Association of left ventricular flow energetics with remodeling after myocardial infarction: New hemodynamic insights for left ventricular remodeling

Left Atrial Strain for Prediction of Left Ventricular Reverse Remodeling After ST-segment Elevation Myocardial Infarction by Cardiac Magnetic Resonance Feature Tracking

PURPOSE

The study aimed to investigate the potential utility of left atrial (LA) strain by using cardiac magnetic resonance feature-tracking (CMR-FT) to predict left ventricular reverse remodeling (LVRR) following ST-segment elevation myocardial infarction (STEMI).

MATERIALS AND METHODS

Patients with a first STEMI treated by primary percutaneous coronary intervention were consecutively enrolled in the prospective study and underwent CMR scans at 5 days and 4 months. LA global longitudinal strain (reservoir strain [εs], conduit strain [εe], booster strain [εa]) and corresponding strain rate were assessed by CMR-FT using cine images. LVRR was defined as a reduction in the LV end-systolic volume index of >10% from baseline to follow-up. Logistic regression analyses were performed to determine the predictors of LVRR.

RESULTS

Of 90 patients analyzed, patients with LVRR (n=35, 39%) showed higher values of LA strain and strain rate and less extensive infarct size (IS) compared with patients without LVRR (n=55, 61%) at initial and second CMR. The LVRR group demonstrated significant improvements in LV and LA cardiac function over time, especially the obvious increase in LA strain and strain rate. In multivariate logistic regression analyses, εs and εe, together with IS, were independent predictors of LVRR. The combination of εs and IS could optimally predict the LVRR with the highest area under the curve of 0.743.

CONCLUSIONS

Post-STEMI patients with LVRR presented better recovery from cardiac function and LA deformation compared with patients without LVRR. Assessment of εs and εe by using CMR-FT after STEMI enabled prediction of LVRR.

Energetics of Cardiac Blood Flow in Hypertrophic Cardiomyopathy through Individualized Computational Modeling

Hypertrophic cardiomyopathy (HCM) is a congenital heart disease characterized by thickening of the heart's left ventricle (LV) wall that can lead to cardiac dysfunction and heart failure. Ventricular wall thickening affects the motion of cardiac walls and blood flow within the heart. Because abnormal cardiac blood flow in turn could lead to detrimental remodeling of heart walls, aberrant ventricular flow patterns could exacerbate HCM progression. How blood flow patterns are affected by hypertrophy and inter-patient variability is not known. To address this gap in knowledge, we present here strategies to generate personalized computational fluid dynamics (CFD) models of the heart LV from patient cardiac magnetic resonance (cMR) images. We performed simulations of CFD LV models from three cases (one normal, two HCM). CFD computations solved for blood flow velocities, from which flow patterns and the energetics of flow within the LV were quantified. We found that, compared to a normal heart, HCM hearts exhibit anomalous flow patterns and a mismatch in the timing of energy transfer from the LV wall to blood flow, as well as changes in kinetic energy flow patterns. While our results are preliminary, our presented methodology holds promise for in-depth analysis of HCM patient hemodynamics in clinical practice.