Preconditioning with selective autoretroperfusion: In vivo and in silico evidence of washout hypothesis.

Introduction: Prompt reperfusion of coronary artery after acute myocardial infarction (AMI) is crucial for minimizing heart injury. The myocardium, however, may experience additional injury due to the flow restoration itself (reperfusion injury, RI). The purpose of this study was to demonstrate that short preconditioning (10 min) with selective autoretroperfusion (SARP) ameliorates RI, based on a washout hypothesis. Methods: AMI was induced in 23 pigs (3 groups) by occluding the left anterior descending (LAD) artery. In SARP-b (SARP balloon inflated) and SARP-nb (SARP balloon deflated) groups, arterial blood was retroperfused for 10 min via the great cardiac vein before releasing the arterial occlusion. A mathematical model of coronary circulation was used to simulate the SARP process and evaluate the potential washout effect. Results: SARP restored left ventricular function during LAD occlusion. Ejection fraction in the SARP-b group returned to baseline levels, compared to SARP-nb and control groups. Infarct area was significantly larger in the control group than in the SARP-b and SARP-nb groups. End-systolic wall thickness was preserved in the SARP-b compared to the SARP-nb and control groups. Analyte values (pH, lactate, glucose, and others), measured every 2 min during retroperfusion, suggest a "washout" effect as one important mechanism of action of SARP in reducing infarct size. With SARP, the values progressively approached baseline levels. The mathematical model also confirmed a possible washout effect of tracers. Discussion: RI can be ameliorated by delaying restoration of arterial flow for a brief period of time while pretreating the infarction with SARP to restore homeostasis via a washout mechanism.

Multiscale Finite Element Modeling of Left Ventricular Growth in Simulations of Valve Disease.

Multiscale models of the cardiovascular system are emerging as effective tools for investigating the mechanisms that drive ventricular growth and remodeling. These models can predict how molecular-level mechanisms impact organ-level structure and function and could provide new insights that help improve patient care. MyoFE is a multiscale computer framework that bridges molecular and organ-level mechanisms in a finite element model of the left ventricle that is coupled with the systemic circulation. In this study, we extend MyoFE to include a growth algorithm, based on volumetric growth theory, to simulate concentric growth (wall thickening/thinning) and eccentric growth (chamber dilation/constriction) in response to valvular diseases. Specifically in our model, concentric growth is controlled by time-averaged total stress along the fiber direction over a cardiac cycle while eccentric growth responds to time-averaged intracellular myofiber passive stress over a cardiac cycle. The new framework correctly predicted different forms of growth in response to two types of valvular diseases, namely aortic stenosis and mitral regurgitation. Furthermore, the model predicted that LV size and function are nearly restored (reversal of growth) when the disease-mimicking perturbation was removed in the simulations for each valvular disorder. In conclusion, the simulations suggest that time-averaged total stress along the fiber direction and time-averaged intracellular myofiber passive stress can be used to drive concentric and eccentric growth in simulations of valve disease.

Mechanisms of coronary sinus reducer for treatment of myocardial ischemia: in silico study.

The coronary sinus reducer (CSR) is an emerging medical device for treating patients with refractory angina, often associated with myocardial ischemia. Patients implanted with CSR have shown positive outcomes, but the underlying mechanisms are unclear. This study sought to understand the mechanisms of CSR by investigating its effects on coronary microcirculation hemodynamics that may help explain the therapy's efficacy. We applied a validated computer model of the coronary microcirculation to investigate how CSR affects hemodynamics under different degrees of coronary artery stenosis. With moderate coronary stenosis, an increase in capillary transit time (CTT) [up to 69% with near-complete coronary sinus (CS) occlusion] is the key change associated with CSR. Because capillaries in the microcirculation can still receive oxygenated blood from the upstream artery with moderate stenosis, the increase in CTT allows more time for the exchange of gases and nutrients, aiding tissue oxygenation. With severe coronary stenosis; however, the redistribution of blood draining from the nonischemic region to the ischemic region (up to 96% with near-complete CS occlusion) and the reduction in capillary flow heterogeneity are the key changes associated with CSR. Because blood draining from the nonischemic region is not completely devoid of O2, the redistribution of blood to the capillaries in the ischemic region by CSR is beneficial especially when little or no oxygenated blood reaches these capillaries. This simulation study provides insights into the mechanisms of CSR in improving clinical symptoms. The mechanisms differ with the severity of the upstream stenosis.NEW & NOTEWORTHY Emerging coronary venous retroperfusion treatments, particularly coronary sinus reducer (CSR) for refractory angina linked to myocardial ischemia, show promise; however, their mechanisms of action are not well understood. We find that CSR's effectiveness varies with the severity of coronary stenosis. In moderate stenosis, CSR improves tissue oxygenation by increasing capillary transit time, whereas in severe stenosis, it redistributes blood from nonischemic to ischemic regions and reduces capillary flow heterogeneity.

