Evidence map›Paper›PMID 39266547›Full record

ArticleNature communications2024

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 and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. Article
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  7. Applications and development of in situ nucleic acid visualization techniques.Frontiers in bioengineering and biotechnology · 2026
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Xilin YangElectrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.
Bijie BaiElectrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.
Yijie ZhangElectrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.
Musa AydinElectrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.ORCID 0000-0002-5825-2230
Yuzhu LiElectrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.
Sahan Yoruc SelcukElectrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.
Paloma Casteleiro CostaElectrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.ORCID 0000-0002-7824-9805
Zhen GuoElectrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.
Gregory A FishbeinDepartment of Pathology and Laboratory Medicine, David Geffen School of Medicine at the University of California, Los Angeles, CA, 90095, USA.ORCID 0000-0002-3632-5654
Karine AtlanDepartment of Pathology, Hadassah Hebrew University Medical Center, Jerusalem, 91120, Israel.
William Dean WallaceDepartment of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA.ORCID 0000-0002-9850-9723
Nir PillarElectrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA. npillar@g.ucla.edu.
Aydogan OzcanElectrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA. ozcan@ucla.edu.ORCID 0000-0002-0717-683X

Funding

TRD3: Data Analytics and Intelligent Systems (AI-ML-DL-Visualization)P41EB032840 · NIBIB · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Laura Marcu · 2022 to 2026
$6.7M
NIBIB NIH HHS P41 EB032840
6 · The paper itself

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.

Indexed as

AmyloidDeep LearningMicroscopy, FluorescenceStaining and LabelingAmyloidosisBirefringenceCongo RedHumansMicroscopy, PolarizationMyocardiumOptical ImagingPlaque, AmyloidAmyloidCongo Red

Identifiers

PMID39266547
PMCPMC11393327

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.