In silico identification of potential calcium dynamics and sarcomere targets for recovering left ventricular function in rat heart failure with preserved ejection fraction

Acute and chronic effects of levosimendan in the ZSF1 obese rat model of heart failure with preserved ejection fraction

Heart failure with preserved ejection fraction (HFpEF) is a syndrome characterized by impaired cardiovascular reserve in which therapeutic options are scarce. Our aim was to evaluate the inodilator levosimendan in the ZSF1 obese rat model of HFpEF. Twenty-week-old male Wistar-Kyoto (WKY), ZSF1 lean (ZSF1 Ln) and ZSF1 obese rats chronically treated for 6-weeks with either levosimendan (1 mg/kg/day, ZSF1 Ob + Levo) or vehicle (ZSF1 Ob + Veh) underwent peak-effort testing, pressure-volume (PV) haemodynamic evaluation and echocardiography (n = 7 each). Samples were collected for histology and western blotting. In obese rats, skinned and intact left ventricular (LV) cardiomyocytes underwent in vitro functional evaluation. Seven additional ZSF1 obese rats underwent PV evaluation to assess acute levosimendan effects (10 μg/kg + 0.1 μg/kg/min). ZSF1 Ob + Veh presented all hallmarks of HFpEF, namely effort intolerance, elevated end-diastolic pressures and reduced diastolic compliance as well as increased LV mass and left atrial area, cardiomyocyte hypertrophy and increased interstitial fibrosis. Levosimendan decreased systemic arterial pressures, raised cardiac index, and enhanced LV relaxation and diastolic compliance in both acute and chronic experiments. ZSF1 Ob + Levo showed pronounced attenuation of hypertrophy and interstitial fibrosis alongside increased effort tolerance (endured workload raised 38 %) and maximum O2 consumption. Skinned cardiomyocytes from ZSF 1 Ob + Levo showed a downward shift in sarcomere length-passive tension relationship and intact cardiomyocytes showed decreased diastolic Ca2+ levels and enhanced Ca2+ sensitivity. On molecular grounds, levosimendan enhanced phosphorylation of phospholamban and mammalian target of rapamycin. The observed effects encourage future clinical trials with levosimendan in a broad population of HFpEF patients.

Calibration of Cohorts of Virtual Patient Heart Models Using Bayesian History Matching

Previous patient-specific model calibration techniques have treated each patient independently, making the methods expensive for large-scale clinical adoption. In this work, we show how we can reuse simulations to accelerate the patient-specific model calibration pipeline. To represent anatomy, we used a Statistical Shape Model and to represent function, we ran electrophysiological simulations. We study the use of 14 biomarkers to calibrate the model, training one Gaussian Process Emulator (GPE) per biomarker. To fit the models, we followed a Bayesian History Matching (BHM) strategy, wherein each iteration a region of the parameter space is ruled out if the emulation with that set of parameter values produces is "implausible". We found that without running any extra simulations we can find 87.41% of the non-implausible parameter combinations. Moreover, we showed how reducing the uncertainty of the measurements from 10 to 5% can reduce the final parameter space by 6 orders of magnitude. This innovation allows for a model fitting technique, therefore reducing the computational load of future biomedical studies.

New Opportunities in Heart Failure with Preserved Ejection Fraction: From Bench to Bedside… and Back

Heart failure with preserved ejection fraction (HFpEF) is a growing public health problem in nearly 50% of patients with heart failure. Therefore, research on new strategies for its diagnosis and management has become imperative in recent years. Few drugs have successfully improved clinical outcomes in this population. Therefore, numerous attempts are being made to find new pharmacological interventions that target the main mechanisms responsible for this disease. In recent years, pathological mechanisms such as cardiac fibrosis and inflammation, alterations in calcium handling, NO pathway disturbance, and neurohumoral or mechanic impairment have been evaluated as new pharmacological targets showing promising results in preliminary studies. This review aims to analyze the new strategies and mechanical devices, along with their initial results in pre-clinical and different phases of ongoing clinical trials for HFpEF patients. Understanding new mechanisms to generate interventions will allow us to create methods to prevent the adverse outcomes of this silent pandemic.

Quantitative mapping of force-pCa curves to whole heart contraction and relaxation

Abstract

The force–pCa (F–pCa) curve is used to characterize steady‐state contractile properties of cardiac muscle cells in different physiological, pathological and pharmacological conditions. This provides a reduced preparation in which to isolate sarcomere mechanisms. However, it is unclear how changes in the F–pCa curve impact emergent whole‐heart mechanics quantitatively. We study the link between sarcomere and whole‐heart function using a multiscale mathematical model of rat biventricular mechanics that describes sarcomere, tissue, anatomy, preload and afterload properties quantitatively. We first map individual cell‐level changes in sarcomere‐regulating parameters to organ‐level changes in the left ventricular function described by pressure–volume loop characteristics (e.g. end‐diastolic and end‐systolic volumes, ejection fraction and isovolumetric relaxation time). We next map changes in the sarcomere‐regulating parameters to changes in the F–pCa curve. We demonstrate that a change in the F–pCa curve can be caused by multiple different changes in sarcomere properties. We demonstrate that changes in sarcomere properties cause non‐linear and, importantly, non‐monotonic changes in left ventricular function. As a result, a change in sarcomere properties yielding changes in the F–pCa curve that improve contractility does not guarantee an improvement in whole‐heart function. Likewise, a desired change in whole‐heart function (i.e. ejection fraction or relaxation time) is not caused by a unique shift in the F–pCa curve. Changes in the F–pCa curve alone cannot be used to predict the impact of a compound on whole‐heart function.

Key points

The force–pCa (F–pCa) curve is used to assess myofilament calcium sensitivity after pharmacological modulation and to infer pharmacological effects on whole‐heart function.

We demonstrate that there is a non‐unique mapping from changes in F–pCa curves to changes in left ventricular (LV) function.

The effect of changes in F–pCa on LV function depend on the state of the heart and could be different for different pathological conditions.

Screening of compounds to impact whole‐heart function by F–pCa should be combined with active tension and calcium transient measurements to predict better how changes in muscle function will impact whole‐heart physiology.

An Integrated Workflow for Building Digital Twins of Cardiac Electromechanics-A Multi-Fidelity Approach for Personalising Active Mechanics

Personalised computer models of cardiac function, referred to as cardiac digital twins, are envisioned to play an important role in clinical precision therapies of cardiovascular diseases. A major obstacle hampering clinical translation involves the significant computational costs involved in the personalisation of biophysically detailed mechanistic models that require the identification of high-dimensional parameter vectors. An important aspect to identify in electromechanics (EM) models are active mechanics parameters that govern cardiac contraction and relaxation. In this study, we present a novel, fully automated, and efficient approach for personalising biophysically detailed active mechanics models using a two-step multi-fidelity solution. In the first step, active mechanical behaviour in a given 3D EM model is represented by a purely phenomenological, low-fidelity model, which is personalised at the organ scale by calibration to clinical cavity pressure data. Then, in the second step, median traces of nodal cellular active stress, intracellular calcium concentration, and fibre stretch are generated and utilised to personalise the desired high-fidelity model at the cellular scale using a 0D model of cardiac EM. Our novel approach was tested on a cohort of seven human left ventricular (LV) EM models, created from patients treated for aortic coarctation (CoA). Goodness of fit, computational cost, and robustness of the algorithm against uncertainty in the clinical data and variations of initial guesses were evaluated. We demonstrate that our multi-fidelity approach facilitates the personalisation of a biophysically detailed active stress model within only a few (2 to 4) expensive 3D organ-scale simulations-a computational effort compatible with clinical model applications.