Applications of Computational Modeling in Cardiac Surgery

Lee, Lik Chuan; Genet, Martin; Dang, Alan B.C.; Ge, Liang; Guccione, Julius M.; Ratcliffe, Mark B.

doi:10.1111/jocs.12332

Cited by 46 publications

(37 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This lets us to recover some mechanical variables, including stress profiles, and allows us to directly compare alterations in response to cardiomyocyte death and collagen degradation. This model, as in many others, has a number of material parameters that are difficult to calibrate [30]. …”

Section: Discussionmentioning

confidence: 99%

Computational modeling of acute myocardial infarction

Saéz

Kuhl

2015

Computer Methods in Biomechanics and Biomedical Engineering

View full text Add to dashboard Cite

Myocardial infarction, commonly known as heart attack, is caused by reduced blood supply and damages the heart muscle because of a lack of oxygen. Myocardial infarction initiates a cascade of biochemical and mechanical events. In the early stages, cardiomyocytes death, wall thinning, collagen degradation, and ventricular dilation are the immediate consequences of myocardial infarction. In the later stages, collagenous scar formation in the infarcted zone and hypertrophy of the non-infarcted zone are auto-regulatory mechanisms to partly correct for these events. Here we propose a computational model for the short-term adaptation after myocardial infarction using the continuum theory of multiplicative growth. Our model captures the effects of cell death initiating wall thinning, and collagen degradation initiating ventricular dilation. Our simulations agree well with clinical observations in early myocardial infarction. They represent a first step towards simulating the progression of myocardial infarction with the ultimate goal to predict the propensity toward heart failure as a function of infarct intensity, location, and size.

show abstract

Section: Discussionmentioning

confidence: 99%

Computational modeling of acute myocardial infarction

Saéz

Kuhl

2015

Computer Methods in Biomechanics and Biomedical Engineering

View full text Add to dashboard Cite

show abstract

“…Computational modeling can help to better understand the interplay between the electrical and the mechanical behavior in the heart, that would otherwise be difficult to characterize in laboratory experiments [8, 37]. Given the complexity of these interactions, different computational studies decide to include or neglect certain components of the electromechanical system.…”

Section: Motivationmentioning

confidence: 99%

The importance of mechano-electrical feedback and inertia in cardiac electromechanics

Costabal

Concha

Hurtado

et al. 2017

Computer Methods in Applied Mechanics and Engineering

View full text Add to dashboard Cite

In the past years, a number cardiac electromechanics models have been developed to better understand the excitation-contraction behavior of the heart. However, there is no agreement on whether inertial forces play a role in this system. In this study, we assess the influence of mass in electromechanical simulations, using a fully coupled finite element model. We include the effect of mechano-electrical feedback via stretch activated currents. We compare five different models: electrophysiology, electromechanics, electromechanics with mechano-electrical feedback, electromechanics with mass, and electromechanics with mass and mechano-electrical feedback. We simulate normal conduction to study conduction velocity and spiral waves to study fibrillation. During normal conduction, mass in conjunction with mechano-electrical feedback increased the conduction velocity by 8.12% in comparison to the plain electrophysiology case. During the generation of a spiral wave, mass and mechano-electrical feedback generated secondary wavefronts, which were not present in any other model. These secondary wavefronts were initiated in tensile stretch regions that induced electrical currents. We expect that this study will help the research community to better understand the importance of mechanoelectrical feedback and inertia in cardiac electromechanics.

show abstract

“…To address cardiovascular diseases, one approach is the use of personalized models for quantitative diagnostic, prognostic, and treatment optimization (Lee, Genet, et al, 2014b). The current bottlenecks in personalized cardiac modeling include the assessment of myofiber architecture (Toussaint, Stoeck, et al, 2013; Harmer, Pushparajah, et al, 2013), non-invasive pressure measurement, tissue properties orthotropy and regionality (Lee, Wenk, et al, 2011; Xi, Lamata, et al, 2011; Marchesseau, Delingette, et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Heterogeneous growth-induced prestrain in the heart

Genet

Rausch²,

Lee³

et al. 2015

Journal of Biomechanics

View full text Add to dashboard Cite

Even when entirely unloaded, biological structures are not stress-free, as shown by Y.C. Fung’s seminal opening angle experiment on arteries and the left ventricle. As a result of this prestrain, subject-specific geometries extracted from medical imaging do not represent an unloaded reference configuration necessary for mechanical analysis, even if the structure is externally unloaded. Here we propose a new computational method to create physiological residual stress fields in subject-specific left ventricular geometries using the continuum theory of fictitious configurations combined with a fixed-point iteration. We also reproduced the opening angle experiment on four swine models, to characterize the range of normal opening angle values. The proposed method generates residual stress fields which can reliably reproduce the range of opening angles between 8.7±1.8 and 16.6 ± 13.7 as measured experimentally. We demonstrate that including the effects of prestrain reduces the left ventricular stiffness by up to 40%, thus facilitating the ventricular filling, which has a significant impact on cardiac function. This method can improve the fidelity of subject-specific models to improve our understanding of cardiac diseases and to optimize treatment options.

show abstract

Applications of Computational Modeling in Cardiac Surgery

Cited by 46 publications

References 47 publications

Computational modeling of acute myocardial infarction

Computational modeling of acute myocardial infarction

The importance of mechano-electrical feedback and inertia in cardiac electromechanics

Heterogeneous growth-induced prestrain in the heart

Contact Info

Product

Resources

About