Towards cardiac MRI based risk stratification in idiopathic dilated cardiomyopathy

Abstract

Sudden cardiac death (SCD) secondary to arrhythmia remains a risk in those with dilated cardiomyopathy (DCM), an implantable cardiac defibrillator (ICD) is an effective strategy to prevent SCD. Current guidelines recommend selection for ICD based on ejection fraction (EF) less than 35%, however, most SCD occurs in those with EF>35%. Although meta-analysis has demonstrated a survival benefit for primary prevention ICD in DCM, no randomised trial has shown a significant reduction in overall mortality including the most recent ‘Danish Study to Assess the Efficacy of ICDs in Patients With Non-Ischemic Systolic Heat Failure on Mortality’ study. Clearly, a more sophisticated selection strategy is required. Cardiac MRI (CMR) is an ideal non-invasive imaging technique which allows calculation of EF as well as tissue characterisation with gadolinium contrast, parametric mapping and feature tracking. Late gadolinium enhancement detects mid-wall fibrosis in approximately 30% of those with DCM, three meta-analyses have demonstrated an association between fibrosis in DCM and SCD, and those without fibrosis are at low risk of SCD. T1 mapping and extracellular volume (ECV) calculation are methods of demonstrating diffuse fibrosis in the myocardium. Raised ECV and native T1 have been associated with worse outcomes but the relationship to SCD has not been well studied. Undoubtedly, more research is required but CMR has several tools which offer incremental value above EF to improve risk stratification and consequent outcomes and resource utilisation in those with DCM.

Quantification of Myocardial Deformation Applying CMR-Feature-Tracking—All About the Left Ventricle?

“…CMR imaging was extensively shown to allow precise and accurate diagnosis of this cardiac disease [56]. Similar to findings in ICM, there is substantial evidence of CMR strain analyses as independent and powerful predictors of adverse outcome and mortality in patients suffering DCM [39,57,58]. Likewise, fast LAS offers incremental information for the prediction of adverse cardiac events in these patients [59].…”

Ischemic and non-ischemic patterns of late gadolinium enhancement in heart failure with reduced ejection fraction

“…Cardiovascular risk stratification is important and could be improved by the use of biomarkers or data from Holter electrocardiogram recordings [37][38][39]. Some studies have demonstrated that the presence of LGE predicts poor clinical outcomes such as hospitalization due to HF, fatal ventricular arrhythmias, and SCD, in patients with either an ischemic or nonischemic etiology of HF [8,26,[40][41][42][43][44]. Non-ischemic HF etiology is one of the predictors of LVEF recovery [45].…”

Resonancia magnética cardiaca: utilidad de la secuencia de realce tardío 3D (RT-3D) en electrofisiología

“…Los resultados del estudio DANISH 45 hacen cuestionar la eficacia de la implantación de un CDI en pacientes con miocardiopatía dilatada de origen no isquémico, pues en su cohorte no se encontró un cambio significativo en la mortalidad por cualquier causa después de la implantación de un CDI. Estos resultados cuestionan la especificidad de los parámetros (FEVI y clase funcional) de la guías vigentes para definir la implantación de un CDI como prevención primaria en pacientes con falla cardiaca sistólica no isquémica, y además resaltan la importancia de encontrar nuevos marcadores para mejorar la estratificación del riesgo en esta población, incluyendo la detección de la presencia y la extensión (porcentaje) de fibrosis miocárdica por RMC 46 , una mejor definición del riesgo de muerte de origen no cardiaco antes de la implantación del CDI (evaluar la comorbilidad y la expectativa de vida) y una mejor categorización de los pacientes de acuerdo con la etiología de la miocardiopatía dilatada no isquémica, incluyendo pruebas genéticas.…”