Uncertainty Quantification in the In Vivo Image-Based Estimation of Local Elastic Properties of Vascular Walls

Fanni, Benigno Marco; Antonuccio, Maria Nicole; Pizzuto, Alessandra; Berti, Sérgio; Santoro, Giuseppe E.; Celi, Simona

doi:10.3390/jcdd10030109

Cited by 7 publications

(2 citation statements)

References 73 publications

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“…The effect of uncertainty in the elastic module (E) on a patient-specific aortic model was investigated using an FSI approach [54]. The uncertainty quantification was performed using the generalized polynomial chaos (gPC) expansion technique.…”

Section: Blood Flow Within Vascular Pathwaysmentioning

confidence: 99%

Modeling Dynamics of the Cardiovascular System Using Fluid-Structure Interaction Methods

Syed

Khan

Toma

2023

Biology

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Using fluid-structure interaction algorithms to simulate the human circulatory system is an innovative approach that can provide valuable insights into cardiovascular dynamics. Fluid-structure interaction algorithms enable us to couple simulations of blood flow and mechanical responses of the blood vessels while taking into account interactions between fluid dynamics and structural behaviors of vessel walls, heart walls, or valves. In the context of the human circulatory system, these algorithms offer a more comprehensive representation by considering the complex interplay between blood flow and the elasticity of blood vessels. Algorithms that simulate fluid flow dynamics and the resulting forces exerted on vessel walls can capture phenomena such as wall deformation, arterial compliance, and the propagation of pressure waves throughout the cardiovascular system. These models enhance the understanding of vasculature properties in human anatomy. The utilization of fluid-structure interaction methods in combination with medical imaging can generate patient-specific models for individual patients to facilitate the process of devising treatment plans. This review evaluates current applications and implications of fluid-structure interaction algorithms with respect to the vasculature, while considering their potential role as a guidance tool for intervention procedures.

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Section: Blood Flow Within Vascular Pathwaysmentioning

confidence: 99%

Modeling Dynamics of the Cardiovascular System Using Fluid-Structure Interaction Methods

Syed

Khan

Toma

2023

Biology

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“…The mechanism of AAA rupture is quite complex due to different material layers and uncertainties in the material properties on the AAA wall [ 21 ]. The wall structure consists of intima, media, and adventitia layers of the artery [ 22 , 23 , 24 ].…”

Section: Introductionmentioning

confidence: 99%

Effect of Intraluminal Thrombus Burden on the Risk of Abdominal Aortic Aneurysm Rupture

Arslan

Salman

2023

JCDD

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Abdominal aortic aneurysm (AAA) is a critical health disorder, where the abdominal aorta dilates more than 50% of its normal diameter. Enlargement in abdominal aorta alters the hemodynamics and flow-induced forces on the AAA wall. Depending on the flow conditions, the hemodynamic forces on the wall may result in excessive mechanical stresses that lead to AAA rupture. The risk of rupture can be predicted using advanced computational techniques such as computational fluid dynamics (CFD) and fluid–structure interaction (FSI). For a reliable rupture risk assessment, formation of intraluminal thrombus (ILT) and uncertainty in arterial material properties should be taken into account, mainly due to the patient-specific differences and unknowns in AAAs. In this study, AAA models are computationally investigated by performing CFD simulations combined with FSI analysis. Various levels of ILT burdens are artificially generated in a realistic AAA geometry, and the peak effective stresses are evaluated to elucidate the effect of material models and ILT formation. The results indicate that increasing the ILT burden leads to lowered effective stresses on the AAA wall. The material properties of the artery and ILT are also effective on the stresses; however, these effects are limited compared to the effect of ILT volume in the AAA sac.

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Uncertainty quantification of the pressure waveform using a Windkessel model

Flores‐Gerónimo,

Keramat,

Alastruey

et al. 2024

Numer Methods Biomed Eng

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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.

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Uncertainty Quantification in the In Vivo Image-Based Estimation of Local Elastic Properties of Vascular Walls

Cited by 7 publications

References 73 publications

Modeling Dynamics of the Cardiovascular System Using Fluid-Structure Interaction Methods

Modeling Dynamics of the Cardiovascular System Using Fluid-Structure Interaction Methods

Effect of Intraluminal Thrombus Burden on the Risk of Abdominal Aortic Aneurysm Rupture

Uncertainty quantification of the pressure waveform using a Windkessel model

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