Digital pathology and image analysis in tissue biomarker research

Peter W. Hamilton, Peter Bankhead, Yinhai Wang, Ryan Hutchinson, Declan Kieran, Darragh G. McArt, Jacqueline James, Manuel Salto-Tellez

Research output: Contribution to journalArticle

84 Citations (Scopus)

Abstract

Digital pathology and the adoption of image analysis have grown rapidly in the last few years. This is largely due to the implementation of whole slide scanning, advances in software and computer processing capacity and the increasing importance of tissue-based research for biomarker discovery and stratified medicine. This review sets out the key application areas for digital pathology and image analysis, with a particular focus on research and biomarker discovery. A variety of image analysis applications are reviewed including nuclear morphometry and tissue architecture analysis, but with emphasis on immunohistochemistry and fluorescence analysis of tissue biomarkers. Digital pathology and image analysis have important roles across the drug/companion diagnostic development pipeline including biobanking, molecular pathology, tissue microarray analysis, molecular profiling of tissue and these important developments are reviewed. Underpinning all of these important developments is the need for high quality tissue samples and the impact of pre-analytical variables on tissue research is discussed. This requirement is combined with practical advice on setting up and running a digital pathology laboratory. Finally, we discuss the need to integrate digital image analysis data with epidemiological, clinical and genomic data in order to fully understand the relationship between genotype and phenotype and to drive discovery and the delivery of personalized medicine.

Original languageEnglish
Pages (from-to)59-73
Number of pages15
JournalMethods
Volume70
Issue number1
Early online date15 Jul 2014
DOIs
Publication statusPublished - Nov 2014

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