Review of cardiac-coronary interaction and insights from mathematical modeling.

Cardiac-coronary interaction is fundamental to the function of the heart. As one of the highest metabolic organs in the body, the cardiac oxygen demand is met by blood perfusion through the coronary vasculature. The coronary vasculature is largely embedded within the myocardial tissue which is continually contracting and hence squeezing the blood vessels. The myocardium-coronary vessel interaction is two-ways and complex. Here, we review the different types of cardiac-coronary interactions with a focus on insights gained from mathematical models. Specifically, we will consider the following: (1) myocardial-vessel mechanical interaction; (2) metabolic-flow interaction and regulation; (3) perfusion-contraction matching, and (4) chronic interactions between the myocardium and coronary vasculature. We also provide a discussion of the relevant experimental and clinical studies of different types of cardiac-coronary interactions. Finally, we highlight knowledge gaps, key challenges, and limitations of existing mathematical models along with future research directions to understand the unique myocardium-coronary coupling in the heart. This article is categorized under: Cardiovascular Diseases > Computational Models Cardiovascular Diseases > Biomedical Engineering Cardiovascular Diseases > Molecular and Cellular Physiology.

A multiscale finite element model of left ventricular mechanics incorporating baroreflex regulation.

Cardiovascular function is regulated by a short-term hemodynamic baroreflex loop, which tries to maintain arterial pressure at a normal level. In this study, we present a new multiscale model of the cardiovascular system named MyoFE. This framework integrates a mechanistic model of contraction at the myosin level into a finite-element-based model of the left ventricle pumping blood through the systemic circulation. The model is coupled with a closed-loop feedback control of arterial pressure inspired by a baroreflex algorithm previously published by our team. The reflex loop mimics the afferent neuron pathway via a normalized signal derived from arterial pressure. The efferent pathway is represented by a kinetic model that simulates the net result of neural processing in the medulla and cell-level responses to autonomic drive. The baroreflex control algorithm modulates parameters such as heart rate and vascular tone of vessels in the lumped-parameter model of systemic circulation. In addition, it spatially modulates intracellular Ca2+ dynamics and molecular-level function of both the thick and the thin myofilaments in the left ventricle. Our study demonstrates that the baroreflex algorithm can maintain arterial pressure in the presence of perturbations such as acute cases of altered aortic resistance, mitral regurgitation, and myocardial infarction. The capabilities of this new multiscale model will be utilized in future research related to computational investigations of growth and remodeling.

Simulation of coronary capillary transit time based on full vascular model of the heart.

