A Computational Framework for Pre-Interventional Planning of Peripheral Arteriovenous Malformations

Franzetti, Gaia; Bonfanti, Mirko; Tanade, Cyrus; Lim, Chung Sim; Tsui, Janice; Hamilton, George; Díaz‐Zuccarini, Vanessa; Balabani, Stavroula

doi:10.1007/s13239-021-00572-5

Cited by 3 publications

(2 citation statements)

References 21 publications

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“…As a kind of fluid, blood was often described by continuum model. According to the property of venous blood flow, 1118 the blood fluid was considered as incompressible, laminar, steady and homogeneous. The corresponding governing equation for blood flow was written as follows:

ρ ([], \frac{\partial boldu}{∂t} goodbreak+ ((), boldu \cdot \nabla) boldu) goodbreak= goodbreak- \nabla \cdot p goodbreak+ μ \nabla^{2} boldu

where

boldu

is the velocity of the fluid flow, p is the pressure, ρ is the density, μ is the dynamic viscosity.…”

Section: Methodsmentioning

confidence: 99%

“…Integrated with Darcy's law, it considered the momentum transfer phenomenon caused by viscosity effect and pressure gradient near the interface between free flow and porous media flow, and then realized the coupling of external free flow and porous media flow. Finally, the velocity and pressure of the liquid are calculated by solving the coupled Brinkman‐Forchheimer equation given as follows:

\frac{1}{{italicε}_{p}^{2}} italicρ ([], \frac{\partial boldu}{\partial t} goodbreak+ ((), boldu \cdot \nabla) boldu) goodbreak= goodbreak- \nabla \cdot p goodbreak+ italicμ \frac{1}{{italicε}_{p}} \nabla^{2} boldu goodbreak- ((), \frac{μ}{κ} goodbreak+ C_{F} italicρ (||, u) goodbreak- \frac{italicρ \nabla \cdot boldu}{{italicε}_{p}^{2}}) boldu

where the porosity of thrombus takes value of

ε_{p} = 0.15, κ

is the permeability of thrombus, taking

κ = 5 \times 10^{- 11} m^{2} .

18 . C F is the Forchheimer constant.…”

Section: Methodsmentioning

confidence: 99%

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Numerical simulation and experimental validation of thrombolytic therapy for patients with venous isomer and normal venous valves

Lin

Zhang

et al. 2023

Numer Methods Biomed Eng

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Thrombus is an extremely dangerous factor in the human body that can block the blood vessel. Once thrombosis happens in venous of lower limbs, local blood flow is impeded. This leads to venous thromboembolism (VTE) and even pulmonary embolism. In recent years, venous thromboembolism has frequently occurred in a variety of people, and there is no effective treatment for patients with different venous structures. For the patients with venous isomer with single valve structure, we establish a coupled computational model to simulate the process of thrombolysis with multi‐dose treatment schemes by considering the blood as non‐Newtonian fluid. Then, the corresponding in vitro experimental platform is built to verify the performance of the developed mathematical model. At last, the effects of different fluid models, valve structures and drug doses on thrombolysis are comprehensively studied through numerical and experimental observations. Comparing with the experimental results, the relative error of blood boosting index (BBI) obtained from non‐Newtonian fluid model is 11% smaller than Newtonian fluid. In addition, the BBI from venous isomer is 1300% times stronger than patient with normal venous valve while the valve displacement is 500% times smaller. As consequence, low eddy current and strong molecular diffusion near the thrombus in case of isomer promote thrombolysis rate up to 18%. Furthermore, the 80 μM dosage of thrombolytic drugs gets the maximum thrombus dissolution rate 18% while the scheme of 50 μM doses obtains a thrombolysis rate of 14% in case of venous isomer. Under the two administration schemes for isomer patients, the rates from experiments are around 19.1% and 14.9%, respectively. It suggests that the proposed computational model and the designed experiment platform can potentially help different patients with venous thromboembolism to carry out clinical medication prediction.

