title: Automated analysis of flow cytometric data for measuring neutrophil CD64 expression using a multi-instrument compatible probability state model.
abstract: BACKGROUND
  Leuko64™ (Trillium Diagnostics) is a flow cytometric assay that measures neutrophil CD64 expression and serves as an in vitro indicator of infection/sepsis or the presence of a systemic acute inflammatory response. Leuko64 assay currently utilizes QuantiCALC, a semiautomated software that employs cluster algorithms to define cell populations. The software reduces subjective gating decisions, resulting in interanalyst variability of <5%. We evaluated a completely automated approach to measuring neutrophil CD64 expression using GemStone™ (Verity Software House) and probability state modeling (PSM).
  
  
  METHODS
  Four hundred and fifty-seven human blood samples were processed using the Leuko64 assay. Samples were analyzed on four different flow cytometer models: BD FACSCanto II, BD FACScan, BC Gallios/Navios, and BC FC500. A probability state model was designed to identify calibration beads and three leukocyte subpopulations based on differences in intensity levels of several parameters. PSM automatically calculates CD64 index values for each cell population using equations programmed into the model. GemStone software uses PSM that requires no operator intervention, thus totally automating data analysis and internal quality control flagging. Expert analysis with the predicate method (QuantiCALC) was performed. Interanalyst precision was evaluated for both methods of data analysis.
  
  
  RESULTS
  PSM with GemStone correlates well with the expert manual analysis, r(2) = 0.99675 for the neutrophil CD64 index values with no intermethod bias detected. The average interanalyst imprecision for the QuantiCALC method was 1.06% (range 0.00-7.94%), which was reduced to 0.00% with the GemStone PSM. The operator-to-operator agreement in GemStone was a perfect correlation, r(2) = 1.000.
  
  
  CONCLUSIONS
  Automated quantification of CD64 index values produced results that strongly correlate with expert analysis using a standard gate-based data analysis method. PSM successfully evaluated flow cytometric data generated by multiple instruments across multiple lots of the Leuko64 kit in all 457 cases. The probability-based method provides greater objectivity, higher data analysis speed, and allows for greater precision for in vitro diagnostic flow cytometric assays.
authors.affiliation: Trillium Diagnostics, LLC, Brewer, Maine.
authors.forename: Linda
authors.initials: L
authors.lastname: Wong
authors.affiliation: Verity Software House, Topsham, Maine.
authors.forename: Beth L
authors.initials: BL
authors.lastname: Hill
authors.affiliation: Verity Software House, Topsham, Maine.
authors.forename: Benjamin C
authors.initials: BC
authors.lastname: Hunsberger
authors.affiliation: Verity Software House, Topsham, Maine.
authors.forename: C Bruce
authors.initials: CB
authors.lastname: Bagwell
authors.affiliation: Trillium Diagnostics, LLC, Brewer, Maine.
authors.forename: Adam D
authors.initials: AD
authors.lastname: Curtis
authors.affiliation: Trillium Diagnostics, LLC, Brewer, Maine.
authors.forename: Bruce H
authors.initials: BH
authors.lastname: Davis
mesh_terms: D000465:Algorithms; D001424:Bacterial Infections / Q000175:diagnosis; D019295:Computational Biology / Q000379:methods*; D005434:Flow Cytometry / Q000379:methods*; D006801:Humans; D007249:Inflammation / Q000175:diagnosis; D009504:Neutrophils / Q000166:cytology / Q000276:immunology*; D017452:Receptors, IgG / Q000096:biosynthesis*; D018805:Sepsis / Q000175:diagnosis
chemical_list: D017452:Receptors, IgG
keywords: GemStoneTM; Leuko64TM; automated analysis; clinical cytometry; infection detection; innate immunity; laboratory improvement; leukocyte analysis; measurement error; quality practice improvement; sepsis assay