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- Title
Virtual birefringence imaging and histological staining of amyloid deposits in label-free tissue using autofluorescence microscopy and deep learning.
- Authors
Yang, Xilin; Bai, Bijie; Zhang, Yijie; Aydin, Musa; Li, Yuzhu; Selcuk, Sahan Yoruc; Casteleiro Costa, Paloma; Guo, Zhen; Fishbein, Gregory A.; Atlan, Karine; Wallace, William Dean; Pillar, Nir; Ozcan, Aydogan
- Abstract
Systemic amyloidosis involves the deposition of misfolded proteins in organs/tissues, leading to progressive organ dysfunction and failure. Congo red is the gold-standard chemical stain for visualizing amyloid deposits in tissue, showing birefringence under polarization microscopy. However, Congo red staining is tedious and costly to perform, and prone to false diagnoses due to variations in amyloid amount, staining quality and manual examination of tissue under a polarization microscope. We report virtual birefringence imaging and virtual Congo red staining of label-free human tissue to show that a single neural network can transform autofluorescence images of label-free tissue into brightfield and polarized microscopy images, matching their histochemically stained versions. Blind testing with quantitative metrics and pathologist evaluations on cardiac tissue showed that our virtually stained polarization and brightfield images highlight amyloid patterns in a consistent manner, mitigating challenges due to variations in chemical staining quality and manual imaging processes in the clinical workflow. Detecting amyloid deposits in tissue with Congo red can be limited by several factors, which can potentially lead to false diagnoses. Here, the authors use virtual birefringence imaging and virtual Congo red staining using autofluorescence of label-free human tissue, highlighting amyloid deposits in a consistent manner.
- Subjects
POLARIZATION microscopy; AMYLOID plaque; CONGO red (Staining dye); STAINS &; staining (Microscopy); POLARIZING microscopes
- Publication
Nature Communications, 2024, Vol 15, Issue 1, p1
- ISSN
2041-1723
- Publication type
Article
- DOI
10.1038/s41467-024-52263-z