Computational Fluid Dynamic Study for aTAA Hemodynamics: An Integrated Image-Based and Radial Basis Functions Mesh Morphing Approach

Capellini, Katia; Vignali, Emanuele; Costa, Emiliano; Gasparotti, Emanuele; Biancolini, Marco Evangelos; Landini, Luigi; Positano, Vincenzo; Celi, Simona

doi:10.1115/1.4040940

Cited by 57 publications

(45 citation statements)

References 51 publications

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“…This effort arises from a twofold need: from one side, to stratify the risk of LAA thrombus formation in AF patients, and, on the other hand, to develop new percutaneous closure procedures. Previous studies have demonstrated the alterations in shape, size and contraction patterns of LAA in AF condition by using different imaging techniques [12,[21][22][23].…”

Section: Discussionmentioning

confidence: 99%

Correlation between LAA Morphological Features and Computational Fluid Dynamics Analysis for Non-Valvular Atrial Fibrillation Patients

et al. 2020

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The left atrial appendage (LAA) is a complex cardiovascular structure which can yield to thrombi formation in patients with non-valvular atrial fibrillation (AF). The study of LAA fluid dynamics together with morphological features should be investigated in order to evaluate the possible connection of geometrical and hemodynamics indices with the stroke risk. To reach this goal, we conducted a morphological analysis of four different LAA shapes considering their variation during the cardiac cycle and computational fluid dynamics (CFD) simulations in AF conditions were carried out. The analysis of main geometrical LAA parameters showed a huger ostium and a reduced motility for the cauliflower and cactus shapes, as well as a lower velocity values from the CFD analysis. Such findings are in line with literature and highlight the importance of coupling dynamics imaging data with CFD calculations for providing information not available at clinical level.

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Section: Discussionmentioning

confidence: 99%

Correlation between LAA Morphological Features and Computational Fluid Dynamics Analysis for Non-Valvular Atrial Fibrillation Patients

et al. 2020

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“…Patients undergo elective repair of the ATAA on the basis of the size and progression rate of the aortic diameter, but aortic size has a limited predictive value, as adverse events may occur when aortic diameters are <55 mm, and even <45 mm [10]. Among novel approaches for risk stratification, computational modeling has shown promise in the estimation of ATAA by means of prediction of intramural stress [11] and shear stress [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Statistical Shape Analysis of Ascending Thoracic Aortic Aneurysm: Correlation between Shape and Biomechanical Descriptors

Cosentino

Raffa

Gentile

et al. 2020

JPM

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An ascending thoracic aortic aneurysm (ATAA) is a heterogeneous disease showing different patterns of aortic dilatation and valve morphologies, each with distinct clinical course. This study aimed to explore the aortic morphology and the associations between shape and function in a population of ATAA, while further assessing novel risk models of aortic surgery not based on aortic size. Shape variability of n = 106 patients with ATAA and different valve morphologies (i.e., bicuspid versus tricuspid aortic valve) was estimated by statistical shape analysis (SSA) to compute a mean aortic shape and its deformation. Once the computational atlas was built, principal component analysis (PCA) allowed to reduce the complex ATAA anatomy to a few shape modes, which were correlated to shear stress and aortic strain, as determined by computational analysis. Findings demonstrated that shape modes are associated to specific morphological features of aneurysmal aorta as the vessel tortuosity and local bulging of the ATAA. A predictive model, built with principal shape modes of the ATAA wall, achieved better performance in stratifying surgically operated ATAAs versus monitored ATAAs, with respect to a baseline model using the maximum aortic diameter. Using current imaging resources, this study demonstrated the potential of SSA to investigate the association between shape and function in ATAAs, with the goal of developing a personalized approach for the treatment of the severity of aneurysmal aorta.

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“…CFD simulation helps to overcome this limitation and was able to predict the WSS and other biomechanical parameters more accurately using the physiological blood flow condition obtained from 4D MRI data. The need for evaluating the impact of ATAAs on biomechanical properties and blood flow was emphasized in a number of previous studies . To address this need, the current article proposed a thorough and robust computational framework combining 4D MRI and CFD to study the influence of changes in aortic morphology on a number of biomechanical descriptors.…”

Section: Discussionmentioning

confidence: 99%

Computational prediction of hemodynamical and biomechanical alterations induced by aneurysm dilatation in patient‐specific ascending thoracic aortas

Jayendiran

Condemi

Campisi

et al. 2020

Numer Methods Biomed Eng

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The aim of the present work is to propose a robust computational framework combining computational fluid dynamics (CFD) and 4D flow MRI to predict the progressive changes in hemodynamics and wall rupture index (RPI) induced by aortic morphological evolutions in patients harboring ascending thoracic aortic aneurysms (ATAAs). An analytical equation has been proposed to predict the aneurysm progression based on age, sex, and body surface area. Parameters such as helicity, wall shear stress (WSS), time‐averaged WSS, oscillatory shear index, relative residence time, and viscosity were evaluated for two patients at different stages of aneurysm growth, and compared with age‐sex‐matched healthy subjects. The study shows that evolution of hemodynamics and RPI, despite being very slow in ATAAs, is strongly affected by morphological alterations and, in turn could impact biomechanical factors and aortic mechanobiology. An aspect of the current work is that the patient‐specific 4D MRI data sets were obtained with a follow‐up of 1 year and the measured time‐averaged velocity maps and flow eccentricity were compared with the CFD simulation for validation. The computational framework presented here is capable of capturing the blood flow patterns and the hemodynamic descriptors during the various stages of aneurysm growth. Further investigations will be conducted in order to verify these results on a larger cohort of patients and with long follow‐up times to finally elucidate the link between deranged hemodynamics, AA geometry, and wall mechanical properties in ATAAs.

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Computational Fluid Dynamic Study for aTAA Hemodynamics: An Integrated Image-Based and Radial Basis Functions Mesh Morphing Approach

Cited by 57 publications

References 51 publications

Correlation between LAA Morphological Features and Computational Fluid Dynamics Analysis for Non-Valvular Atrial Fibrillation Patients

Correlation between LAA Morphological Features and Computational Fluid Dynamics Analysis for Non-Valvular Atrial Fibrillation Patients

Statistical Shape Analysis of Ascending Thoracic Aortic Aneurysm: Correlation between Shape and Biomechanical Descriptors

Computational prediction of hemodynamical and biomechanical alterations induced by aneurysm dilatation in patient‐specific ascending thoracic aortas

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