183 Computational Fluid Dynamics – A Patient-Specific Assessment of The Thoracic Aorta. (3rd June 2016)

• Record Type: Journal Article
• Authors: Youssefi, Pouya; Gomez, Alberto; He, Taigang; Anderson, Lisa; Bunce, Nick; Sharma, Rajan; Figueroa, Alberto; Jahangiri, Marjan
• Is Part Of: Heart. Volume 102(2016)Supplement 6
• Page Start: A126
• Page End: A127
• Publication Date: 2016-06-03
• Subjects: Computational Fluid Dynamics -- Wall Shear Stress -- Aorta; Heart -- Diseases -- Treatment -- Periodicals; Cardiology -- Periodicals; 616.12
• DOI: 10.1136/heartjnl-2016-309890.183
• Languages: English
• ISSNs: 1355-6037

Abstract

Abstract : Introduction: Current intervention criteria for the thoracic aorta concentrate on size. However, the complexity of aortic disease is not fully exposed by aortic dimensions alone, and morbidity or mortality can occur before intervention thresholds are reached. Computational fluid dynamics (CFD) is a non-invasive approach to quantify haemodynamics in assessment of aneurysms and rupture risk. Wall shear stress (WSS) measuring viscous shearing forces on the endothelium, and oscillatory shear index (OSI) measuring disturbed flow, are a pathophysiological stimulus to gene expression, extracellular-matrix remodelling, and aortic wall thinning. We aimed to evaluate the efficacy of a new patient-specific approach to CFD of the thoracic aorta, and its functional and haemodynamic indices in assessment of aortic pathology. Methods: 45 subjects were divided into 5 groups: Volunteers, AR-TAV, AS-TAV, AS-BAV(RL), AS-BAV(RN), where AR=aortic regurgitation, AS=aortic stenosis, TAV=tricuspid aortic valve, BAV=bicuspid aortic valve, RL=right-left cusp fusion, RN=right-non cusp fusion. Subjects underwent magnetic resonance angiography, with phase-contrast MRI at the sino-tubular junction to define patient-specific inflow velocity profiles. Three-dimensional aorta models were constructed from MRA data and discretized to form a finite element mesh. The 3D velocity profile from PC-MRI was mapped onto the inflow mesh, allowing prescription of patient-specific inflow boundary conditions. Blood pressure, cardiac output, and cross-sectional area of each vessel were processed to assign outflow boundary conditions to arch vessels and descending aorta. Results: CFD enabled measurement of WSS throughout the thoracic aorta. WSS was significantly elevated in aortic stenosis, highest in AS-BAV(RN) (mean WSS=37.1 ± 4.0 dyn/cm 2, compared to 19.9 ± 1.9 dyn/cm 2 for AS-BAV(RL), 25.7 ± 1.2 dyn/cm 2 in AS-TAV, 12.3 ± 3.4 dyn/cm 2 in AR-TAV, and 9.9 ± 5.4 dyn/cm 2 in healthy volunteers, p < 0.05). Aortic stenosis patients displayed asymmetrical WSS distributions, the greater curvature experiencing the highest WSS. OSI was lower in bicuspid right-non fusion (p < 0.05). Eccentricity of flow was higher in bicuspid patients (Flowasymmetry = 84.1 ± 5.4%, compared to 28.1 ± 21.5 for tricuspids, p < 0.05). Helicity of flow was assessed by the Helical Flow Index (HFI), which was higher in bicuspid right-left fusion (HFIsystole = 0.39 ± 0.04, compared to 0.28 ± 0.03 for all others, p < 0.05). Conclusions: BAV displays eccentric flow with high helicity. Presence of AS, particularly in BAV-RN led to higher WSS and lower OSI in the greater curvature of the ascending aorta. Patient-specific CFD provides non-invasive functional assessment of the thoracic aorta, and enables development of a personalized approach to diagnosis and management of aortic disease beyond traditional guidelines.