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

Next Generation Flow for highly sensitive and standardized detection of minimal residual disease in multiple myeloma

Stemcel biology/Regenerative medicine (incl. bloodtransfusion

Standardized flow cytometry for highly sensitive MRD measurements in B-cell acute lymphoblastic leukemia

A fully-standardized EuroFlow 8–color antibody panel and laboratory procedure was stepwise designed to measure minimal residual disease (MRD) in B-cell precursor (BCP) acute lymphoblastic leukemia (ALL) patients with a sensitivity of £1025, comparable to real-time quantitative polymerase chain reaction (RQ-PCR)–based MRD detection via antigen-receptor rearrangements. Leukocyte markers and the corresponding antibodies and fluorochromes were selected based on their contribution in separating BCP-ALL cells from normal/regenerating BCP cells in multidimensional principal component analyses. After 5 multicenter design-test-evaluate-redesign phases with a total of 319 BCP-ALL patients at diagnosis, two 8-color antibody tubes were selected, which allowed separation between normal and malignant BCP cells in 99% of studied patients. These 2 tubes were tested with a new erythrocyte bulk-lysis protocol allowing acquisition of high cell numbers in 377 bone marrow follow-up samples of 178 BCP-ALL patients. Comparison with RQ-PCR–based MRD data showed a clear positive relation between the percentage concordant cases and the number of cells acquired. For those samples with >4 million cells acquired, concordant results were obtained in 93% of samples. Most discordances were clarified upon high-throughput sequencing of antigen-receptor rearrangements and blind multicenter reanalysis of flow cytometric data, resulting in an unprecedented concordance of 98% (97% for samples with MRD 98% of patients with sensitivities at least similar to RQ-PCR (£1025), if sufficient cells (>4 3 106, preferably more) are evaluated

On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection

A new 1D radial fluid code, IMAGINE, is used to simulate the penetration of gas into a tokamak plasma during a massive gas injection (MGI). The main result is that the gas is in general strongly braked as it reaches the plasma, due to mechanisms related to charge exchange and (to a smaller extent) recombination. As a result, only a fraction of the gas penetrates into the plasma. Also, a shock wave is created in the gas which propagates away from the plasma, braking and compressing the incoming gas. Simulation results are quantitatively consistent, at least in terms of orders of magnitude, with experimental data for a D 2 MGI into a JET Ohmic plasma. Simulations of MGI into the background plasma surrounding a runaway electron beam show that if the background electron density is too high, the gas may not penetrate, suggesting a possible explanation for the recent results of Reux et al in JET (2015 Nucl. Fusion 55 093013)

Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

Relationship of edge localized mode burst times with divertor flux loop signal phase in JET

A phase relationship is identified between sequential edge localized modes (ELMs) occurrence times in a set of H-mode tokamak plasmas to the voltage measured in full flux azimuthal loops in the divertor region. We focus on plasmas in the Joint European Torus where a steady H-mode is sustained over several seconds, during which ELMs are observed in the Be II emission at the divertor. The ELMs analysed arise from intrinsic ELMing, in that there is no deliberate intent to control the ELMing process by external means. We use ELM timings derived from the Be II signal to perform direct time domain analysis of the full flux loop VLD2 and VLD3 signals, which provide a high cadence global measurement proportional to the voltage induced by changes in poloidal magnetic flux. Specifically, we examine how the time interval between pairs of successive ELMs is linked to the time-evolving phase of the full flux loop signals. Each ELM produces a clear early pulse in the full flux loop signals, whose peak time is used to condition our analysis. The arrival time of the following ELM, relative to this pulse, is found to fall into one of two categories: (i) prompt ELMs, which are directly paced by the initial response seen in the flux loop signals; and (ii) all other ELMs, which occur after the initial response of the full flux loop signals has decayed in amplitude. The times at which ELMs in category (ii) occur, relative to the first ELM of the pair, are clustered at times when the instantaneous phase of the full flux loop signal is close to its value at the time of the first ELM

