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 O
, 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.
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.
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.
•A novel electromechanics-perfusion computational model based on animal-specific geometry and measurements is developed.•The relationship between contractility and myocardial perfusion is considered.•The calibrated model is applied to optimize cardiac resynchronization therapy (CRT) response.•The effects of pacing site and degree of coronary perfusion on CRT response are investigated.
Predictive computational modeling has revolutionized classical engineering disciplines and is in the process of transforming cardiovascular research. This is particularly relevant for investigating ...emergent therapies for heart failure, which remains a leading cause of death globally. The creation of subject-specific biventricular computational cardiac models has been a long-term endeavor within the biomedical engineering community. Using high resolution (0.3 × 0.3 × 0.8 mm)
data, we constructed a precise fully subject-specific biventricular finite-element model of healthy and failing swine hearts. Each model includes fully subject-specific geometries, myofiber architecture and, in the case of the failing heart, fibrotic tissue distribution. Passive and active material properties are prescribed using hyperelastic strain energy functions that define a nearly incompressible, orthotropic material capable of contractile function. These materials were calibrated using a sophisticated multistep approach to match orthotropic tri-axial shear data as well as subject-specific hemodynamic ventricular targets for pressure and volume to ensure realistic cardiac function. Each mechanically beating heart is coupled with a lumped-parameter representation of the circulatory system, allowing for a closed-loop definition of cardiovascular flow. The circulatory model incorporates unidirectional fluid exchanges driven by pressure gradients of the model, which in turn are driven by the mechanically beating heart. This creates a computationally meaningful representation of the dynamic beating of the heart coupled with the circulatory system. Each model was calibrated using subject-specific experimental data and compared with independent
strain data obtained from echocardiography. Our methods produced highly detailed representations of swine hearts that function mechanically in a remarkably similar manner to the
subject-specific strains on a global and regional comparison. The degree of subject-specificity included in the models represents a milestone for modeling efforts that captures realism of the whole heart. This study establishes a foundation for future computational studies that can apply these validated methods to advance cardiac mechanics research.
•A novel model couples full coronary network with cardiac mechanics in a closed loop.•A novel particle-tracking approach computes myocardial and capillary transit time.•Simulations show capillary ...transit time increases with occlusion/stenosis severity.•Model predicts blood flow redistribution from non-occluded to occluded regions.
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.
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:
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;
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;
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;
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.
•A novel computational model that considers the myocardial demand-supply closed-loop feedback system is developed to study mechanism of exercise intolerance in heart diseases.•Myocardial work affects ...coronary perfusion via flow regulation and myocardial-vessel interactions, whereas coronary perfusion affects myocardial contractility.•Coronary flow reserve for patients deteriorates faster during graded exercise, suggesting a decrease in exercise tolerance for patients with cardiovascular diseases.•Findings in this study have clinical implications in diagnosing cardiovascular diseases.
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.
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.
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.
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.
Mechanical dyssynchrony (MD) affects left ventricular (LV) mechanics and coronary perfusion. To understand the multifactorial effects of MD, we developed a computational model that bidirectionally ...couples the systemic circulation with the LV and coronary perfusion with flow regulation. In the model, coronary flow in the left anterior descending (LAD) and left circumflex (LCX) arteries affects the corresponding regional contractility based on a prescribed linear LV contractility-coronary flow relationship. The model is calibrated with experimental measurements of LV pressure and volume, as well as LAD and LCX flow rate waveforms acquired under regulated and fully dilated conditions from a swine under right atrial (RA) pacing. The calibrated model is applied to simulate MD. The model can simultaneously reproduce the reduction in mean LV pressure (39.3%), regulated flow (LAD: 7.9%; LCX: 1.9%), LAD passive flow (21.6%), and increase in LCX passive flow (15.9%). These changes are associated with right ventricular pacing compared with RA pacing measured in the same swine only when LV contractility is affected by flow alterations with a slope of 1.4 mmHg/mL
in a contractility-flow relationship. In sensitivity analyses, the model predicts that coronary flow reserve (CFR) decreases and increases in the LAD and LCX with increasing delay in LV free wall contraction. These findings suggest that asynchronous activation associated with MD impacts
) the loading conditions that further affect the coronary flow, which may explain some of the changes in CFR, and
) the coronary flow that reduces global contractility, which contributes to the reduction in LV pressure.
A computational model that couples the systemic circulation of the left ventricular (LV) and coronary perfusion with flow regulation is developed to study the effects of mechanical dyssynchrony. The delayed contraction in the LV free wall with respect to the septum has a significant effect on LV function and coronary flow reserve.