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ρ ([], \frac{\partial boldu}{∂t} goodbreak+ ((), boldu \cdot \nabla) boldu) goodbreak= goodbreak- \nabla \cdot p goodbreak+ μ \nabla^{2} boldu

where

boldu

is the velocity of the fluid flow, p is the pressure, ρ is the density, μ is the dynamic viscosity.…”

Section: Methodsmentioning

confidence: 99%

\frac{1}{{italicε}_{p}^{2}} italicρ ([], \frac{\partial boldu}{\partial t} goodbreak+ ((), boldu \cdot \nabla) boldu) goodbreak= goodbreak- \nabla \cdot p goodbreak+ italicμ \frac{1}{{italicε}_{p}} \nabla^{2} boldu goodbreak- ((), \frac{μ}{κ} goodbreak+ C_{F} italicρ (||, u) goodbreak- \frac{italicρ \nabla \cdot boldu}{{italicε}_{p}^{2}}) boldu

where the porosity of thrombus takes value of

ε_{p} = 0.15, κ

is the permeability of thrombus, taking

κ = 5 \times 10^{- 11} m^{2} .

18 . C F is the Forchheimer constant.…”

Section: Methodsmentioning

confidence: 99%

Numerical simulation and experimental validation of thrombolytic therapy for patients with venous isomer and normal venous valves

Lin

Zhang

et al. 2023

Numer Methods Biomed Eng

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Computational modeling and simulation for endovascular embolization of cerebral arteriovenous malformations with liquid embolic agents

Zhang,

Chen,

Zhang

et al. 2023

Acta Mech. Sin.

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Endovascular embolization of arteriovenous malformations (AVMs) in the brain usually requires injecting liquid embolic agents (LEAs) to reduce blood flow through the malformation. In clinical procedures, the feeding artery into which the LEAs are injected, and the amount of LEAs needs to be carefully planned preoperatively. Computational fluid dynamics can simulate the injecting process of LEAs in nidus and evaluate the therapeutic effects of different procedures preoperatively. Applying a porous media model avoided the difficulties of geometric modeling of AVMs, and the complex vascular network structure within the nidus was reproduced. The multi-phase flow was applied to simulate the interaction between LEAs and blood. The viscosity of LEAs is determined by the concentration of its solute ethylene-vinyl alcohol copolymer (EVOH). The diffusion process of the solvent dimethyl sulfoxide (DMSO) was calculated by solving the species transport equation. The coagulation of LEAs was simulated by constructing the relationship between the concentration of EVOH and viscosity. The numerical simulation method of LEAs for injection and coagulation was tested on two patient-specific AVMs. The calculations predicted the flow direction of the LEAs in the nidus. The morphology of the injected LEAs could be well visualized by 3D rendering. Quantitative analysis was conducted, including flow rate changes at the feeding arteries and draining veins. The embolization process of AVMs with LEAs can be simulated by computational fluid dynamics (CFD) methods to show the therapeutic effects of different embolization procedure planning, the optimal treatment plan can be determined.

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Hemodynamic Study of Cerebral Arteriovenous Malformation: Newtonian and Non-Newtonian Blood Flow

Ganjkhanlou,

Shahidian,

Shahmohammadi

2024

World Neurosurgery

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A Computational Framework for Pre-Interventional Planning of Peripheral Arteriovenous Malformations

Cited by 3 publications

References 21 publications

Numerical simulation and experimental validation of thrombolytic therapy for patients with venous isomer and normal venous valves

Numerical simulation and experimental validation of thrombolytic therapy for patients with venous isomer and normal venous valves

Computational modeling and simulation for endovascular embolization of cerebral arteriovenous malformations with liquid embolic agents

Hemodynamic Study of Cerebral Arteriovenous Malformation: Newtonian and Non-Newtonian Blood Flow

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