Risk stratification of post-MI patients for ICD implantation using texture analysis to quantify heterogeneity of scar

Background Following myocardial infarction (MI), patients are at risk of sudden cardiac death (SCD) due to ventricular arrhythmia, which can be prevented with an implantable cardioverter-defibrillator (ICD). Recommendations for ICD implantation is currently based on left ventricular ejection fraction (LVEF), however less than a quarter of patients who receive ICDs based on LVEF have appropriate therapy. Heterogeneity of scar has been implicated in the development of re-entrant arrhythmias and SCD. Texture analysis (TA) is a method of quantifying heterogeneity of tissues in imaging, usually using statistical-based methods to evaluate distribution of grey-level pixels. This study aimed to determine whether TA could be used to quantify heterogeneity of scar as a method of accurately risk stratifying patients. Methods This was a retrospective blinded analysis of late-gadolinium enhanced cardiac magnetic resonance (LGE-CMR) images. Twenty post-MI patients who received ICDs were followed up for up to 686 days after implantation. Ten of these patients went on to have events and were categorised as high risk, while the remaining ten had no events on follow up and were categorised as low risk. TA was performed on regions of interest delineating