Can I read Reliable Computational Quantification of Liver Fibrosis Is Compromised by Inherent Staining Variation on EtoBox?

Reliable Computational Quantification of Liver Fibrosis Is Compromised by Inherent Staining Variation by Astbury, Stuart (author);Grove, Jane I (author);Dorward, David A (author);Guha, Indra N (author);Fallowfield, Jonathan A (author);Kendall, Timothy J (author) is a Medicine article available to read on EtoBox.

What is Reliable Computational Quantification of Liver Fibrosis Is Compromised by Inherent Staining Variation about?

## Abstract Biopsy remains the gold‐standard measure for staging liver disease, both to inform prognosis and to assess the response to a given treatment. Semiquantitative scores such as the Ishak fibrosis score are used for evaluation. These scores are utilised in clinical trials, with the US Food and Drug Administration mandating particular scores as inclusion criteria for participants and using the change in score as evidence of treatment efficacy. There is an urgent need for improved, quantitative assessment of liver biopsies to detect small incremental changes in liver architecture over the course of a clinical trial. Artificial intelligence (AI) methods have been proposed as a way to increase the amount of information extracted from a biopsy and to potentially remove bias introduced by manual scoring. We have trained and evaluated an AI tool for measuring the amount of scarring in sections of picrosirius red‐stained liver. The AI methodology was compared with both manual scoring and widely available colour space thresholding. Four sequential sections from each case were stained on two separate occasions by two independent clinical laboratories using routine protocols to study

Who reads Reliable Computational Quantification of Liver Fibrosis Is Compromised by Inherent Staining Variation?

Author

Astbury, Stuart (author);Grove, Jane I (author);Dorward, David A (author);Guha, Indra N (author);Fallowfield, Jonathan A (author);Kendall, Timothy J (author)

Publisher

Wiley

Published

2021

Language

EN

Field

Medicine (Health Sciences)