Non-invasive estimation of the parameters of a three-element windkessel model of aortic arch arteries in patients undergoing thoracic endovascular aortic repair

Tricarico, Rosamaria; Berceli, Scott A.; Tran‐Son‐Tay, Roger; He, Yong

doi:10.3389/fbioe.2023.1127855

Cited by 3 publications

(1 citation statement)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The numerical values of R p , R d and C can be defined relying on specific patient measurements regarding mainly cardiac output and mean aortic pressure [16,[35][36][37]. Following the various literature references, the proximal resistance results to be 10% of the overall vascular resistance while the distal resistance is 90% [38].…”

Section: Model Setupmentioning

confidence: 99%

Blood Flow Simulation of Aneurysmatic and Sane Thoracic Aorta Using OpenFOAM CFD Software

Duronio,

Di Mascio

2023

Fluids

View full text Add to dashboard Cite

Cardiovascular diseases still represent one of the most deadly pathologies worldwide. Knowledge of the blood flow dynamics within the cardio-vascular system is crucial in preventing these diseases and analysing their physiology and physio-pathology. CFD simulations are highly effective in guiding clinical predictions and, more importantly, allow the evaluation of physical and clinical parameters that are difficult to measure with common diagnostic techniques. Therefore, in particular, this study is focused on investigating the hemodynamics of the thoracic aorta. Real aortic geometries regarding a sane and diseased patient presenting an aneurysm were considered. CFD simulations were performed with the OpenFOAM C++ library using patient-specific pulsatile blood flow waveforms and implementing the Windkessel pressure boundary condition for the artery outflow. The adopted methodology was preliminarily verified for assessing the numerical uncertainty and convergence. Then, the CFD results were evaluated against experimental data concerning pressure and velocity of the thoracic aorta measured with standard diagnostic techniques. The normal aorta’s blood flow was also compared against the pattern regarding the patient-specific aortic aneurysm. Parameters such as wall pressure, wall shear stress (WSS) and velocity distribution were investigated and discussed. The research highlighted that the blood flow in the aorta is strongly affected by the aneurysm onset, with the growth of recirculation zones being potentially hazardous. The outcomes of the investigation finally demonstrate how CFD simulation tools, capturing the detailed physics of the aortic flow, are powerful tools for supporting clinical activities of the cardio-vascular system.

show abstract

Section: Model Setupmentioning

confidence: 99%

Blood Flow Simulation of Aneurysmatic and Sane Thoracic Aorta Using OpenFOAM CFD Software

Duronio,

Di Mascio

2023

Fluids

View full text Add to dashboard Cite

show abstract

A new method for scaling inlet flow waveform in hemodynamic analysis of aortic dissection

Wang,

Armour,

Guo

et al. 2024

Numer Methods Biomed Eng

View full text Add to dashboard Cite

Computational fluid dynamics (CFD) simulations have shown great potentials in cardiovascular disease diagnosis and postoperative assessment. Patient‐specific and well‐tuned boundary conditions are key to obtaining accurate and reliable hemodynamic results. However, CFD simulations are usually performed under non‐patient‐specific flow conditions due to the absence of in vivo flow and pressure measurements. This study proposes a new method to overcome this challenge by tuning inlet boundary conditions using data extracted from electrocardiogram (ECG). Five patient‐specific geometric models of type B aortic dissection were reconstructed from computed tomography (CT) images. Other available data included stoke volume (SV), ECG, and 4D‐flow magnetic resonance imaging (MRI). ECG waveforms were processed to extract patient‐specific systole to diastole ratio (SDR). Inlet boundary conditions were defined based on a generic aortic flow waveform tuned using (1) SV only, and (2) with ECG and SV (ECG + SV). 4D‐flow MRI derived inlet boundary conditions were also used in patient‐specific simulations to provide the gold standard for comparison and validation. Simulations using inlet flow waveform tuned with ECG + SV not only successfully reproduced flow distributions in the descending aorta but also provided accurate prediction of time‐averaged wall shear stress (TAWSS) in the primary entry tear (PET) and abdominal regions, as well as maximum pressure difference, ∆Pmax, from the aortic root to the distal false lumen. Compared with simulations with inlet waveform tuned with SV alone, using ECG + SV in the tuning method significantly reduced the error in false lumen ejection fraction at the PET (from 149.1% to 6.2%), reduced errors in TAWSS at the PET (from 54.1% to 5.7%) and in the abdominal region (from 61.3% to 11.1%), and improved ∆Pmax prediction (from 283.1% to 18.8%) However, neither of these inlet waveforms could be used for accurate prediction of TAWSS in the ascending aorta. This study demonstrates the importance of SDR in tailoring inlet flow waveforms for patient‐specific hemodynamic simulations. A well‐tuned flow waveform is essential for ensuring that the simulation results are patient‐specific, thereby enhancing the confidence and fidelity of computational tools in future clinical applications.

show abstract

Uncertainty quantification of the pressure waveform using a Windkessel model

Flores‐Gerónimo,

Keramat,

Alastruey

et al. 2024

Numer Methods Biomed Eng

View full text Add to dashboard Cite

The Windkessel (WK) model is a simplified mathematical model used to represent the systemic arterial circulation. While the WK model is useful for studying blood flow dynamics, it suffers from inaccuracies or uncertainties that should be considered when using it to make physiological predictions. This paper aims to develop an efficient and easy‐to‐implement uncertainty quantification method based on a local gradient‐based formulation to quantify the uncertainty of the pressure waveform resulting from aleatory uncertainties of the WK parameters and flow waveform. The proposed methodology, tested against Monte Carlo simulations, demonstrates good agreement in estimating blood pressure uncertainties due to uncertain Windkessel parameters, but less agreement considering uncertain blood‐flow waveforms. To illustrate our methodology's applicability, we assessed the aortic pressure uncertainty generated by Windkessel parameters‐sets from an available in silico database representing healthy adults. The results from the proposed formulation align qualitatively with those in the database and in vivo data. Furthermore, we investigated how changes in the uncertainty of the Windkessel parameters affect the uncertainty of systolic, diastolic, and pulse pressures. We found that peripheral resistance uncertainty produces the most significant change in the systolic and diastolic blood pressure uncertainties. On the other hand, compliance uncertainty considerably modifies the pulse pressure standard deviation. The presented expansion‐based method is a tool for efficiently propagating the Windkessel parameters' uncertainty to the pressure waveform. The Windkessel model's clinical use depends on the reliability of the pressure in the presence of input uncertainties, which can be efficiently investigated with the proposed methodology. For instance, in wearable technology that uses sensor data and the Windkessel model to estimate systolic and diastolic blood pressures, it is important to check the confidence level in these calculations to ensure that the pressures accurately reflect the patient's cardiovascular condition.

show abstract

Non-invasive estimation of the parameters of a three-element windkessel model of aortic arch arteries in patients undergoing thoracic endovascular aortic repair

Cited by 3 publications

References 44 publications

Blood Flow Simulation of Aneurysmatic and Sane Thoracic Aorta Using OpenFOAM CFD Software

Blood Flow Simulation of Aneurysmatic and Sane Thoracic Aorta Using OpenFOAM CFD Software

A new method for scaling inlet flow waveform in hemodynamic analysis of aortic dissection

Uncertainty quantification of the pressure waveform using a Windkessel model

Contact Info

Product

Resources

About