Flow cytometry (FC) instruments settings classically rely on local establishment of photomultipliers (PMT) voltages adapted to the measurements expected to be performed. In the era of multiparameter FC (MFC), it appears more and more desirable that comparable patterns of fluorescence are obtained in different settings. This relies on a harmonization of settings between instruments. Although this has been shown to be feasible within a given brand of flow cytometers, little information is available about broader comparisons in a given center or in a multicenter fashion. Here, we report a two-phase series of experiments first performed between a Canto II (BD Biosciences) and a Navios (Beckman Coulter) instruments in the same center. PMT values adjusted on the reference instrument (RI) Canto II were used to establish target values for PMT settings on the paired Navios practice instrument (PI). This allowed to show the good correlation of all but peaks 1 and 2 of Rainbow V R beads between RI and PI. Using 4-or 8-color stained leukocytes, the similitude of the settings was further confirmed. A complex set of matrices was then established between five centers all equipped with both instruments. Using Bland & Altman difference comparisons for median fluorescence values, it was shown that using either Rainbow beads or CD16 stained polymorphonuclears to set-up target values on the RI CantoII, highly superimposable results could be obtained on all 9 PI. The latter were obtained using Rainbow beads or Compbeads V R for comparisons. In summary, this two-phase study demonstrates the feasibility of different methods allowing for a robust harmonization of settings for MFC. V C 2013 International Society for Advancement of Cytometry

No abstract

Acute myeloid leukemias (AMLs) are hematologic malignancies with varied molecular and immunophenotypic profiles, making them difficult to diagnose and classify. High-dimensional analysis algorithms might increase the utility of multicolor flow cytometry for AML diagnosis and follow-up. The objective of the present study was to assess whether a Compass database-guided analysis can be used to achieve rapid and accurate diagnoses. We conducted this study to determine whether this method could be employed to pilote the genetic and molecular tests and to objectively identify different-from-normal (DfN) patterns to improve measurable residual disease follow-up in AML. Three Compass databases were built using Infinicyt 2.0 software, including normal myeloid-committed hematopoietic precursors (n = 20) and AML blasts harboring the most frequent recurrent genetic abnormalities (n = 50). The diagnostic accuracy of the Compass database-guided analysis was evaluated in a prospective validation study (125 suspected AML patients). This method excluded AML associated with the following genetic abnormalities: t(8;21), t(15;17), inv(16), and KMT2A translocation, with 92% sensitivity [95% confidence interval (CI): 78.6%–98.3%] and a 98.5% negative predictive value (95% CI: 90.6%–99.8%). Our data showed that the Compass database-guided analysis could identify phenotypic differences between AML groups, representing a useful tool for the identification of DfN patterns.

Acute myeloid leukemias (AMLs) are a group of hematologic malignancies that are heterogeneous in their molecular and immunophenotypic profiles. Identification of the immunophenotypic differences between AML blasts and normal myeloid hematopoietic precursors (myHPCs) is a prerequisite to achieving better performance in AML measurable residual disease follow-ups. In the present study, we applied high-dimensional analysis algorithms provided by the Infinicyt 2.0 and Cytobank software to evaluate the efficacy of antibody combinations of the EuroFlow AML/myelodysplastic syndrome panel to distinguish AML blasts with recurrent genetic abnormalities (n = 39 AML samples) from normal CD45low CD117+ myHPCs (n = 23 normal bone marrow samples). Two types of scores were established to evaluate the abilities of the various methods to identify the most useful parameters/markers for distinguishing between AML blasts and normal myHPCs, as well as to distinguish between different AML groups. The Infinicyt Compass database-guided analysis was found to be a more user-friendly tool than other analysis methods implemented in the Cytobank software. According to the developed scoring systems, the principal component analysis based algorithms resulted in better discrimination between AML blasts and myHPCs, as well as between blasts from different AML groups. The most informative markers for the discrimination between myHPCs and AML blasts were CD34, CD36, human leukocyte antigen-DR (HLA-DR), CD13, CD105, CD71, and SSC, which were highly rated by all evaluated analysis algorithms. The HLA-DR, CD34, CD13, CD64, CD33, CD117, CD71, CD36, CD11b, SSC, and FSC were found to be useful for the distinction between blasts from different AML groups associated with recurrent genetic abnormalities. This study identified both benefits and the drawbacks of integrating multiple high-dimensional algorithms to gain complementary insights into the flow-cytometry data.