IntegrAlign: A comprehensive tool for multi-immunofluorescence panel integration through image alignment

2025 · doi:10.1101/2025.04.10.648082
preprint OA: closed
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Abstract

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 analyzed 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 Implementation IntegrAlign is open-source, implemented in Python, and freely available under the MIT license at https://github.com/CAUXlab/IntegrAlign .
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Abstract

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 analyzed 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 Implementation IntegrAlign is open-source, implemented in Python, and freely available under the MIT license at https://github.com/CAUXlab/IntegrAlign. Competing Interest Statement The authors have declared no competing interest.

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last seen: 2026-05-20T01:45:00.602351+00:00