Capillary transit time (CTT) is a fundamental determinant of gas exchange between blood and tissues in the heart and other organs. Despite advances in experimental techniques, it remains difficult to measure coronary CTT in vivo. Here, we developed a novel computational framework that couples coronary microcirculation with cardiac mechanics in a closed-loop system that enables prediction of hemodynamics in the entire coronary network, including arteries, veins, and capillaries. We also developed a novel "particle-tracking" approach for computing CTT where "virtual tracers" are individually tracked as they traverse the capillary network. Model predictions compare well with blood pressure and flow rate distributions in the arterial network reported in previous studies. Model predictions of transit times in the capillaries (1.21 ± 1.5 s) and entire coronary network (11.8 ± 1.8 s) also agree with measurements. We show that, with increasing coronary artery stenosis (as quantified by fractional flow reserve, FFR), intravascular pressure and flow rate downstream are reduced but remain non-stationary even at 100 % stenosis because some flow (∼3 %) is redistributed from the non-occluded to the occluded territories. Importantly, the model predicts that occlusion of a large artery results in higher CTT. For moderate stenosis (FFR > 0.6), the increase in CTT (from 1.21 s without stenosis to 2.23 s at FFR=0.6) is caused by a decrease in capillary flow rate. In severe stenosis (FFR = 0.1), the increase in CTT to 14.2 s is due to both a decrease in flow rate and an increase in path length taken by "virtual tracers" in the capillary network.

An in silico study of the effects of left ventricular assist device on right ventricular function and inter-ventricular interaction.

BACKGROUND: Left ventricular assist device (LVAD) is associated with a high incidence of right ventricular (RV) failure, which is hypothesized to be caused by the occurring inter-ventricular interactions when the LV is unloaded. Factors contributing to these interactions are unknown. METHODS: We used computer modeling to investigate the impact of the HeartMate 3 LVAD on RV functions. The model was first calibrated against pressure-volume (PV) loops associated with a heart failure (HF) patient and validated against measurements of inter-ventricular interactions in animal experiments. The model was then applied to investigate the effects of LVAD on (1) RV chamber contractility indexed by V 60 derived from its end-systolic PV relationship, and (2) RV diastolic function indexed by V 20 derived from its end-diastolic PV relationship. We also investigated how septal wall thickness and regional contractility affect the impact of LVAD on RV function. RESULTS: The impact of LVAD on RV chamber contractility is small at a pump speed lower than 4k rpm. At a higher pump speed between 4k and 9k rpm, however, RV chamber contractility is reduced (by ~3% at 6k rpm and ~10% at 9k rpm). The reduction of RV chamber contractility is greater with a thinner septal wall or with a lower myocardial contractility at the LV free wall, septum, or RV free wall. CONCLUSION: RV chamber contractility is reduced at a pump speed higher than 4k rpm, and this reduction is greater with a thinner septal wall or lower regional myocardial contractility. Findings here may have clinical implications in identifying LVAD patients who may suffer from RV failure.

Coupled thermal-hemodynamics computational modeling of cryoballoon ablation for pulmonary vein isolation.

Cryoballoon ablation (CBA) is a cryo-energy based minimally invasive treatment procedure for patients suffering from left atrial (LA) fibrillation. Although this technique has proved to be effective, it is prone to reoccurrences and some serious thermal complications. Also, the factors affecting thermal distribution at the pulmonary vein-antrum junction that are critical to the treatment success is poorly understood. Computer modeling of CBA can resolve this issue and help understand the factors affecting this treatment. To do so, however, numerical challenges associated with the simulation of advection-dominant transport process must be resolved. Here, we describe the development of a thermal-hemodynamics computational framework to simulate incomplete occlusion in a patient-specific LA geometry during CBA. The modeling framework uses the finite element method to predict hemodynamics, thermal distribution, and lesion formation during CBA. An incremental pressure correction scheme is used to decouple velocity and pressure in the Navier-Stokes equation, whereas several stabilization techniques are also applied to overcome numerical instabilities. The framework was implemented using an open-source FE library (FEniCS). We show that model predictions of the hemodynamics in a realistic human LA geometry match well with measurements. The effects of cryoballoon position, pulmonary vein blood velocity and mitral regurgitation on lesion formation during CBA was investigated. For a -700C cryoballoon temperature, the model predicts lesion formation for gaps less than 2.5 mm and increasing efficiency of CBA for higher balloon tissue contact areas. The simulations also predict that lesion formation is not sensitive to variation in pulmonary vein blood velocity and mitral regurgitation. The framework can be applied to optimize CBA in patients for future clinical studies.

