Patient-specific predictions of aneurysm growth and remodeling in the ascending thoracic aorta using the homogenized constrained mixture model

Mousavi, S. Jamaleddin; Farzaneh, Solmaz

doi:10.1007/s10237-019-01184-8

Cited by 57 publications

(68 citation statements)

References 65 publications

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“…Note the excessive dilation and thickening for the simulation (c) that preserves local values of volumetric stress with respect to (b) but neglects shear stress effects, see Eq. (35); in contrast, observe the mechano-adaptive thickening with little dilation (d), with slightly decreased volumetric stresses consistent with shear stresses reduced with respect to (b), see Eq. (79).…”

Section: Appendix B Stresses During Transient Hyperelastic Responsesmentioning

confidence: 93%

“…For K τ /K σ = 0, the constraint Υ h = 1 implies preservation of volumetric stresses σ vh = σ vo (recall Eqs. (35) or (37)), which the FE simulation satisfies locally at each radial coordinate (Fig. 2) and, in particular, at the mid-thickness (Fig.…”

Section: Equilibrated Gandr Response (Stagementioning

confidence: 97%

“…The (pre)stress computed at each material point after this initial, required calculation serves as a reference for the subsequent G&R computations by means of the specified equilibrium condition in Υ h = 1, as, for example, the local preservation of volumetric Cauchy stresses at the mixture level specified in Eq. (35).…”

Section: Original (Loaded In Vivo) Homeostatic Statementioning

confidence: 99%

“…Since the idealized formula τ w = 4µQ/πa 3 is only valid for fully developed steady flows in a long circular segment, we first considered G&R driven by intramural stresses only, for which K σ = 0 and K τ = 0, such that volumetric stresses were preserved locally, recall Eq. (35). As an example, a G&R response that can be modeled with K τ = 0 in Υ is the enlargement of fusiform aneurysms, where the medial layer appears to be severely damaged (hence no shear stress regulation of smooth muscle tone) and enlargement likely occurs primarily via turnover of remnant collagen in the adventitia [7,29,[32][33][34][35].…”

Section: Non-uniform Equilibrated Gandr Response (Stage Ii) To Localizementioning

confidence: 99%

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Fast, Rate-Independent, Finite Element Implementation of a 3D Constrained Mixture Model of Soft Tissue Growth and Remodeling

Latorre¹,

Humphrey

2020

Preprint

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Constrained mixture models of soft tissue growth and remodeling enable one to simulate many evolving conditions in health, disease, and its treatment, but they tend to be computationally expensive. In this paper, we derive a new fast, robust finite element implementation based on a concept of mechanobiological equilibrium which allows computation of fully resolved long-term solutions as well as quasi-equilibrated evolutions for which imposed perturbations are slow relative to the adaptive process. We demonstrate quadratic convergence and verify the model via comparisons with semi-analytical solutions for arterial mechanics. We further examine more complex situations, including the enlargement of aneurysms, and identify new mechanobiological insights into factors that affect the nearby non-aneurysmal segment as it responds to the changing mechanics within the diseased segment. Since this new 3D approach can be implemented within many existing finite element solvers, we submit that constrained mixture models of growth and remodeling can now be used more widely.

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Section: Appendix B Stresses During Transient Hyperelastic Responsesmentioning

confidence: 93%

Section: Equilibrated Gandr Response (Stagementioning

confidence: 97%

Section: Original (Loaded In Vivo) Homeostatic Statementioning

confidence: 99%

Section: Non-uniform Equilibrated Gandr Response (Stage Ii) To Localizementioning

confidence: 99%

See 2 more Smart Citations

Fast, Rate-Independent, Finite Element Implementation of a 3D Constrained Mixture Model of Soft Tissue Growth and Remodeling

Latorre¹,

Humphrey

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…We would like to acknowledge that the limitation of the present growth prediction model is that it does not reproduce the complex multifactorial phenomenon of aneurysm growth but only its main components such as localized increase of diameter and inclination angle. Nevertheless, our future work will be focused on using sophisticated growth and remodelling models to predict the growth of aneurysm and to have more realistic predictions …”

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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Patient‐specific computational modeling of endovascular aneurysm repair: State of the art and future directions

Avril

Gee

Hemmler

et al. 2021

Numer Methods Biomed Eng

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Endovascular aortic repair (EVAR) has become the preferred intervention option for aortic aneurysms and dissections. This is because EVAR is much less invasive than the alternative open surgery repair. While in‐hospital mortality rates are smaller for EVAR than open repair (1%–2% vs. 3%–5%), the early benefits of EVAR are lost after 3 years due to larger rates of complications in the EVAR group. Clinicians follow instructions for use (IFU) when possible, but are left with personal experience on how to best proceed and what choices to make with respect to stent‐graft (SG) model choice, sizing, procedural options, and their implications on long‐term outcomes. Computational modeling of SG deployment in EVAR and tissue remodeling after intervention offers an alternative way of testing SG designs in silico, in a personalized way before intervention, to ultimately select the strategies leading to better outcomes. Further, computational modeling can be used in the optimal design of SGs in cases of complex geometries. In this review, we address some of the difficulties and successes associated with computational modeling of EVAR procedures. There is still work to be done in all areas of EVAR in silico modeling, including model validation, before models can be applied in the clinic, but much progress has already been made. Critical to clinical implementation are current efforts focusing on developing fast algorithms that can achieve (near) real‐time solutions, as well as ways of dealing with inherent uncertainties related to patient aortic wall degradation on an individualized basis. We are optimistic that EVAR modeling in the clinic will soon become a reality to help clinicians optimize EVAR interventions and ultimately reduce EVAR‐associated complications.

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Patient-specific predictions of aneurysm growth and remodeling in the ascending thoracic aorta using the homogenized constrained mixture model

Cited by 57 publications

References 65 publications

Fast, Rate-Independent, Finite Element Implementation of a 3D Constrained Mixture Model of Soft Tissue Growth and Remodeling

Fast, Rate-Independent, Finite Element Implementation of a 3D Constrained Mixture Model of Soft Tissue Growth and Remodeling

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

Patient‐specific computational modeling of endovascular aneurysm repair: State of the art and future directions

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