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arXiv · 2304.13736

Automated Whole Slide Imaging for Label-Free Histology using Photon Absorption Remote Sensing Microscopy

Abstract

The field of histology relies heavily on antiquated tissue processing and staining techniques that limit the efficiency of pathologic diagnoses of cancer and other diseases. Current staining and advanced labeling methods are often destructive and mutually incompatible, requiring new tissue sections for each stain. This prolongs the diagnostic process and depletes valuable biopsy samples. In this study, we present an alternative label-free histology platform using the first transmission-mode Photon Absorption Remote Sensing microscope. Optimized for automated whole slide scanning of unstained tissue samples, the system provides slide images at magnifications up to 40x that are fully compatible with existing digital pathology tools. The scans capture high quality and high-resolution images with subcellular diagnostic detail. After imaging, samples remain suitable for histochemical, immunohistochemical, and other staining techniques. Scattering and absorption (radiative and non-radiative) contrasts are shown in whole slide images of malignant human breast and skin tissues samples. Clinically relevant features are highlighted, and close correspondence and analogous contrast is demonstrated with one-to-one gold standard H&E stained images. Our previously reported pix2pix virtual staining model is applied to an entire whole slide image, showcasing the potential of this approach in whole slide label-free H&E emulation. This work is a critical advance for integrating label-free optical methods into standard histopathology workflows, both enhancing diagnostic efficiency, and broadening the number of stains that can be applied while preserving valuable tissue samples.

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BibTeXRIS

James E. D. Tweel, Benjamin R. Ecclestone, Marian Boktor, Deepak Dinakaran, John R. Mackey, Parsin Haji Reza. 2023-05-16. Automated Whole Slide Imaging for Label-Free Histology using Photon Absorption Remote Sensing Microscopy. https://doi.org/10.1109/tbme.2024.3355296

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