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An Open-Source Workflow for Semi-Automated Spatial Profiling of Multiplex Immunofluorescent Images.

Alisha Dabb1,2, Cynthia Morgan1,2, Sophia Noble1

  • 1Malaghan Institute of Medical Research, Wellington, New Zealand.

Current Protocols
|March 18, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces QuPath, a free software for analyzing multiplex immunofluorescence images. It offers accessible, standardized methods for spatial analysis, improving tissue structure and cellular organization quantification for research.

Keywords:
QuPathcell clusteringimmunofluorescence microscopypythonspatial

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Area of Science:

  • Biomedical Imaging
  • Computational Biology
  • Pathology

Background:

  • Multiplex immunofluorescence microscopy enables detailed cellular and spatial analysis in tissues.
  • Advances in computational methods enhance data extraction from multiplex images.
  • Existing spatial analysis pipelines often lack accessibility and reproducibility due to technical complexity or proprietary software.

Purpose of the Study:

  • To present accessible, standardized protocols for semi-automated spatial analysis of multiplex immunofluorescence images using free, open-source software.
  • To detail methods for quantifying cellular organization and tissue structure in multiplex images.
  • To facilitate reproducible spatial profiling for translational research and biomarker discovery.

Main Methods:

  • Utilized QuPath software for semi-automated spatial analysis of 2D multiplex immunofluorescence images.
  • Employed object and pixel classification, cell distance, and cluster measurements for spatial profiling.
  • Incorporated training images, basic scripting for batch processing, and a browser-based tool for data consolidation and reporting.

Main Results:

  • Developed and validated protocols for spatial analysis of multiplex immunofluorescence images using QuPath.
  • Demonstrated objective and standardized analysis through training images and batch processing.
  • Provided a pipeline for automated reporting of spatial data, including cell plots, measurements, and clustering.

Conclusions:

  • QuPath offers an accessible, reproducible, and scalable solution for spatial analysis of multiplex immunofluorescence microscopy images.
  • The presented protocols enhance the quantification of cellular organization and tissue structure.
  • This approach strengthens the integration of spatial data into translational research, biomarker discovery, and mechanistic studies.