3 research outputs found

    Automated database-guided expert-supervised orientation for immunophenotypic diagnosis and classification of acute leukemia

    Get PDF
    Precise classification of acute leukemia (AL) is crucial for adequate treatment. EuroFlow has previously designed an AL orientation tube (ALOT) to guide towards the relevant classification panel (T-cell acute lymphoblastic leukemia (T-ALL), B-cell precursor (BCP)-ALL and/or acute myeloid leukemia (AML)) and final diagnosis. Now we built a reference database with 656 typical AL samples (145 T-ALL, 377 BCP-ALL, 134 AML), processed and analyzed via standardized protocols. Using principal component analysis (PCA)-based plots and automated classification algorithms for direct comparison of single-cells from individual patients against the database, another 783 cases were subsequently evaluated. Depending on the database-guided results, patients were categorized as: (i) typical T, B or Myeloid without or; (ii) with a transitional component to another lineage; (iii) atypical; or (iv) mixed-lineage. Using this automated algorithm, in 781/783 cases (99.7%) the right panel was selected, and data comparable to the final WHO-diagnosis was already provided in >93% of cases (85% T-ALL, 97% BCP-ALL, 95% AML and 87% mixed-phenotype AL patients), even without data on the full-characterization panels. Our results show that database-guided analysis facilitates standardized interpretation of ALOT results and allows accurate selection of the relevant classification panels, hence providing a solid basis for designing future WHO AL classifications

    Automated database-guided expert-supervised orientation for immunophenotypic diagnosis and classification of acute leukemia

    No full text
    Precise classification of acute leukemia (AL) is crucial for adequate treatment. EuroFlow has previously designed an AL orientation tube (ALOT) to guide towards the relevant classification panel (T-cell acute lymphoblastic leukemia (T-ALL), B-cell precursor (BCP)-ALL and/or acute myeloid leukemia (AML)) and final diagnosis. Now we built a reference database with 656 typical AL samples (145 T-ALL, 377 BCP-ALL, 134 AML), processed and analyzed via standardized protocols. Using principal component analysis (PCA)-based plots and automated classification algorithms for direct comparison of single-cells from individual patients against the database, another 783 cases were subsequently evaluated. Depending on the database-guided results, patients were categorized as: (i) typical T, B or Myeloid without or; (ii) with a transitional component to another lineage; (iii) atypical; or (iv) mixed-lineage. Using this automated algorithm, in 781/783 cases (99.7%) the right panel was selected, and data comparable to the final WHO-diagnosis was already provided in >93% of cases (85% T-ALL, 97% BCP-ALL, 95% AML and 87% mixed-phenotype AL patients), even without data on the full-characterization panels. Our results show that database-guided analysis facilitates standardized interpretation of ALOT results and allows accurate selection of the relevant classification panels, hence providing a solid basis for designing future WHO AL classifications.The research was performed within the EuroFlow Consortium, which started with an EU-FP6 grant (LSHB-CT-2006-018708) and obtained sustainability by protecting and licensing intellectual property, thereby obtaining royalties, which are exclusively being used for supporting the EuroFlow research program (chairmen: JJMvD and AO). LS, JB and TS were supported by STRATEGMED3/304586/5/NCBR/2017 PersonALL grant of the Polish National Center for Research and Development. ESC acknowledges FAPERJ, Rio de Janeiro, Brazil (E26/110.105/2014; E26/102.191/2013) and Conselho Nacional de Desenvolvimento Científico e Tecnológico—CNPQ of Brazil (400194/2014-7). AO, SM and AL acknowledge the Instituto de Salud Carlos III (MINECO, Madrid, Spain) for the DTS15/00119, and CIBERONC-FEDER-CB16/12/00400 grants. EM, OH, TK and MN were supported by Ministry of Health grant number 15-28525A and NPU LO1604. The research for this manuscript was in part performed within the framework of the Erasmus Postgraduate School Molecular Medicine.Peer Reviewe
    corecore