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

Xilin Yang; Bijie Bai; Yijie Zhang; Musa Aydin; Yuzhu Li; Sahan Yoruc Selcuk; Paloma Casteleiro Costa; Zhen Guo; Gregory A Fishbein; Karine Atlan; William Dean Wallace; Nir Pillar; Aydogan Ozcan

doi:10.1038/s41467-024-52263-z

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

Nat Commun. 2024 Sep 12;15(1):7978. doi: 10.1038/s41467-024-52263-z.

Authors

Xilin Yang^{1

2

3}, Bijie Bai^{1

2

3}, Yijie Zhang^{1

2

3}, Musa Aydin^{1

4}, Yuzhu Li^{1

2

3}, Sahan Yoruc Selcuk^{1

2

3}, Paloma Casteleiro Costa^{1

2

3}, Zhen Guo¹, Gregory A Fishbein⁵, Karine Atlan⁶, William Dean Wallace⁷, Nir Pillar^{8

9

10}, Aydogan Ozcan^{11

12

13

14}

Affiliations

¹ Electrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.
² Bioengineering Department, University of California, Los Angeles, CA, 90095, USA.
³ California NanoSystems Institute (CNSI), University of California, Los Angeles, CA, 90095, USA.
⁴ Department of Computer Engineering, Fatih Sultan Mehmet Vakif University, Istanbul, 34038, Turkey.
⁵ Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at the University of California, Los Angeles, CA, 90095, USA.
⁶ Department of Pathology, Hadassah Hebrew University Medical Center, Jerusalem, 91120, Israel.
⁷ Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA.
⁸ Electrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA. [email protected].
⁹ Bioengineering Department, University of California, Los Angeles, CA, 90095, USA. [email protected].
¹⁰ California NanoSystems Institute (CNSI), University of California, Los Angeles, CA, 90095, USA. [email protected].
¹¹ Electrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA. [email protected].
¹² Bioengineering Department, University of California, Los Angeles, CA, 90095, USA. [email protected].
¹³ California NanoSystems Institute (CNSI), University of California, Los Angeles, CA, 90095, USA. [email protected].
¹⁴ Department of Surgery, University of California, Los Angeles, CA, 90095, USA. [email protected].

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.

MeSH terms

Amyloid* / metabolism
Amyloidosis / diagnostic imaging
Amyloidosis / metabolism
Amyloidosis / pathology
Birefringence
Congo Red
Deep Learning*
Humans
Microscopy, Fluorescence* / methods
Microscopy, Polarization / methods
Myocardium / metabolism
Myocardium / pathology
Optical Imaging / methods
Plaque, Amyloid / diagnostic imaging
Plaque, Amyloid / metabolism
Plaque, Amyloid / pathology
Staining and Labeling* / methods

Substances

Amyloid
Congo Red