Related Experiment Video
Updated: Jan 15, 2026
Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment
Published on: March 25, 2020
IntegrAlign: a comprehensive tool for multi-immunofluorescence panel integration through image alignment
Leo Hermet1,2,3, Leo Laoubi1,2,3, Martial Scavino1
1Centre Léon Bérard, Centre de Recherche en Cancérologie de Lyon, Univ Lyon, Université Claude Bernard Lyon 1, INSERM U1052, CNRS 5286, Lyon, 69008, France.
Motivation:
Tyramide-based multiplex-immunofluorescence (mIF) enables the simultaneous analysis of up to seven protein markers on a whole slide, providing a comprehensive approach to study the tumor microenvironment. Integrating multiple mIF panels through image alignment of serial slide significantly expands the number of cell populations analysed in a single space. IntegrAlign was developed to optimize this integration on serial whole slides, enhancing the value and applicability of -mIF for comprehensive spatial analyses and enabling biomarker discovery at scale.
Results:
IntegrAlign, leveraging the SimpleITK toolkit, applies a two-step alignment using rigid and B-spline transformations to integrate serial mIF whole slides. Validation on simulated and real datasets demonstrated alignment accuracy below the diameter of a cell nucleus (∼6 µm), outperforming existing methods. This precision enhances spatial analyses by combining extended phenotypic data, supporting novel insights into tissue architecture and cellular interactions.
Availability And Implemention:
IntegrAlign is open-source, implemented in Python, and freely available under the MIT license at https://github.com/CAUXlab/IntegrAlign.
