Haemodynamic imaging of thoracic stent-grafts by computational fluid dynamics (CFD): presentation of a patient-specific method combining magnetic resonance imaging and numerical simulations
Abstract:• Functional vascular imaging of the thoracic aorta offers new diagnostic opportunities • CFD can model vascular haemodynamics for clinical aortic problems • Combining CFD with MRI offers patient specific method of aortic analysis • Haemodynamic analysis of stent-grafts could improve clinical management and follow-up.
“…The geometry movements are generated from a 4D sequence (MRI or CT scan images) treated by an appropriate image registration algorithm [41,42]. This approach has been used before to compute blood flow in aortas [43]. It is further developed for application to the left heart flow, notably by introducing valve modeling.…”
Section: Recent Technological Innovations In Imaging Techniques Have mentioning
To cite this version:Christophe Chnafa, Simon Mendez, Franck Nicoud. Image-based large-eddy simulation in a realistic left heart. Computers and Fluids, Elsevier, 2014, 94, pp.173-187. 10.1016/j.compfluid.2014
“…The geometry movements are generated from a 4D sequence (MRI or CT scan images) treated by an appropriate image registration algorithm [41,42]. This approach has been used before to compute blood flow in aortas [43]. It is further developed for application to the left heart flow, notably by introducing valve modeling.…”
Section: Recent Technological Innovations In Imaging Techniques Have mentioning
To cite this version:Christophe Chnafa, Simon Mendez, Franck Nicoud. Image-based large-eddy simulation in a realistic left heart. Computers and Fluids, Elsevier, 2014, 94, pp.173-187. 10.1016/j.compfluid.2014
“…Finally the N − 1 deformations are computed through this iterative optimisation process. This approach was successfully applied before to large vessels as the aorta cross [29].…”
Section: Extraction Of the Heart Deformationmentioning
confidence: 99%
“…In the present work, an image-based CFD method developed to compute flows in aortas [29] is extended to compute intracardiac flows. Medical images are used to generate a moving patient-specific domain, in which the blood flow equations are solved.…”
A numerical framework designed to compute the blood flow in patientspecific human hearts is presented. The geometry of the heart cavities and associated wall motion are extracted from 4D medical images while the valves of the heart are accounted for thanks to low order geometrical models. The resulting blood flow equations are solved using a fourth-order low-dissipative finite-volume scheme and a mixed Aribtrary Lagrangian-Eulerian / Immersed Boundary framework. On top of retrieving the main fluid flow phenomena commonly observed in the left heart, the methodology allows studying the heart flow dynamics, including the turbulence characteristics and cycle-to-cycle variations.
“…Although such combined studies are under extensive research, a reasonable comparison method has not yet been developed. Most of these works do either not describe in detail how the comparisons were achieved exactly or perform visual interpretation [2,3,4], whereas some other works compare velocity magnitude profiles and/or peak-velocities [5,6], linear correlation coefficients [7] or volumetric flow rates [8]. Most of these comparisons are performed on 2D planes, do not define any norm or do not consider flow properties.…”
Recent achievements in 4D flow MRI increased the interest of CFD-MRI studies, which require comparison of velocity fields from both approaches for validation purposes. A novel flow regularization approach is proposed to provide a ground truth and to perform robust, mathematically reasonable comparisons between CFD and MRI. Our suggested method projects the measured and denoised data into the same space as the computational domain and applies the Helmholtz-Hodge theorem to recover the divergence-free property of the flow field by decomposing the velocity field into its divergence-free, curl-free and harmonic components. Furthermore, an aortic phantom study has been set-up under fully controlled laminar flow conditions with helical flow patterns to validate the proposed method using phase-contrast MRI measurements, whereas a dynamic stenosed case was used under turbulent flow conditions to analyse the robustness of applied pre-processings including the denoising of MRI data and the decomposition of velocity vector field.
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