svFSI: A Multiphysics Package for Integrated Cardiac
Modeling

Zhu, Chi; Vedula, Vijay; Parker, Dave; Wilson, Nathan M.; Shadden, Shawn C.; Marsden, Alison

doi:10.21105/joss.04118

Cited by 27 publications

(17 citation statements)

References 17 publications

(15 reference statements)

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“…TAWSS (TAWSS=1T∫0Tfalse∣WSSfalse∣dt) contours, OSI true[OSI=12true(1−true|∫0TWSS dttrue|∫0Tfalse|WSSfalse|italicdttrue)true], and velocity profiles for a time-dependent model were acquired by solving the Navier-Stokes equations using the using svFSI solver ( 91 )ρtrue(normal∂trueV→normal∂t+trueV→.∇trueV→true)=−∇P+μ∇2Vtrue→∇.Vtrue→=0…”

Section: Methodsmentioning

confidence: 99%

Exercise mitigates flow recirculation and activates metabolic transducer SCD1 to catalyze vascular protective metabolites

Cavallero,

Roustaei,

Satta

et al. 2024

Sci. Adv.

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Exercise promotes pulsatile shear stress in the arterial circulation and ameliorates cardiometabolic diseases. However, exercise-mediated metabolic transducers for vascular protection remain under-investigated. Untargeted metabolomic analysis demonstrated that wild-type mice undergoing voluntary wheel running exercise expressed increased endothelial stearoyl-CoA desaturase 1 (SCD1) that catalyzes anti-inflammatory lipid metabolites, namely, oleic (OA) and palmitoleic acids (PA), to mitigate NF-κB–mediated inflammatory responses. In silico analysis revealed that exercise augmented time-averaged wall shear stress but mitigated flow recirculation and oscillatory shear index in the lesser curvature of the mouse aortic arch. Following exercise, endothelial Scd1 –deleted mice ( Ldlr −/− Scd1 EC−/− ) on high-fat diet developed persistent VCAM1-positive endothelium in the lesser curvature and the descending aorta, whereas SCD1 overexpression via adenovirus transfection mitigated endoplasmic reticulum stress and inflammatory biomarkers. Single-cell transcriptomics of the aorta identified Scd1 -positive and Vcam1 -negative endothelial subclusters interacting with other candidate genes. Thus, exercise mitigates flow recirculation and activates endothelial SCD1 to catalyze OA and PA for vascular endothelial protection.

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Section: Methodsmentioning

confidence: 99%

Exercise mitigates flow recirculation and activates metabolic transducer SCD1 to catalyze vascular protective metabolites

Cavallero,

Roustaei,

Satta

et al. 2024

Sci. Adv.

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“…2006), which is implemented in the open-source software svFSI (Zhu et al. 2022). The CMM has recently been rigorously verified with Womersley's deformable wall analytical solution (Filonova et al.…”

Section: Analytic Solutionmentioning

confidence: 99%

“…The characteristics of pulse wave propagation is critical in understanding the behaviour and functionality of arteries and, therefore, cardiovascular fitness (Safar, Levy & Struijker-Boudier 2003;van de Vosse & Stergiopulos 2011). Pulse wave propagation has been studied extensively through experiments (Moens 1878; Segers & Verdonck 2000;Bessems et al 2008), theoretical analysis (Korteweg 1878;Womersley 1955Womersley , 1957Papadakis 2011) and numerical simulations (Alastruey et al 2011;Mynard & Smolich 2015;Charlton et al 2019;Zimmermann et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Analytic solution for pulse wave propagation in flexible tubes with application to a patient-specific arterial tree

Wu,

Zhu

2023

J. Fluid Mech.

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In this paper, we present an analytic solution for pulse wave propagation in a flexible arterial model with tapering, physiological boundary conditions and variable wall properties (wall elasticity and thickness). The change of wall properties follows a profile that is proportional to $r^\alpha$ , where $r$ represents the lumen radius and $\alpha$ is a material coefficient. The cross-sectionally averaged velocity and pressure are obtained by solving a hyperbolic system derived from the mass and momentum conservations, and they are expressed in Bessel functions of order $(4-\alpha )/(3-\alpha )$ and $1/(3-\alpha )$ , respectively. The solution is successfully validated by comparing it with numerical results from three-dimensional (3-D) fluid–structure interaction simulations. Subsequently, the solution is employed to study pulse wave propagation in an arterial model, revealing that the wall properties and the physiological outlet boundary conditions, such as the resistor–capacitor–resistor (RCR) model, play a crucial role in characterizing the input impedance and reflection coefficient. At low-frequency range, the input impedance is found to be insensitive to the wall properties and is primarily determined by the RCR parameters. At high-frequency range, the input impedance oscillates around the local characteristic impedance, and the oscillation amplitude varies non-monotonically with $\alpha$ . Expressions for the input impedance at both low-frequency and high-frequency limits are presented. This analytic solution is also successfully applied to model flow inside a patient-specific arterial tree, with the maximum relative errors in pressure and flow rate never exceeding $1.6\,\%$ and $9.0\,\%$ when compared with results from 3-D numerical simulations.

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“…All electrophysiology simulations are performed at the Stanford Research Computing Center using svFSIplus [70], a C++ high-performance computing multiphysics and multiscale finite element solver for cardiac and cardiovascular modeling. This solver is part of the SimVascular software suite for patient-specific cardiovascular modeling [64].…”

Section: Software and Hardwarementioning

confidence: 99%

Digital twinning of cardiac electrophysiology for congenital heart disease

Salvador,

Kong,

Peirlinck

et al. 2023

Preprint

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In recent years, blending mechanistic knowledge with machine learning has had a major impact in digital healthcare. In this work, we introduce a computational pipeline to build certified digital replicas of cardiac electrophysiology in pediatric patients with congenital heart disease. We construct the patient-specific geometry by means of semi-automatic segmentation and meshing tools. We generate a dataset of electrophysiology simulations covering cell-to-organ level model parameters and utilizing rigorous mathematical models based on differential equations. We previously proposed Branched Latent Neural Maps (BLNMs) as an accurate and efficient means to recapitulate complex physical processes in a neural network. Here, we employ BLNMs to encode the parametrized temporal dynamics of in silico 12-lead electrocardiograms (ECGs). BLNMs act as a geometry-specific surrogate model of cardiac function for fast and robust parameter estimation to match clinical ECGs in pediatric patients. Identifiability and trustworthiness of calibrated model parameters are assessed by sensitivity analysis and uncertainty quantification.

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svFSI: A Multiphysics Package for Integrated Cardiac Modeling

Cited by 27 publications

References 17 publications

Exercise mitigates flow recirculation and activates metabolic transducer SCD1 to catalyze vascular protective metabolites

Exercise mitigates flow recirculation and activates metabolic transducer SCD1 to catalyze vascular protective metabolites

Analytic solution for pulse wave propagation in flexible tubes with application to a patient-specific arterial tree

Digital twinning of cardiac electrophysiology for congenital heart disease

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