Association diastolic function by echo and infarct size by magnetic resonance imaging after STEMI

Sensitivity analysis and inverse uncertainty quantification for the left ventricular passive mechanics

Personalized computational cardiac models are considered to be a unique and powerful tool in modern cardiology, integrating the knowledge of physiology, pathology and fundamental laws of mechanics in one framework. They have the potential to improve risk prediction in cardiac patients and assist in the development of new treatments. However, in order to use these models for clinical decision support, it is important that both the impact of model parameter perturbations on the predicted quantities of interest as well as the uncertainty of parameter estimation are properly quantified, where the first task is a priori in nature (meaning independent of any specific clinical data), while the second task is carried out a posteriori (meaning after specific clinical data have been obtained). The present study addresses these challenges for a widely used constitutive law of passive myocardium (the Holzapfel-Ogden model), using global sensitivity analysis (SA) to address the first challenge, and inverse-uncertainty quantification (I-UQ) for the second challenge. The SA is carried out on a range of different input parameters to a left ventricle (LV) model, making use of computationally efficient Gaussian process (GP) surrogate models in place of the numerical forward simulator. The results of the SA are then used to inform a low-order reparametrization of the constitutive law for passive myocardium under consideration. The quality of this parameterization in the context of an inverse problem having observed noisy experimental data is then quantified with an I-UQ study, which again makes use of GP surrogate models. The I-UQ is carried out in a Bayesian manner using Markov Chain Monte Carlo, which allows for full uncertainty quantification of the material parameter estimates. Our study reveals insights into the relation between SA and I-UQ, elucidates the dependence of parameter sensitivity and estimation uncertainty on external factors, like LV cavity pressure, and sheds new light on cardio-mechanic model formulation, with particular focus on the Holzapfel-Ogden myocardial model.

Prognostic Impact of Hybrid Comprehensive Telerehabilitation Regarding Diastolic Dysfunction in Patients with Heart Failure with Reduced Ejection Fraction—Subanalysis of the TELEREH-HF Randomized Clinical Trial

Aims: The objective of the study was to evaluate the effects of individually prescribed hybrid comprehensive telerehabilitation (HCTR) implemented at patients’ homes on left ventricular (LV) diastolic function in heart failure (HF) patients. Methods and results: The Telerehabilitation in Heart Failure Patients trial (TELEREH-HF) is a multicenter, prospective, randomized (1:1), open-label, parallel-group, controlled trial involving HF patients assigned either to HCTR involving a remotely monitored home training program in conjunction with usual care (HCTR group) or usual care only (UC group). The patient in the HCTR group underwent a 9-week HCTR program consisting of two stages: an initial stage (1 week) conducted in hospital and the subsequent stage (eight weeks) of home-based HCTR five times weekly. Due to difficulties of proper assessment and differences in the evaluation of diastolic function in patients with atrial fibrillation, we included in our subanalysis only patients with sinus rhythm. Depending on the grade of diastolic dysfunction, patients were assigned to subgroups with mild diastolic (MDD) or severe diastolic dysfunction (SDD), both in HCTR (HCTR-MDD and HCTR-SDD) and UC groups (UC-MDD and UC-SDD). Changes from baseline to 9 weeks in echocardiographic parameters were seen only in A velocities in HCTR-MDD vs. UC-MDD; no significant shifts between groups of different diastolic dysfunction grades were observed after HCTR. All-cause mortality was higher in UC-SDD vs. UC-MDD with no difference between HCTR-SDD and HCTR-MDD. Higher probability of HF hospitalization was observed in HCTR-SDD than HCTR-MDD and in UC-SDD than UC-MDD. No differences in the probability of cardiovascular mortality and hospitalization were found. Conclusions: HCTR did not influence diastolic function in HF patients in a significant manner. The grade of diastolic dysfunction had an impact on mortality only in the UC group and HF hospitalization over a 12–24-month follow-up in HCTR and UC groups.

Determinants of Exercise Capacity Following ST-Elevation Myocardial Infarction (STEMI)

BACKGROUND

Abnormal left ventricular systolic and diastolic function and reduced exercise capacity are associated with worse prognosis following ST-elevation myocardial infarction (STEMI). However, evidence is lacking on the determinants of exercise capacity following STEMI. We sought to determine the impact of systolic and diastolic dysfunction on exercise capacity and outcomes following first-ever STEMI.

METHODS

In a retrospective analysis of 139 consecutive STEMI patients who had a transthoracic echocardiogram following STEMI and completed exercise treadmill testing, the primary outcome was to identify clinical and echocardiographic determinants of exercise capacity, and the secondary outcome was to identify determinants of major adverse cardiac events (MACEs).

RESULTS

Mean number of metabolic equivalents (METs > 8) was used as a cut-off. Age, female sex, anterior infarction, abnormal diastolic function, minimum left atrial indexed volume (LAVI_min) ≥ 18 mL/m², average e', and E/e' were associated with METs ≤ 8, but not left ventricular ejection fraction (LVEF). On multivariate analysis, LAVI_min (OR 4.3, 95%CI 1.3-14.2; p = 0.017), anterior infarction (OR 2.6, 95%CI 1.2-5.9; p = 0.022), and abnormal diastolic function (OR 3.73, 95%CI 1.7-8.4; p = 0.001) were independent predictors of METs ≤ 8. On Kaplan-Meier analysis, METs ≤ 8 (p = 0.01) and abnormal diastolic function (p = 0.04) were associated with MACEs (median follow-up 2.3 years). METs ≤ 8 was an independent predictor of MACEs (HR 3.4, 95%CI 1.2-9.8; p = 0.02).

