Robust FCS Parsing: Exploring 211,359 Public Files

When it comes to data storage, the field of flow cytometry is fairly standardized, thanks to the flow cytometry standard (FCS) file format. The structure of FCS files is described in the FCS specification. Software that strictly complies with the FCS specification is guaranteed to be interoperable (in terms of exchange via FCS files). Nowadays, software interoperability is crucial for eco system, as FCS files are frequently shared, and workflows rely on more than one piece of software (e.g., acquisition and analysis software). Ideally, software developers strictly follow the FCS specification. Unfortunately, this is not always the case, which resulted in various nonconformant FCS files being generated over time. Therefore, robust FCS parsers must be developed, which can handle a wide variety of nonconformant FCS files, from different resources. Development of robust FCS parsers would greatly benefit from a fully fledged set of testing files. In this study, readability of 211,359 public FCS files was evaluated. Each FCS file was checked for conformance with the FCS specification. For each data set, within each FCS file, validated parse results were obtained for the TEXT segment. Highly space efficient testing files were generated. FlowCore was benchmarked in depth, by using the validated parse results, the generated testing files, and the original FCS files. Robustness of FlowCore (as measured by testing against 211,359 files) was improved by re-implementing the TEXT segment parser. Altogether, this study provides a comprehensive resource for FCS parser development, an in-depth benchmark of FlowCore, and a concrete proposal for improving FlowCore

CD123 expression levels in 846 acute leukemia patients based on standardized immunophenotyping

Background: While it is known that CD123 is normally strongly expressed on plasmacytoid dendritic cells and completely absent on nucleated red blood cells, detailed information regarding CD123 expression in acute leukemia is scarce and, if available, hard to compare due to different methodologies. Methods: CD123 expression was evaluated using standardized EuroFlow immunophenotyping in 139 pediatric AML, 316 adult AML, 193 pediatric BCP-ALL, 69 adult BCP-ALL, 101 pediatric T-A

Standardised immunophenotypic analysis of myeloperoxidase in acute leukaemia

Given its myeloid-restricted expression, myeloperoxidase (MPO) is typically used for lineage assignment (myeloid vs. lymphoid) during acute leukaemia (AL) diagnostics. In the present study, a robust flow cytometric definition for MPO positivity was established based on the standardised EuroFlow protocols, the standardised Acute Leukaemia Orientation Tube and 1734 multicentre AL cases (with confirmed assay stability). The best diagnostic performance was achieved by defining MPO positivity as ≥20% of the AL cells exceeding a lymphocyte-based threshold. The methodology employed should be applicable to any form of standardised flow cytometry

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

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

Quality assessment of a large multi-center flow cytometric dataset of acute myeloid leukemia patients-a EuroFlow study

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 datas

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

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