/s41379-020-00677-7
DO - 10.1038/s41379-020-00677-7
M3 - Article
C2 - 32999413
AN - SCOPUS:85091753367
SN - 0893-3952
VL - 34
SP - 59
EP - 69
JO - Modern Pathology
JF - Modern Pathology
IS - 1
ER -