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Related Concept Videos

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Two basic types of preparation are used to visualize specimens with a light microscope: wet mounts and fixed specimens.
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Immunocytochemistry (ICC) and immunohistochemistry (IHC) are techniques that use antibodies to check for specific proteins or antigens in a sample. The technique was first published by Albert Coons in 1941 to detect the presence of pneumococcal antigen in tissue sections from mice infected with Pneumococcus. Immunocytochemistry helps localization of proteins or antigens in individual cells like blood cells, stem cells, etc., while immunohistochemistry does the same for tissue samples.
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Updated: Jan 9, 2026

Histological-Based Stainings Using Free-Floating Tissue Sections
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PRompt-aware Interactive Stain Model for Unpaired H&E-to-IHC Stain Translation.

Chujie Zhang, Yangyang Xie, Yinhao Li

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    Summary

    Virtual staining offers a cost-effective alternative to traditional immunohistochemistry (IHC) by converting H&E images. Our PRISM framework achieves superior H&E-to-IHC stain translation, enhancing histopathological image analysis.

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    Area of Science:

    • Digital pathology
    • Computational imaging
    • Histopathology

    Background:

    • Traditional immunohistochemistry (IHC) is resource-intensive.
    • Virtual staining aims to generate IHC images from H&E slides.
    • Developing accurate H&E-to-IHC stain translation models is crucial.

    Purpose of the Study:

    • To introduce PRompt-aware Interactive Stain Model (PRISM), a novel framework for unpaired H&E-to-IHC stain translation.
    • To enhance histopathological image analysis through improved virtual staining techniques.
    • To develop a universal translation model for diverse histopathological image analysis tasks.

    Main Methods:

    • Developed the Style-Prompt Integrated Residual Image Translator Generator (SPIRIT-G) with a Prompt-Aware Fusion Layer.
    • Implemented the Dual Auxiliary Classifier Attention Discriminator (DA-CAD) with stain type identification.
    • Utilized learned priors for capturing complex relationships among tasks and modalities, moving beyond one-hot encoding.

    Main Results:

    • Achieved state-of-the-art results across five distinct H&E-to-IHC translation tasks on two public datasets.
    • Demonstrated significant improvements in structure preservation and staining pattern fidelity.
    • Validated PRISM's effectiveness as a universal translation model.

    Conclusions:

    • PRISM offers a powerful and effective solution for virtual staining in histopathology.
    • The framework enhances the utility of H&E stained images for diagnostic purposes.
    • PRISM represents a significant advancement in computational pathology and digital image analysis.