Computational analysis of ventricular mechanics in hypertrophic cardiomyopathy patients.

Hypertrophic cardiomyopathy (HCM) is a genetic heart disease that is associated with many pathological features, such as a reduction in global longitudinal strain (GLS), myofiber disarray and hypertrophy. The effects of these features on left ventricle (LV) function are, however, not clear in two phenotypes of HCM, namely, obstructive and non-obstructive. To address this issue, we developed patient-specific computational models of the LV using clinical measurements from 2 female HCM patients and a control subject. Left ventricular mechanics was described using an active stress formulation and myofiber disarray was described using a structural tensor in the constitutive models. Unloaded LV configuration for each subject was first determined from their respective end-diastole LV geometries segmented from the cardiac magnetic resonance images, and an empirical single-beat estimation of the end-diastolic pressure volume relationship. The LV was then connected to a closed-loop circulatory model and calibrated using the clinically measured LV pressure and volume waveforms, peak GLS and blood pressure. Without consideration of myofiber disarray, peak myofiber tension was found to be lowest in the obstructive HCM subject (60 kPa), followed by the non-obstructive subject (242 kPa) and the control subject (375 kPa). With increasing myofiber disarray, we found that peak tension has to increase in the HCM models to match the clinical measurements. In the obstructive HCM patient, however, peak tension was still depressed (cf. normal subject) at the largest degree of myofiber disarray found in the clinic. The computational modeling workflow proposed here can be used in future studies with more HCM patient data.

The dependency of fetal left ventricular biomechanics function on myocardium helix angle configuration.

The helix angle configuration of the myocardium is understood to contribute to the heart function, as finite element (FE) modeling of postnatal hearts showed that altered configurations affected cardiac function and biomechanics. However, similar investigations have not been done on the fetal heart. To address this, we performed image-based FE simulations of fetal left ventricles (LV) over a range of helix angle configurations, assuming a linear variation of helix angles from epicardium to endocardium. Results showed that helix angles have substantial influence on peak myofiber stress, cardiac stroke work, myocardial deformational burden, and spatial variability of myocardial strain. A good match between LV myocardial strains from FE simulations to those measured from 4D fetal echo images could only be obtained if the transmural variation of helix angle was generally between 110 and 130°, suggesting that this was the physiological range. Experimentally discovered helix angle configurations from the literature were found to produce high peak myofiber stress, high cardiac stroke work, and a low myocardial deformational burden, but did not coincide with configurations that would optimize these characteristics. This may suggest that the fetal development of myocyte orientations depends concurrently on several factors rather than a single factor. We further found that the shape, rather than the size of the LV, determined the manner at which helix angles influenced these characteristics, as this influence changed significantly when the LV shape was varied, but not when a heart was scaled from fetal to adult size while retaining the same shape. This may suggest that biomechanical optimality would be affected during diseases that altered the geometric shape of the LV.

Computational modelling of multi-temporal ventricular-vascular interactions during the progression of pulmonary arterial hypertension.

A computational framework is developed to consider the concurrent growth and remodelling (G&R) processes occurring in the large pulmonary artery (PA) and right ventricle (RV), as well as ventricular-vascular interactions during the progression of pulmonary arterial hypertension (PAH). This computational framework couples the RV and the proximal PA in a closed-loop circulatory system that operates in a short timescale of a cardiac cycle, and evolves over a long timescale due to G&R processes in the PA and RV. The framework predicts changes in haemodynamics (e.g. 68.2% increase in mean PA pressure), RV geometry (e.g. 38% increase in RV end-diastolic volume) and PA tissue microstructure (e.g. 90% increase in collagen mass) that are consistent with clinical and experimental measurements of PAH. The framework also predicts that a reduction in RV contractility is associated with long-term RV chamber dilation, a common biomarker observed in the late-stage PAH. Sensitivity analyses on the G&R rate constants show that large PA stiffening (both short and long term) is affected by RV remodelling more than the reverse. This framework can serve as a foundation for the future development of a more predictive and comprehensive cardiovascular G&R model with realistic heart and vascular geometries.

