In European heart journal cardiovascular Imaging
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.
Raisi-Estabragh Zahra, Izquierdo Cristian, Campello Victor M, Martin-Isla Carlos, Jaggi Akshay, Harvey Nicholas C, Lekadir Karim, Petersen Steffen E
cardiac magnetic resonance, image-based diagnosis, machine learning, radiomics, texture analysis