CONCLUSIONS

Following first-ever STEMI, increased LAVI_min, anterior infarction, and abnormal diastolic function were independent predictors of reduced exercise capacity. Furthermore, reduced exercise capacity was an independent predictor of MACEs. These results highlight important prognostic and therapeutic implications related to abnormal diastolic function in STEMI patients that are distinct from those with LV systolic impairment.

Finite-element based optimization of left ventricular passive stiffness in normal volunteers and patients after myocardial infarction: Utility of an inverse deformation gradient calculation of regional diastolic strain

INTRODUCTION

Left ventricular (LV) diastolic dysfunction (DD) is common after myocardial infarction (MI). Whereas current clinical assessment of DD relies on indirect markers including LV filling, finite element (FE) -based computational modeling directly measures regional diastolic stiffness. We hypothesized that an inverse deformation gradient (DG) method calculation of diastolic strain (IDGDS) allows the FE model-based calculation of regional diastolic stiffness (material parameters; MP) in post-MI patients with DD.

METHODS

Cardiac magnetic resonance (CMR) with tags (CSPAMM) and late gadolinium enhancement (LGE) was performed in 10 patients with post-MI DD and 10 healthy volunteers. The 3-dimensional (3D) LV DG from end-diastole (ED) to early diastolic filling (EDF; DG_ED→EDF) was calculated from CSPAMM. Diastolic strain was calculated from DG_EDF→ED by inverting the DG_ED→EDF. FE models were created with MI and non-MI (remote; RM) regions determined by LGE. Guccione MPs C, and exponential fiber, b_f, and transverse, b_t , terms were optimized with IDGDS strain.

RESULTS

3D circumferential and longitudinal diastolic strain (E_cc;E_ll) calculated using IDGDS in CSPAMM obtained in volunteers and MI patients were [Formula: see text]  = 0.27 ± 0.01, [Formula: see text]  = 0.24 ± 0.03 and [Formula: see text]  = 0.21 ± 0.02, and [Formula: see text]  = 0.15 ± 0.02, respectively. MPs in the volunteer group were C_H = 0.013 [0.001, 0.235] kPa, [Formula: see text]  = 20.280 ± 4.994, and [Formula: see text]  = 7.460 ± 2.171 and C_RM = 0.0105 [0.010, 0.011] kPa, [Formula: see text]  = 50.786 ± 13.511 (p = 0.0846), and [Formula: see text]  = 17.355 ± 2.743 (p = 0.0208) in the remote myocardium of post-MI patients.

CONCLUSION

Diastolic strain, calculated from CSPAMM with IDGDS, enables calculation of FE model-based regional diastolic material parameters. Transverse stiffness of the remote myocardium, , may be a valuable new metric for determination of DD in patients after MI.

Determinants of Diastolic Dysfunction Following Myocardial Infarction: Evidence for Causation Beyond Infarct Size

BACKGROUND

The determinants of severe diastolic dysfunction (DD) following myocardial infarction (MI) are not well defined. This study sought to define the determinants of severe DD (restrictive mitral inflow pattern on Doppler echocardiography [RFP]) in patients with a first-ever MI, with particular emphasis on the impact of infarct size.

METHODS

Retrospective single-centre study including consecutive patients admitted to a tertiary referral centre with a first-ever non-ST-elevation-MI (NSTEMI) or ST-elevation-MI (STEMI) (n=477). Peak troponin-I (Peak-TnI) was used as the principal measure of infarct size, whilst left ventricular ejection fraction (LVEF) and wall motion score index (WMSI) were regarded as surrogate measures. Echocardiography was performed within 24 hours of admission for all patients. RFP was defined as E/A ratio >2.0 or E/A ratio >1.5 and E-wave deceleration time <140 ms.

RESULTS

A total of 69 patients (14.5%) had RFP. Peak-TnI levels were higher in the RFP group (32.6±32.7 versus 16.9±25.2 μg/L, p<0.001). In sequential multivariable models incorporating significant clinical, angiographic and left ventricular (LV) size-related variables, Peak-TnI (OR 1.98, p=0.001), WMSI (OR 2.34, p=0.048) and LVEF (OR 0.97, p=0.044) were independent predictors of RFP. Presence of diabetes was also an independent predictor in all the models constructed. When patients were stratified according to an LVEF of 50%, 39% of RFP patients had a preserved LVEF (RFP/preserved EF group), and these patients had lower Peak-TnI levels compared to the RFP/reduced EF group (14.4±18.7 vs 44.5±35.5 μg/L).

CONCLUSIONS

Whilst infarct size is a major determinant of severe diastolic dysfunction after MI, a significant subset of patients develop severe diastolic dysfunction despite a small infarct size and preserved LVEF, highlighting that other factors such as pre-existing diastolic dysfunction due to risk factors such as diabetes have an important role in causation.