In the last decade, there was been increasing interest in finding imaging techniques able to provide a functional vascular imaging of the thoracic aorta. The purpose of this paper is to present an imaging method combining magnetic resonance imaging (MRI) and computational fluid dynamics (CFD) to obtain a patient-specific haemodynamic analysis of patients treated by thoracic endovascular aortic repair (TEVAR).
MRI was used to obtain boundary conditions. MR angiography (MRA) was followed by cardiac-gated cine sequences which covered the whole thoracic aorta. Phase contrast imaging provided the inlet and outlet profiles. A CFD mesh generator was used to model the arterial morphology, and wall movements were imposed according to the cine imaging. CFD runs were processed using the finite volume (FV) method assuming blood as a homogeneous Newtonian fluid.
Twenty patients (14 men; mean age 62.2 years) with different aortic lesions were evaluated. Four-dimensional mapping of velocity and wall shear stress were obtained, depicting different patterns of flow (laminar, turbulent, stenosis-like) and local alterations of parietal stress in-stent and along the native aorta.
A computational method using a combined approach with MRI appears feasible and seems promising to provide detailed functional analysis of thoracic aorta after stent-graft implantation.
• 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.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
Tax calculation will be finalised during checkout.
Magnetic resonance imaging
Computational fluid dynamics
Thoracic endovascular aortic repair
Magnetic resonance angiography
Phase contrast imaging
Wall shear stress
Balanced turbo field echo
Thoracic aortic aneurysms
Acute traumatic aortic rupture
Fillinger MF, Greenberg RK, McKinsey JF, Chaikof EL (2010) Society for Vascular Surgery Ad Hoc Committee on TEVAR Reporting Standards. Reporting standards for thoracic endovascular aortic repair (TEVAR). J Vasc Surg 52:1022–1033
Hodgson KJ, Matsumura JS, Ascher E, Dake MD, Sacks D, Krol K, Bersin RM, SVS/SIR/SCAI/SVMB Writing Committee (2006) Clinical competence statement on thoracic endovascular aortic repair (TEVAR)—multispecialty consensus recommendations. A report of the SVS/SIR/SCAI/SVMB Writing Committee to develop a clinical competence standard for TEVAR. J Vasc Surg 43:858–862
Corbillon E, Bergeron P, Poullié AI, Primus C, Ojasoo T, Gay J (2008) The French National Authority for Health reports on thoracic stent grafts. J Vasc Surg 47:1099–1107
Frydrychowicz A, Francois CJ, Turski PA (2011) Four-dimensional phase contrast magnetic resonance angiography: potential clinical applications. Eur J Radiol 80:24–35
Hope TA, Herfkens RJ (2008) Imaging of the thoracic aorta with time-resolved three-dimensional phase-contrast MRI: a review. Semin Thorac Cardiovasc Surg 20:358–364
Markl M, Draney MT, Miller DC et al (2005) Time-resolved three-dimensional magnetic resonance velocity mapping of aortic flow in healthy volunteers and patients after valve-sparing aortic root replacement. J Thorac Cardiovasc Surg 130:456–463
Hope TA, Markl M, Wigstrom L, Alley MT, Miller DC, Herfkens RJ (2007) Comparison of flow patterns in ascending aortic aneurysms and volunteers using four-dimensional magnetic resonance velocity mapping. J Magn Reson Imaging 26:1471–1479
Frydrychowicz A, Harloff A, Jung B et al (2007) Time-resolved, 3-dimensional magnetic resonance flow analysis at 3 T: visualization of normal and pathological aortic vascular hemodynamics. J Comput Assist Tomogr 31:9–15
Howell BA, Kim T, Cheer A, Dwyer H, Saloner D, Chuter TA (2007) Computational fluid dynamics within bifurcated abdominal aortic stent-grafts. J Endovasc Ther 14:138–143
Frauenfelder T, Lotfey M, Boehm T, Wildermuth S (2006) Computational fluid dynamics: hemodynamic changes in abdominal aortic aneurysm after stent-graft implantation. Cardiovasc Intervent Radiol 29:613–623
Sethian JA (1999) Level set methods and fast marching methods: evolving interfaces in computational geometry, fluid mechanics, computer vision, and materials science, 2nd edn. Cambridge University Press, Cambridge