Mechanism of exercise intolerance in heart diseases predicted by a computer model of myocardial demand-supply feedback system.

BACKGROUND AND OBJECTIVE: The myocardial demand-supply feedback system plays an important role in augmenting blood supply in response to exercise-induced increased myocardial demand. During this feedback process, the myocardium and coronary blood flow interact bidirectionally at many different levels. METHODS: To investigate these interactions, a novel computational framework that considers the closed myocardial demand-supply feedback system was developed. In the framework coupling the systemic circulation of the left ventricle and coronary perfusion with regulation, myocardial work affects coronary perfusion via flow regulation mechanisms (e.g., metabolic regulation) and myocardial-vessel interactions, whereas coronary perfusion affects myocardial contractility in a closed feedback system. The framework was calibrated based on the measurements from healthy subjects under graded exercise conditions, and then was applied to simulate the effects of graded exercise on myocardial demand-supply under different physiological and pathological conditions. RESULTS: We found that the framework can recapitulate key features found during exercise in clinical and animal studies. We showed that myocardial blood flow is increased but maximum hyperemia is reduced during exercise, which led to a reduction in coronary flow reserve. For coronary stenosis and myocardial inefficiency, the model predicts that an increase in heart rate is necessary to maintain the baseline cardiac output. Correspondingly, the resting coronary flow reserve is exhausted and the range of heart rate before exhaustion of coronary flow reserve is reduced. In the presence of metabolic regulation dysfunction, the model predicts that the metabolic vasodilator signal is higher at rest, saturates faster during exercise, and as a result, causes quicker exhaustion of coronary flow reserve. CONCLUSIONS: Model predictions showed that the coronary flow reserve deteriorates faster during graded exercise, which in turn, suggests a decrease in exercise tolerance for patients with stenosis, myocardial inefficiency and metabolic flow regulation dysfunction. The findings in this study may have clinical implications in diagnosing cardiovascular diseases.

Morphological, functional, and biomechanical progression of LV remodelling in a porcine model of HFpEF.

Heart failure (HF) with preserved ejection fraction (HFpEF) accounts for about half of heart failure cases, but the progression of cardiac biomechanics during pathogenesis is not completely understood. We investigated a published porcine model of HFpEF, generated by progressive constriction of an aortic cuff causing progressive left ventricle (LV) pressure overload, and characterized by hypertrophy, diastolic dysfunction and overt HF with elevated plasma beta natriuretic peptide (BNP). We characterized morphological and functional features and performed image-based finite element modelling over multiple time points, so as to understand how biomechanics evolved with morphological and functional changes during pathogenesis, and to provide data for future growth and remodeling investigations. Results showed that the hypertrophic responses quickly manifested and were effective at preventing an elevation of systolic myocardial stresses, suggesting active compensated remodeling. Consequent to the hypertrophy, diastolic myocardial stresses decreased despite the elevations in diastolic pressures. The left ventricle hypertrophy (LVH) myocardium also exhibited a quick elevation of active tension at the onset of the disease. There was a progressive and significant decrease in myocardial strain, which was more significant in the longitudinal direction. Further, elevated myocardial stiffness and diastolic pressures, which reflected diastolic dysfunction, also manifested, but this was delayed from the onset of the disease. Correlation analysis showed that hypertrophy was closely correlated to systolic pressure, active tension and systolic myocardial stress, suggesting that these factors may play a role in initiating hypertrophy. Myocardial stiffness was weakly correlated to LV pressures and myocardial stresses.

Data-driven computational models of ventricular-arterial hemodynamics in pediatric pulmonary arterial hypertension.

