Morphometry to identify subtypes of leukocytes

Abstract

Introduction: Recent studies in image cytometry evaluated the replacement of specific markers by morphological parameters. The aim of this study was to develop and evaluate a method to identify subtypes of leukocytes using morphometric data of the nuclei.

Method: The analyzed images were generated with a laser scanning cytometer. Two free programs were used for image analysis and statistical evaluation: Cellprofiler and Tanagra respectively. A sample of leukocytes with 200 sets of images (DAPI, CD45 and CD14) was analyzed. Using feature selection, the 20 best parameters were chosen to conduct cross-validation.

Results: The morphometric data identified the subpopulations of the analyzed leukocytes with a sensitivity and specificity of 0.95 per sample.

Conclusion: The present study is the first that identifies subpopulations of leukocytes by nuclear morphology.

Keywords: Image cytometry; Leukocyte count; Machine learning; Morphometry; Quantitative imaging; Texture.