How to Build an Image-Processing Pipeline for Automating Multiparameter Histocytometry Analysis

Curr Protoc. 2022 Mar;2(3):e380. doi: 10.1002/cpz1.380.

Abstract

Until relatively recently, analysis of imaging data has been primarily quantitative and limited to 3-4 markers. The advancement of various technologies overcoming this marker limitation provided the capability of analyzing multiparameter imaging data down to the single cell level, termed histocytometry. Currently, most published end-to-end histocytometric analysis of imaging data is performed using expensive commercial programs or freely available analysis packages that require significant knowledge of programming languages for execution. Here we present a protocol that performs cell segmentation, phenotyping and spatial analysis, using software with easy-to-use GUIs (graphical user interfaces). These protocols allow the user to derive spatial and phenotypical data for the analysis of multiparameter microscopic images from most imaging platforms in a low-cost manner. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Cell Segmentation and generation of histocytometric .csv file Basic Protocol 2: Phenotyping of cell populations Basic Protocol 3: Spatial relationship analyses of phenotyped populations Support Protocol 1: Nuclei Segmentation Accuracy Test Support Protocol 2: Correcting y-axis Inversion of Histocytometry Data Relative to Original Image File.

Keywords: cell segmentation; data analysis; histocytometry; imaging; immunophenotyping; microscopy; multiparameter; nearest neighbor; spatial analysis.

MeSH terms

  • Cell Nucleus
  • Image Processing, Computer-Assisted* / methods
  • Programming Languages
  • Software*