Pulmonary arterial hypertension (PAH) is a complex disease involving increased resistance in the pulmonary arteries and subsequent right ventricular (RV) remodeling. Ventricular-arterial interactions are fundamental to PAH pathophysiology but are rarely captured in computational models. It is important to identify metrics that capture and quantify these interactions to inform our understanding of this disease as well as potentially facilitate patient stratification. Towards this end, we developed and calibrated two multi-scale high-resolution closed-loop computational models using open-source software: a high-resolution arterial model implemented using CRIMSON, and a high-resolution ventricular model implemented using FEniCS. Models were constructed with clinical data including non-invasive imaging and invasive hemodynamic measurements from a cohort of pediatric PAH patients. A contribution of this work is the discussion of inconsistencies in anatomical and hemodynamic data routinely acquired in PAH patients. We proposed and implemented strategies to mitigate these inconsistencies, and subsequently use this data to inform and calibrate computational models of the ventricles and large arteries. Computational models based on adjusted clinical data were calibrated until the simulated results for the high-resolution arterial models matched within 10% of adjusted data consisting of pressure and flow, whereas the high-resolution ventricular models were calibrated until simulation results matched adjusted data of volume and pressure waveforms within 10%. A statistical analysis was performed to correlate numerous data-derived and model-derived metrics with clinically assessed disease severity. Several model-derived metrics were strongly correlated with clinically assessed disease severity, suggesting that computational models may aid in assessing PAH severity.

Optimization of cardiac resynchronization therapy based on a cardiac electromechanics-perfusion computational model.

Cardiac resynchronization therapy (CRT) is an established treatment for left bundle branch block (LBBB) resulting in mechanical dyssynchrony. Approximately 1/3 of patients with CRT, however, are non-responders. To understand factors affecting CRT response, an electromechanics-perfusion computational model based on animal-specific left ventricular (LV) geometry and coronary vascular networks located in the septum and LV free wall is developed. The model considers contractility-flow and preload-activation time relationships, and is calibrated to simultaneously match the experimental measurements in terms of the LV pressure, volume waveforms and total coronary flow in the left anterior descending and left circumflex territories from 2 swine models under right atrium and right ventricular pacing. The model is then applied to investigate the responses of CRT indexed by peak LV pressure and (dP/dt)max at multiple pacing sites with different degrees of perfusion in the LV free wall. Without the presence of ischemia, the model predicts that basal-lateral endocardial region is the optimal pacing site that can best improve (dP/dt)max by 20%, and is associated with the shortest activation time. In the presence of ischemia, a non-ischemic region becomes the optimal pacing site when coronary flow in the ischemic region fell below 30% of its original value. Pacing at the ischemic region produces little response at that perfusion level. The optimal pacing site is associated with one that optimizes the LV activation time. These findings suggest that CRT response is affected by both pacing site and coronary perfusion, which may have clinical implication in improving CRT responder rates.

Transmural Distribution of Coronary Perfusion and Myocardial Work Density Due to Alterations in Ventricular Loading, Geometry and Contractility.

Myocardial supply changes to accommodate the variation of myocardial demand across the heart wall to maintain normal cardiac function. A computational framework that couples the systemic circulation of a left ventricular (LV) finite element model and coronary perfusion in a closed loop is developed to investigate the transmural distribution of the myocardial demand (work density) and supply (perfusion) ratio. Calibrated and validated against measurements of LV mechanics and coronary perfusion, the model is applied to investigate changes in the transmural distribution of passive coronary perfusion, myocardial work density, and their ratio in response to changes in LV contractility, preload, afterload, wall thickness, and cavity volume. The model predicts the following: (1) Total passive coronary flow varies from a minimum value at the endocardium to a maximum value at the epicardium transmurally that is consistent with the transmural distribution of IMP; (2) Total passive coronary flow at different transmural locations is increased with an increase in either contractility, afterload, or preload of the LV, whereas is reduced with an increase in wall thickness or cavity volume; (3) Myocardial work density at different transmural locations is increased transmurally with an increase in either contractility, afterload, preload or cavity volume of the LV, but is reduced with an increase in wall thickness; (4) Myocardial work density-perfusion mismatch ratio at different transmural locations is increased with an increase in contractility, preload, wall thickness or cavity volume of the LV, and the ratio is higher at the endocardium than the epicardium. These results suggest that an increase in either contractility, preload, wall thickness, or cavity volume of the LV can increase the vulnerability of the subendocardial region to ischemia.

