The summaries are free for public
use. The Chronic Liver Disease
Foundation will continue to add and
archive summaries of articles deemed
relevant to CLDF by the Board of
Trustees and its Advisors.
Abstract Details
A large-scale internal validation study of unsupervised virtual trichrome staining technologies on nonalcoholic steatohepatitis liver biopsies
Mod Pathol. 2020 Dec 9. doi: 10.1038/s41379-020-00718-1. Online ahead of print.
Joshua J Levy123, Nasim Azizgolshani4, Michael J Andersen Jr5, Arief Suriawinata5, Xiaoying Liu5, Mikhail Lisovsky5, Bing Ren5, Carly A Bobak6789, Brock C Christensen41011, Louis J Vaickus5
Author information
1Emerging Diagnostic and Investigative Technologies, Clinical Genomics and Advanced Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Hitchcock Medical Center, Lebanon, NH, 03756, USA. joshua.j.levy.gr@dartmouth.edu.
2Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, 03756, USA. joshua.j.levy.gr@dartmouth.edu.
3Program in Quantitative Biomedical Sciences, Geisel School of Medicine at Dartmouth, Lebanon, NH, 03756, USA. joshua.j.levy.gr@dartmouth.edu.
4Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, 03756, USA.
5Emerging Diagnostic and Investigative Technologies, Clinical Genomics and Advanced Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Hitchcock Medical Center, Lebanon, NH, 03756, USA.
6Program in Quantitative Biomedical Sciences, Geisel School of Medicine at Dartmouth, Lebanon, NH, 03756, USA.
7Thayer School of Engineering, Dartmouth College, Hanover, NH, 03755, USA.
8Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, NH, 03756, USA.
9The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH, 03756, USA.
10Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Lebanon, NH, 03756, USA.
11Department of Community and Family Medicine, Geisel School of Medicine at Dartmouth, Lebanon, NH, 03756, USA.
Abstract
Non-alcoholic steatohepatitis (NASH) is a fatty liver disease characterized by accumulation of fat in hepatocytes with concurrent inflammation and is associated with morbidity, cirrhosis and liver failure. After extraction of a liver core biopsy, tissue sections are stained with hematoxylin and eosin (H&E) to grade NASH activity, and stained with trichrome to stage fibrosis. Methods to computationally transform one stain into another on digital whole slide images (WSI) can lessen the need for additional physical staining besides H&E, reducing personnel, equipment, and time costs. Generative adversarial networks (GAN) have shown promise for virtual staining of tissue. We conducted a large-scale validation study of the viability of GANs for H&E to trichrome conversion on WSI (n = 574). Pathologists were largely unable to distinguish real images from virtual/synthetic images given a set of twelve Turing Tests. We report high correlation between staging of real and virtual stains ([Formula: see text]; 95% CI: 0.84-0.88). Stages assigned to both virtual and real stains correlated similarly with a number of clinical biomarkers and progression to End Stage Liver Disease (Hazard Ratio HR = 2.06, 95% CI: 1.36-3.12, p < 0.001 for real stains; HR = 2.02, 95% CI: 1.40-2.92, p < 0.001 for virtual stains). Our results demonstrate that virtual trichrome technologies may offer a software solution that can be employed in the clinical setting as a diagnostic decision aid.