What is a Tissue Slide Scanner?

12. May 2025

Technological innovation is key to expanding the frontiers of modern life sciences.

Consider tissue analysis - as a field of enquiry, tissue analysis didn't exist until the advent of light microscopy. Each new generation of technology propelled our understanding of anatomical structures further. New staining methods, new imaging techniques and so on, have proven integral to countless areas of revolutionary studies. In-depth tissue analysis using high-end automated slide scanners as well as AI-assisted image analysis is the next paradigm shift.

A tissue slide scanner is an automated microscopy-based platform which combines whole-slide imaging with image analysis and thus offers unprecedented detail in cellular analysis. It enables researchers to explore the complexities of cells in their native tissue environments. Thus, tissue slide scanners provide insights into cell-to-cell interactions and microenvironmental dynamics. Additionally, the integration of multispectral imaging using liquid crystal tunable filers (LCTF), multispectral unmixing, and powerful computational tools enables a more comprehensive and quantitative analysis of tissue samples. This shift from qualitative to quantitative, context-rich analysis marks a significant leap in our ability to understand complex biological processes at the tissue level.

Current academic research, particularly studies employing instruments like our TissueFAXS SPECTRA, highlights the broad applications and capabilities of these sophisticated devices. 

Core Principles and Technology

At its core, a tissue slide scanner is designed for multiplexed fluorescence microscopy, focusing on the analysis of cells within their native tissue context. It leverages imaging and image analysis to extract quantitative information from stained cells and tissues. This approach allows for the comprehensive characterisation of the cellular phenotype, analysis of their functional properties, and assessment of morphological substructures and cell interactions.

Key Technological Features

Multispectral Imaging

Multispectral imaging acquires images across various wavelengths using a LCTF. It is a highly sophisticated process for various reasons:

• Enhanced Marker Detection: Multispectral imaging can simultaneously detect multiple markers by capturing images at different wavelengths (using the LCTF). This enables the imaging of several cellular components within a single tissue section, revealing complex cellular interactions and microenvironmental contexts.
• Reduction of Spectral Overlap: Advanced spectral unmixing algorithms are used to reduce the overlap of spectral signals, a common challenge in fluorescence microscopy. This is crucial in accurately assigning fluorescence signals to their respective sources, enhancing the specificity of detection.

Advanced Imaging and Light Sources

The integration of high-power LEDs and precise optical filters is vital for the following functionalities:

• Improved Resolution and Clarity: High-power LEDs provide intense, stable illumination, essential for high-resolution imaging. Combined with high-quality optical filters, this illumination ensures the captured images are clear and detailed.
• Flexible Wavelength Selection: LEDs allow for a wide range of wavelength selection, accommodating various fluorophores used in tissue staining. This flexibility is critical in multispectral imaging, where multiple wavelengths are needed.
• Minimized Photobleaching: LEDs typically produce less heat than traditional light sources, reducing the risk of photobleaching and preserving the integrity of the fluorescent dyes.

Image Analysis Software

The integration of advanced image analysis software in tissue slide scanners provides several key benefits:

• Complex Data Handling: It can manage and process the complex data generated by multispectral imaging. This includes image stitching, spectral unmixing, and signal quantification.
• Deep Quantitative Analysis: The software can perform in-depth quantitative analyses, such nuclei segmentation, phenotyping and phenotype interactions, tissue segmentation, dot detection (FISH), and much more. This analysis is vital for understanding tissue composition, cellular phenotypes, and functional states.
• Integration with AI and Machine Learning: Advanced software increasingly incorporates artificial intelligence and machine learning algorithms. These algorithms can learn from large datasets to improve nuclei segmentation and structure classification outputs.

In summary, the convergence of these advanced technological features in tissue slide scanners enables detailed, accurate, and comprehensive analysis of complex tissues. This capability advances our understanding of cellular and molecular mechanisms in various biological and pathological contexts.

Applications in Current Research

Recent studies utilising tissue slide scanners, such as those involving the TissueFAXS SPECTRA, demonstrate the instrument's versatility across various research fields:

1. Oncology: Automated image cytometry is increasingly used in oncology for characterising tumour microenvironments and evaluating the efficacy of immunotherapy e.g. in lung cancer².
2. Immune System Analysis: The multispectral slide scanner has facilitated research in immune checkpoint markers in glioma mechanisms, allowing for simultaneous scanning of multiple markers on tissue microarrays.
3. Neurology: a study of neurons involved in human arm movement was performed using an automated slide scanner to image transverse sections of whole nerve taken from human heart donors³.

Interested in Learning More About Tissue Image Cytometry?

Tissue slide scanners, exemplified by the TissueFAXS SPECTRA, represent a paradigm shift in tissue analysis and next-gen digital pathology. They offer a more comprehensive understanding of the cellular dynamics and interactions within tissue microenvironments, surpassing the capabilities of traditional methods like flow cytometry. As illustrated by recent studies, this technological advancement is pivotal in advancing our understanding of complex biological systems, from cancer research to the study of infectious diseases. Explore our website for more information on the capabilities and applications of tissue slide scanners.

 

References

1. Machine Learning Tissue Classifier from TissueGnostics. TissueGnostics. https://tissuegnostics.com/news-machine-learning-tissue-classifier-from-tissuegnostics. Published 4th May 2021. Accessed 8th February 2024.  

2. Jonke O. Artificial Intelligence in Biomedicine: A Global Outlook. TissueGnostics. https://tissuegnostics.com/images/pdfs/TG_Dossier_AI_in_Biomedicine.pdf. Accessed 8th February 2024.