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

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 dataset and developed a QA methodology of the EuroFlow Acute Myeloid Leukemia (AML) database, based on the eight-color EuroFlow AML panel consisting of six different antibody combinations, including four backbone markers. In total, 1142 AML cases and 42 normal bone marrow samples were included in this analysis. QA was performed on 803 AML cases using multidimensional analysis of backbone markers, as well as tube-specific markers, and data were compared using classical analysis employing median and peak expression values. Validation of the QA procedure was performed by re-analysis of >300 cases and by running an independent cohort of 339 AML cases. Initial evaluation of the final cohort confirmed specific immunophenotypic patterns in AML subgroups; the dataset therefore can reliably be used for more detailed exploration of the immunophenotypic variability of AML. Our data show the potential pitfalls and provide possible solutions for constructing large flowcytometric databases. In addition, the provided approach may facilitate the building of other databases and thereby support the development of novel tools for (semi)automated QA and subsequent data analysis

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 dataset and developed a QA methodology of the EuroFlow Acute Myeloid Leukemia (AML) database, based on the eight-color EuroFlow AML panel consisting of six different antibody combinations, including four backbone markers. In total, 1142 AML cases and 42 normal bone marrow samples were included in this analysis. QA was performed on 803 AML cases using multidimensional analysis of backbone markers, as well as tube-specific markers, and data were compared using classical analysis employing median and peak expression values. Validation of the QA procedure was performed by re-analysis of >300 cases and by running an independent cohort of 339 AML cases. Initial evaluation of the final cohort confirmed specific immunophenotypic patterns in AML subgroups; the dataset therefore can reliably be used for more detailed exploration of the immunophenotypic variability of AML. Our data show the potential pitfalls and provide possible solutions for constructing large flowcytometric databases. In addition, the provided approach may facilitate the building of other databases and thereby support the development of novel tools for (semi)automated QA and subsequent data analysis.Stemcel biology/Regenerative medicine (incl. bloodtransfusion

Immunophenotypic Analysis of Acute Megakaryoblastic Leukemia: A EuroFlow Study

Simple Summary Acute megakaryoblastic leukemia (AMKL) is a rare and heterogeneous subtype of acute myeloid leukemia (AML). We show that such patients can be identified by flowcytometric immunophenotyping using the standardized EuroFlow panel. AMKL patients show a unique immunophenotypic profile, and among AMKL patients, various subgroups can be distinguished. Acute megakaryoblastic leukemia (AMKL) is a rare and heterogeneous subtype of acute myeloid leukemia (AML). We evaluated the immunophenotypic profile of 72 AMKL and 114 non-AMKL AML patients using the EuroFlow AML panel. Univariate and multivariate/multidimensional analyses were performed to identify most relevant markers contributing to the diagnosis of AMKL. AMKL patients were subdivided into transient abnormal myelopoiesis (TAM), myeloid leukemia associated with Down syndrome (ML-DS), AML-not otherwise specified with megakaryocytic differentiation (NOS-AMKL), and AMKL-other patients (AML patients with other WHO classification but with flowcytometric features of megakaryocytic differentiation). Flowcytometric analysis showed good discrimination between AMKL and non-AMKL patients based on differential expression of, in particular, CD42a.CD61, CD41, CD42b, HLADR, CD15 and CD13. Combining CD42a.CD61 (positive) and CD13 (negative) resulted in a sensitivity of 71% and a specificity of 99%. Within AMKL patients, TAM and ML-DS patients showed higher frequencies of immature CD34+/CD117+ leukemic cells as compared to NOS-AMKL and AMKL-Other patients. In addition, ML-DS patients showed a significantly higher expression of CD33, CD11b, CD38 and CD7 as compared to the other three subgroups, allowing for good distinction of these patients. Overall, our data show that the EuroFlow AML panel allows for straightforward diagnosis of AMKL and that ML-DS is associated with a unique immunophenotypic profile