Cardiac magnetic resonance radiomics: basic principles and clinical perspectives

Author:

Raisi-Estabragh Zahra12ORCID,Izquierdo Cristian3,Campello Victor M3,Martin-Isla Carlos3,Jaggi Akshay3,Harvey Nicholas C45,Lekadir Karim3,Petersen Steffen E12

Affiliation:

1. Department of advanced cardiovascular imaging, William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK

2. Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, West Smithfield, EC1A 7BE London, UK

3. Departament de Matemàtiques & Informàtica, Universitat de Barcelona, Gran Via de les Corts Catalanes, 585, 08007 Barcelona, Spain

4. MRC Lifecourse Epidemiology Unit, University of Southampton, Tremona Road, Southampton SO16 6YD, UK

5. NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Tremona Road, Southampton, SO16 6YD, UK

Abstract

Abstract Radiomics is a novel image analysis technique, whereby voxel-level information is extracted from digital images and used to derive multiple numerical quantifiers of shape and tissue character. Cardiac magnetic resonance (CMR) is the reference imaging modality for assessment of cardiac structure and function. Conventional analysis of CMR scans is mostly reliant on qualitative image analysis and basic geometric quantifiers. Small proof-of-concept studies have demonstrated the feasibility and superior diagnostic accuracy of CMR radiomics analysis over conventional reporting. CMR radiomics has the potential to transform our approach to defining image phenotypes and, through this, improve diagnostic accuracy, treatment selection, and prognostication. The purpose of this article is to provide an overview of radiomics concepts for clinicians, with particular consideration of application to CMR. We will also review existing literature on CMR radiomics, discuss challenges, and consider directions for future work.

Funder

London Medical Imaging and Artificial Intelligence Centre for Value Based Healthcare

Data to Early Diagnosis and Precision Medicine

Industrial Strategy Challenge Fund

NHS

British Heart Foundation Clinical Research Training Fellowship

Fulbright Predoctoral Research Award

National Institute for Health Research

NIHR

Publisher

Oxford University Press (OUP)

Subject

Cardiology and Cardiovascular Medicine,Radiology, Nuclear Medicine and imaging,General Medicine

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