Multiscale simulations of left ventricular growth and remodeling.

Cardiomyocytes can adapt their size, shape, and orientation in response to altered biomechanical or biochemical stimuli. The process by which the heart undergoes structural changes-affecting both geometry and material properties-in response to altered ventricular loading, altered hormonal levels, or mutant sarcomeric proteins is broadly known as cardiac growth and remodeling (G&R). Although it is likely that cardiac G&R initially occurs as an adaptive response of the heart to the underlying stimuli, prolonged pathological changes can lead to increased risk of atrial fibrillation, heart failure, and sudden death. During the past few decades, computational models have been extensively used to investigate the mechanisms of cardiac G&R, as a complement to experimental measurements. These models have provided an opportunity to quantitatively study the relationships between the underlying stimuli (primarily mechanical) and the adverse outcomes of cardiac G&R, i.e., alterations in ventricular size and function. State-of-the-art computational models have shown promise in predicting the progression of cardiac G&R. However, there are still limitations that need to be addressed in future works to advance the field. In this review, we first outline the current state of computational models of cardiac growth and myofiber remodeling. Then, we discuss the potential limitations of current models of cardiac G&R that need to be addressed before they can be utilized in clinical care. Finally, we briefly discuss the next feasible steps and future directions that could advance the field of cardiac G&R.

Inverse modeling framework for characterizing patient-specific microstructural changes in the pulmonary arteries.

Microstructural changes in the pulmonary arteries associated with pulmonary arterial hypertension (PAH) is not well understood and characterized in humans. To address this issue, we developed and applied a patient-specific inverse finite element (FE) modeling framework to characterize mechanical and structural changes of the micro-constituents in the proximal pulmonary arteries using in-vivo pressure measurements and magnetic resonance images. The framework was applied using data acquired from a pediatric PAH patient and a heart transplant patient with normal pulmonary arterial pressure, which serves as control. Parameters of a constrained mixture model that are associated with the structure and mechanical properties of elastin, collagen fibers and smooth muscle cells were optimized to fit the patient-specific pressure-diameter responses of the main pulmonary artery. Based on the optimized parameters, individual stress and linearized stiffness resultants of the three tissue constituents, as well as their aggregated values, were estimated in the pulmonary artery. Aggregated stress resultant and stiffness are, respectively, 4.6 and 3.4 times higher in the PAH patient than the control subject. Stress and stiffness resultants of each tissue constituent are also higher in the PAH patient. Specifically, the mean stress resultant is highest in elastin (PAH: 69.96, control: 14.42 kPa-mm), followed by those in smooth muscle cell (PAH: 13.95, control: 4.016 kPa-mm) and collagen fibers (PAH: 13.19, control: 2.908 kPa-mm) in both the PAH patient and the control subject. This result implies that elastin may be the key load-bearing constituent in the pulmonary arteries of the PAH patient and the control subject.

Computational Modeling Studies of the Roles of Left Ventricular Geometry, Afterload, and Muscle Contractility on Myocardial Strains in Heart Failure with Preserved Ejection Fraction.

Global longitudinal strain and circumferential strain are found to be reduced in HFpEF, which some have interpreted that the global left ventricular (LV) contractility is impaired. This finding is, however, contradicted by a preserved ejection fraction (EF) and confounded by changes in LV geometry and afterload resistance that may also affect the global strains. To reconcile these issues, we used a validated computational framework consisting of a finite element LV model to isolate the effects of HFpEF features in affecting systolic function metrics. Simulations were performed to quantify the effects on myocardial strains due to changes in LV geometry, active tension developed by the tissue, and afterload. We found that only a reduction in myocardial contractility and an increase in afterload can simultaneously reproduce the blood pressures, EF and strains measured in HFpEF patients. This finding suggests that it is likely that the myocardial contractility is reduced in HFpEF patients. Graphical abstract.