Figueroa CA, Taylor CA, Chiou AJ, Yeh V, Zarins CK (2009) Magnitude and direction of pulsatile displacement forces acting on thoracic aortic endografts. J Endovasc Ther 16:350–358
Moreno RNF, Veunac L, Rousseau H (2006) Non-linear-transformation-field to build moving meshes for patient specific blood flow simulations. In: Wesseling P, Onate E, Periaux J (eds) European conference on computational fluid dynamics. TU Delft, Delft
Canstein C, Cachot P, Faust A et al (2008) 3D MR flow analysis in realistic rapid-prototyping model systems of the thoracic aorta: comparison with in vivo data and computational fluid dynamics in identical vessel geometries. Magn Reson Med 59:535–546
Markl M, Harloff A, Bley TA et al (2007) Time-resolved 3D MR velocity mapping at 3 T: improved navigator-gated assessment of vascular anatomy and blood flow. J Magn Reson Imaging 25:824–831
Lima JA, Desai MY (2004) Cardiovascular magnetic resonance imaging: current and emerging applications. J Am Coll Cardiol 44:1164–1171
Molony DS, Kavanagh EG, Madhavan P, Walsh MT, McGloughlin TM (2010) A computational study of the magnitude and direction of migration forces in patient-specific abdominal aortic aneurysm stent-grafts. Eur J Vasc Endovasc Surg 40:332–339
Prasad A, To LK, Gorrepati ML, Zarins CK, Figueroa CA (2011) Computational analysis of stresses acting on intermodular junctions in thoracic aortic endografts. J Endovasc Ther 18:559–568
Srichai MB, Kim S, Axel L, Babb J, Hecht EM (2010) Non-gadolinium-enhanced 3-dimensional magnetic resonance angiography for the evaluation of thoracic aortic disease: a preliminary experience. Tex Heart Inst J 37:58–65
Tay WB, Tseng YH, Lin LY, Tseng WY (2011) Towards patient-specific cardiovascular modeling system using the immersed boundary technique. Biomed Eng Online 10:52
Saber NR, Gosman AD, Wood NB, Kilner PJ, Charrier CL, Firmin DN (2001) Computational flow modeling of the left ventricle based on in vivo MRI data: initial experience. Ann Biomed Eng 29:275–283
Kitajima HD, Sundareswaran KS, Teisseyre TZ, et al (2008) Comparison of particle image velocimetry and phase contrast MRI in a patient-specific extracardiac total cavopulmonary connection. J Biomech Eng 130:041004
Nichols WW, O’Rourke MF (2005) McDonald’s blood flow in arteries: theoretical, experimental and clinical principles, 5th edn. Hodder Arnold, London
Saber NR, Wood NB, Gosman AD et al (2003) Progress towards patient-specific computational flow modeling of the left heart via combination of magnetic resonance imaging with computational fluid dynamics. Ann Biomed Eng 31:42–52
Wentzel JJ, Corti R, Fayad ZA, Wisdom P, Macaluso F, Winkelman MO, Fuster V, Badimon JJ (2005) Does shear stress modulate both plaque progression and regression in the thoracic aorta? Human study using serial magnetic resonance imaging. J Am Coll Cardiol 45:846–854
Ramiro Moreno has been financed during the development of the project by the Medtronic Vascular (Santa Rosa, CA); the project OCFIA has been supported by the French National Agency for Research (ANR 07-CIS7-006-01). CINES (Montpellier) is acknowledged for CFD calculations.
The early results of the project have been presented twice at the ECR, in 2008 and in 2011. The first presentation was honoured with the first prize in the vascular topic, of which we are sincerely proud.
Electronic supplementary materials
Below is the link to the electronic supplementary material.
(AVI 3033 kb)
(AVI 6251 kb)
Tetrahedral moving mesh obtained after segmentation of the aortic volume and imposition of the wall movements according to the MRI cine imaging. The approach proposed with the presented method would yield more realistic conditions for the numerical simulations and could be a further step towards patient-specific computational flow modelling via a combination of MRI with CFD (see text) (AVI 11031 kb)
About this article
Cite this article
Midulla, M., Moreno, R., Baali, A. et al. Haemodynamic imaging of thoracic stent-grafts by computational fluid dynamics (CFD): presentation of a patient-specific method combining magnetic resonance imaging and numerical simulations. Eur Radiol 22, 2094–2102 (2012). https://doi.org/10.1007/s00330-012-2465-7
- Time-resolved 3D MRI