Mechanical dyssynchrony affects left ventricular (LV) mechanics and coronary perfusion. Due to the confounding effects of their bi-directional interactions, the mechanisms behind these changes are ...difficult to isolate from experimental and clinical studies alone. Here, we develop and calibrate a closed-loop computational model that couples the systemic circulation, LV mechanics, and coronary perfusion. The model is applied to simulate the impact of mechanical dyssynchrony on coronary flow in the left anterior descending artery (LAD) and left circumflex artery (LCX) territories caused by regional alterations in perfusion pressure and intramyocardial pressure (
IMP
). We also investigate the effects of regional coronary flow alterations on regional LV contractility in mechanical dyssynchrony based on prescribed contractility-flow relationships without considering autoregulation. The model predicts that LCX and LAD flows are reduced by 7.2%, and increased by 17.1%, respectively, in mechanical dyssynchrony with a systolic dyssynchrony index of 10% when the LAD's
IMP
is synchronous with the arterial pressure. The LAD flow is reduced by 11.6% only when its
IMP
is delayed with respect to the arterial pressure by 0.07 s. When contractility is sensitive to coronary flow, mechanical dyssynchrony can affect global LV mechanics,
IMP
s and contractility that in turn, further affect the coronary flow in a feedback loop that results in a substantial reduction of
dP
LV
/
dt
, indicative of ischemia. Taken together, these findings imply that regional
IMP
s play a significant role in affecting regional coronary flows in mechanical dyssynchrony and the changes in regional coronary flow may produce ischemia when contractility is sensitive to the changes in coronary flow.
An understanding of left ventricle (LV) mechanics is fundamental for designing better preventive, diagnostic, and treatment strategies for improved heart function. Because of the costs of clinical ...and experimental studies to treat and understand heart function, respectively, in-silico models play an important role. Finite element (FE) models, which have been used to create in-silico LV models for different cardiac health and disease conditions, as well as cardiac device design, are time-consuming and require powerful computational resources, which limits their use when real-time results are needed. As an alternative, we sought to use deep learning (DL) for LV in-silico modeling. We used 80 four-chamber heart FE models for feed forward, as well as recurrent neural network (RNN) with long short-term memory (LSTM) models for LV pressure and volume. We used 120 LV-only FE models for training LV stress predictions. The active material properties of the myocardium and time were features for the LV pressure and volume training, and passive material properties and element centroid coordinates were features of the LV stress prediction models. For six test FE models, the DL error for LV volume was 1.599 ± 1.227 ml, and the error for pressure was 1.257 ± 0.488 mmHg; for 20 LV FE test examples, the mean absolute errors were, respectively, 0.179 ± 0.050 for myofiber, 0.049 ± 0.017 for cross-fiber, and 0.039 ± 0.011 kPa for shear stress. After training, the DL runtime was in the order of seconds whereas equivalent FE runtime was in the order of several hours (pressure and volume) or 20 min (stress). We conclude that using DL, LV in-silico simulations can be provided for applications requiring real-time results.
Despite positive initial outcomes emerging from preclinical and early clinical investigation of alginate hydrogel injection therapy as a treatment for heart failure, the lack of knowledge about the ...mechanism of action remains a major shortcoming that limits the efficacy of treatment design. To identify the mechanism of action, we examined previously unobtainable measurements of cardiac function from in vivo, ex vivo, and in silico states of clinically relevant heart failure (HF) in large animals. High-resolution ex vivo magnetic resonance imaging and histological data were used along with state-of-the-art subject-specific computational model simulations. Ex vivo data were incorporated in detailed geometric computational models for swine hearts in health (n = 5), ischemic HF (n = 5), and ischemic HF treated with alginate hydrogel injection therapy (n = 5). Hydrogel injection therapy mitigated elongation of sarcomere lengths (1.68 ± 0.10μm treated vs. 1.78 ± 0.15μm untreated, p<0.001). Systolic contractility in treated animals improved substantially (ejection fraction = 43.9 ± 2.8% treated vs. 34.7 ± 2.7% untreated, p<0.01). The in silico models realistically simulated in vivo function with >99% accuracy and predicted small myofiber strain in the vicinity of the solidified hydrogel that was sustained for up to 13 mm away from the implant. These findings suggest that the solidified alginate hydrogel material acts as an LV mid-wall constraint that significantly reduces adverse LV remodeling compared to untreated HF controls without causing negative secondary outcomes to cardiac function.
Heart failure is considered a growing epidemic and hence an important health problem in the US and worldwide. Its high prevalence (5.8 million and 23 million, respectively) is expected to increase by 25% in the US alone by 2030. Heart failure is associated with high morbidity and mortality, has a 5-year mortality rate of 50%, and contributes considerably to the overall cost of health care ($53.1 billion in the US by 2030). Despite positive initial outcomes emerging from preclinical and early clinical investigation of alginate hydrogel injection therapy as a treatment for heart failure, the lack of knowledge concerning the mechanism of action remains a major shortcoming that limits the efficacy of treatment design. To understand the mechanism of action, we combined high-resolution ex vivo magnetic resonance imaging and histological data in swine with state-of-the-art subject-specific computational model simulations. The in silico models realistically simulated in vivo function with >99% accuracy and predicted small myofiber strain in the vicinity of the solidified hydrogel that was sustained for up to 13 mm away from the implant. These findings suggest that the solidified alginate hydrogel material acts as a left ventricular mid-wall constraint that significantly reduces adverse LV remodeling compared to untreated heart failure controls without causing negative secondary outcomes to cardiac function. Moreover, if the hydrogel can be delivered percutaneously rather than via the currently used open-chest procedure, this therapy may become routine for heart failure treatment. A minimally invasive procedure would be in the best interest of this patient population; i.e., one that cannot tolerate general anesthesia and surgery, and it would be significantly more cost-effective than surgery.
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