Virtual birefringence imaging and histological staining of amyloid deposits in label-free tissue using autofluorescence microscopy and deep learning

Abstract

Systemic amyloidosis is a group of diseases characterized by the deposition of misfolded proteins in various organs and tissues, leading to progressive organ dysfunction and failure. Congo red stain is the gold standard chemical stain for the visualization of amyloid deposits in tissue sections, as it forms complexes with the misfolded proteins and shows a birefringence pattern under polarized light microscopy. However, Congo red staining is tedious and costly to perform, and prone to false diagnoses due to variations in the amount of amyloid, staining quality and expert interpretation through manual examination of tissue under a polarization microscope. Here, we report the first demonstration of virtual birefringence imaging and virtual Congo red staining of label-free human tissue to show that a single trained neural network can rapidly transform autofluorescence images of label-free tissue sections into brightfield and polarized light microscopy equivalent images, matching the histochemically stained versions of the same samples. We demonstrate the efficacy of our method with blind testing and pathologist evaluations on cardiac tissue where the virtually stained images agreed well with the histochemically stained ground truth images. Our virtually stained polarization and brightfield images highlight amyloid birefringence patterns in a consistent, reproducible manner while mitigating diagnostic challenges due to variations in the quality of chemical staining and manual imaging processes as part of the clinical workflow.

20 Pages, 5 Figures

References in corpus (8)

• PyTorch: An Imperative Style, High-Performance Deep Learning Library
• Conditional Generative Adversarial Nets
• Deep Learning-enabled Virtual Histological Staining of Biological Samples
• Artificial Intelligence for Digital and Computational Pathology
• Virtual histological staining of unlabeled autopsy tissue
• Virtual stain transfer in histology via cascaded deep neural networks
• Digital staining in optical microscopy using deep learning -- a review
• Virtual staining of defocused autofluorescence images of unlabeled tissue using deep neural networks

Cited by in corpus (4)

• Pixel super-resolved virtual staining of label-free tissue using diffusion models
• Virtual Gram staining of label-free bacteria using darkfield microscopy and deep learning
• Virtual Staining of Label-Free Tissue in Imaging Mass Spectrometry
• Label-free evaluation of lung and heart transplant biopsies using tissue autofluorescence-based virtual staining