Utility of advanced echocardiographic deformation measures to delineate cause of pathological left ventricular hypertrophy: value of a multiparametric approach

Abstract

Background Early diagnosis of cardiac amyloidosis (CA) is warranted to initiate specific treatment and improve outcomes. Conventional echocardiography is unable to reliably differentiate CA from other causes of increased left ventricular (LV) wall thickness.

Purpose To demonstrate the value of a multiparametric approach utilising both standard and advanced echocardiographic measures to distinguish CA from other pathological causes of increased LV wall thickness.

Results Patients with HCM had the highest septal thickness, maximum LV wall thickness, septum/posterior wall (Sep/PW) thickness ratio and left ventricular outflow tract (LVOT) gradient and lowest PW thickness (p<0.0001) among all groups. Patients with CA had the lowest global longitudinal strain (GLS), tissue Doppler-derived myocardial systolic and diastolic velocities and LV ejection fraction (EF) (p<0.0001). EF strain ratio (EFSR=LVEF/GLS) and LV longitudinal strain (apex/base) ratio were highest (largest number) in CA patients (p<0.0001). Multivariate linear regression identified 5 independent predictors (PW thickness, Sep/PW thickness ratio, LVOT gradient, LV longitudinal strain (apex/base) ratio and GLS) that discriminated CA from other causes of increased LV wall thickness. A regression equation (using multivariate linear regression) {CA prediction value = (0.230*LS apex/base) − (0.002*LVOT gradient) − [0.068*(Sep/PW ratio)] + (0.007*PW thickness) + (0.022*GLS) + 0.189; r=0.667)} was derived which allowed reliable distinction of CA with a sensitivity of 92.3% and specificity of 91.2% at the optimal cut-off.

Conclusion PW thickness, Sep/PW thickness ratio, LVOT gradient, LV longitudinal strain (apex/base) ratio and GLS are independent predictors of CA. We developed a multiparametric regression equation which allowed discrimination of CA from other causes of increased LV wall thickness. Future studies involving larger cohorts are required to validate these findings.

Funding Acknowledgement Type of funding sources: None.