Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning

Korsuk Sirinukunwattana; Enric Domingo; Susan D Richman; Keara L Redmond; Andrew Blake; Clare Verrill; Simon J Leedham; Aikaterini Chatzipli; Claire Hardy; Celina M Whalley; Chieh-hsi Wu; Andrew D Beggs; Ultan McDermott; Philip D Dunne; Angela Meade; Steven M Walker; Graeme I Murray; Leslie Samuel; Matthew Seymour; Ian Tomlinson; Phil Quirke; Timothy Maughan; Jens Rittscher; Viktor H Koelzer

doi:10.1136/gutjnl-2019-319866

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Artificial intelligence/machine learning

Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning

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Korsuk Sirinukunwattana Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Oxford, UK Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK PubMed articles Google scholar articles
Enric Domingo Department of Oncology, University of Oxford, Oxford, UK PubMed articles Google scholar articles
Susan D Richman Department of Pathology and Tumour Biology, Leeds Institute of Cancer and Pathology, Leeds, UK PubMed articles Google scholar articles
Keara L Redmond Centre for Cancer Research and Cell Biology, Faculty of Medicine, Health and Life Sciences, Queen's University Belfast, Belfast, UK PubMed articles Google scholar articles
Andrew Blake Department of Oncology, University of Oxford, Oxford, UK PubMed articles Google scholar articles
Clare Verrill Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK Nuffield Department of Surgical Sciences and NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK PubMed articles Google scholar articles
Simon J Leedham Gastrointestinal Stem-cell Biology Laboratory, Oxford Centre for Cancer Gene Research, Wellcome Trust Centre for Human Genetics, Oxford, UK Translational Gastroenterology Unit, Experimental Medicine Division, Nuffield Department of Clinical Medicine, John Radcliffe Hospital, University of Oxford, Oxford, UK PubMed articles Google scholar articles
Aikaterini Chatzipli Wellcome Trust Sanger Institute, Hinxton, UK PubMed articles Google scholar articles
Claire Hardy Wellcome Trust Sanger Institute, Hinxton, UK PubMed articles Google scholar articles
Celina M Whalley Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK PubMed articles Google scholar articles
Chieh-hsi Wu Department of Statistics, University of Oxford, Oxford, UK PubMed articles Google scholar articles
Andrew D Beggs School of Cancer Sciences, University of Birmingham, Birmingham, UK PubMed articles Google scholar articles
Ultan McDermott Wellcome Trust Sanger Institute, Hinxton, UK PubMed articles Google scholar articles
Philip D Dunne Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast, UK PubMed articles Google scholar articles
Angela Meade MRC Clinical Trials Unit at University College London, London, UK PubMed articles Google scholar articles
Steven M Walker Almac Diagnostics Ltd, Craigavon, UK PubMed articles Google scholar articles
Graeme I Murray Department of Pathology, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, UK PubMed articles Google scholar articles
Leslie Samuel Department of Clinical Oncology, Aberdeen Royal Infirmary, Aberdeen, UK PubMed articles Google scholar articles
Matthew Seymour Department of Oncology, Leeds Institute of Cancer and Pathology, Leeds, UK PubMed articles Google scholar articles
Ian Tomlinson Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK Edinburgh Cancer Centre, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK PubMed articles Google scholar articles
Phil Quirke Department of Pathology and Tumour Biology, Leeds Institute of Cancer and Pathology, Leeds, UK PubMed articles Google scholar articles
Timothy Maughan CRUK/MRC Oxford Institute for Radiation Oncology, University of Oxford, Oxford, UK PubMed articles Google scholar articles
Jens Rittscher Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Oxford, UK Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK Ludwig Institute for Cancer Research, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK PubMed articles Google scholar articles
Viktor H Koelzer Department of Oncology, University of Oxford, Oxford, UK Nuffield Department of Medicine, University of Oxford, Oxford, UK Department of Pathology and Molecular Pathology, University of Zurich, Zurich, Switzerland PubMed articles Google scholar articles
On behalf of S:CORT consortium
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Correspondence to Professor Viktor H Koelzer, Department of Pathology and Molecular Pathology, University of Zurich Faculty of Medicine, Zurich, ZH, Switzerland; viktor.koelzer{at}usz.ch; Professor Jens Rittscher; jens.rittscher{at}eng.ox.ac.uk; Dr Enric Domingo; enric.domingo{at}oncology.ox.ac.uk

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Sirinukunwattana K, Domingo E, Richman SD On behalf of S:CORT consortium, et al

Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning

Gut 2021;70:544-554.

Publication history

Received September 16, 2019
Revised May 19, 2020
Accepted June 8, 2020
First published July 20, 2020.

Online issue publication

February 05, 2021

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© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

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