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Keywords:

  • myelodysplastic syndromes;
  • flow cytometry;
  • cytomics;
  • machine learning

Abstract

Background:

The role of flow cytometry (FCM) in diagnosing myelodysplastic syndromes (MDS) remains controversial, because analysis of myeloid maturation may involve subjective interpretation of sometimes subtle patterns on multiparameter FCM.

Methods:

Using six-parameter marker combinations known to be useful in evaluating the myeloid compartment in MDS, we measured objective immunophenotypic differences between non-neoplastic (n = 25) and dysplastic (n = 17) granulopoiesis using a novel method, called Fisher information nonparametric embedding (FINE), that measures information distances among FCM datasets modeled as individual high-dimensional probability density functions, rather than as sets of two-dimensional histograms. Information-preserving component analysis (IPCA) was used to create information-optimized “rotated” two-dimensional histograms for visualizing myelopoietic immunophenotypes for each individual sample.

Results:

There was a consistent trend of segregation of higher-grade MDS (RAEB and RCMD) from benign by FINE analysis. This difference was accentuated in cases with morphologic dysgranulopoiesis and in cases with clonal cytogenetic abnormalities. However, lower grades of MDS or cases that lacked morphologic dysgranulopoiesis showed much greater overlap with non-neoplastic cases. Two cases of reactive left shift were consistently embedded within the higher-grade MDS group. IPCA yielded two-dimensional histogram projections for each individual case by relative weighting of measured cellular characteristics, optimized for preserving information distances derived through FINE.

Conclusions:

Objective analysis by information geometry supports the conclusions of previous studies that there are immunophenotypic differences in the maturation patterns of benign granulopoiesis and high grade MDS, but also reinforces the known pitfalls of overlap between low-grade MDS and benign granulopoiesis and overlap between reactive granulocytic left shifts and dysplastic granulopoiesis. © 2011 International Clinical Cytometry Society