Automated Analysis of GPI-Deficient Leukocyte Flow Cytometric Data Using GemStone™

Background: Flow Cytometry is widely used for enumeration of hematopoietic stem cell (SC) levels in bone marrow, cord blood, peripheral blood, and apheresis products. The ISHAGE single-platform gating method is considered by many to be the standard for CD34+ SC enumeration. However, attempts at uniform application of this ISHAGE method have met with only partial success. We propose an automated, multivariate classification approach for SC analysis based on Probability State Modeling (TM) (PSM). In this study, we compare the results from automated PSM analysis with manual ISHAGE gating analysis as performed by a trained analyst. Methods: A total of 258 samples were assayed on BD FACSCanto II flow cytometers using a stain-lyse-no-wash technique. Populations were defined using CD34, CD45, 7-AAD, and light scatter. BD TruCount (TM) bead tubes were used for absolute SC concentrations. A PSM was designed to classify events into beads, debris, intact-dead cells, and intact-live SC; run unattended and record results. Results: The ISHAGE and PSM methods show excellent agreement in estimating the concentration of #SC/mu L: slope = 1.009, r2 = 0.999. Bland-Altman Analysis for the SC concentration has an average difference (bias) of 2.018 SC/mu L. The 95% confidence interval is from -59.350 to 63.380 SC/mu L. The operator-to-operator agreement using PSM is perfect: r2 = 1.000. Conclusions: Automated PSM analysis of SC listmode data produces results that agree strongly with ISHAGE gate-based results. The PSM approach provides higher reproducibility, objectivity, and speed with accuracy at least equivalent to the ISHAGE method. (c) 2012 International Clinical Cytometry Society