Wall shear stress estimation in the aorta: Impact of wall motion, spatiotemporal resolution, and phase noise.

BACKGROUND: Wall shear stress (WSS) presents an important parameter for assessing blood flow characteristics and evaluating flow-mediated lesions in the aorta. PURPOSE: To investigate the robustness of WSS and oscillatory shear index (OSI) estimation based on 4D flow MRI against vessel wall motion, spatiotemporal resolution, and velocity encoding (VENC). STUDY TYPE: Simulated and prospective. POPULATION: Synthetic 4D flow MRI data of the aorta, simulated using the Lattice-Boltzmann method; in vivo 4D flow MRI data of the aorta from healthy volunteers (n = 11) and patients with congenital heart defects (n = 17). FIELD STRENGTH/SEQUENCE: 1.5T; 4D flow MRI with PEAK-GRAPPA acceleration and prospective electrocardiogram triggering. ASSESSMENT: Predicated upon 3D cubic B-splines interpolation of the image velocity field, WSS was estimated in mid-systole, early-diastole, and late-diastole and OSI was derived. We assessed the impact of spatiotemporal resolution and phase noise, and compared results based on tracked-using deformable registration-and static vessel wall location. STATISTICAL TESTS: Bland-Altman analysis to assess WSS/OSI differences; Hausdorff distance (HD) to assess wall motion; and Pearson's correlation coefficient (PCC) to assess correlation of HD with WSS. RESULTS: Synthetic data results show systematic over-/underestimation of WSS when different spatial resolution (mean ± 1.96 SD up to -0.24 ± 0.40 N/m2 and 0.5 ± 1.38 N/m2 for 8-fold and 27-fold voxel size, respectively) and VENC-depending phase noise (mean ± 1.96 SD up to 0.31 ± 0.12 N/m2 and 0.94 ± 0.28 N/m2 for 2-fold and 4-fold VENC increase, respectively) are given. Neglecting wall motion when defining the vessel wall perturbs WSS estimates to a considerable extent (1.96 SD up to 1.21 N/m2 ) without systematic over-/underestimation (Bland-Altman mean range -0.06 to 0.05). DATA CONCLUSION: In addition to sufficient spatial resolution and velocity to noise ratio, accurate tracking of the vessel wall is essential for reliable image-based WSS estimation and should not be neglected if wall motion is present. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Determination of aortic stiffness using 4D flow cardiovascular magnetic resonance - a population-based study.

BACKGROUND: Increased aortic stiffness is an independent predictor of cardiovascular disease. Optimal measurement is highly beneficial for the detection of atherosclerosis and the management of patients at risk. Thus, it was our purpose to selectively measure aortic stiffness using a novel imaging method and to provide reference values from a population-based study. METHODS: One hundred twenty six inhabitants of Freiburg, Germany, between 20 and 80 years prospectively underwent 3 Tesla cardiovascular magnetic resonance (CMR) of the thoracic aorta. 4D flow CMR (spatial/temporal resolution 2mm3/20ms) was executed to calculate aortic pulse wave velocity (PWV) in m/s using dedicated software. In addition, we calculated distensibility coefficients (DC) using 2D CINE CMR imaging of the ascending (AAo) and descending aorta (DAo). Segmental aortic diameter and thickness of aortic plaques were determined by 3D T1 weighted CMR (spatial resolution 1mm3). RESULTS: PWV increased from 4.93 ± 0.54 m/s in 20-30 year-old to 8.06 ± 1.03 m/s in 70-80 year-old subjects. PWV was significantly lower in women compared to men (p < 0.0001). Increased blood pressure (systolic r = 0.36, p < 0.0001; diastolic r = 0.33, p = 0.0001; mean arterial pressure r = 0.37, p < 0.0001) correlated with PWV after adjustment for age and gender. Finally, PWV increased with increasing diameter of the aorta (ascending aorta r = 0.20, p = 0.026; aortic arch r = 0.24, p = 0.009; descending aorta r = 0.26, p = 0.004). Correlation of PWV and DC of the AAo and DAo or the mean of both was high (r = 0.69, r = 0.68, r = 0.73; p < 0.001). CONCLUSIONS: 4D flow CMR was successfully applied to calculate aortic PWV and thus aortic stiffness. Findings showed a high correlation with distensibility coefficients representing local compliance of the aorta. Our novel method and reference data for PWV may provide a reliable biomarker for the identification of patients with underlying cardiovascular disease and optimal guidance of future treatment in studies or clinical routine.

MRI-based computational hemodynamics in patients with aortic coarctation using the lattice Boltzmann methods: Clinical validation study.

PURPOSE: To introduce a scheme based on a recent technique in computational hemodynamics, known as the lattice Boltzmann methods (LBM), to noninvasively measure pressure gradients in patients with a coarctation of the aorta (CoA). To provide evidence on the accuracy of the proposed scheme, the computed pressure drop values are compared against those obtained using the reference standard method of catheterization. MATERIALS AND METHODS: Pre- and posttreatment LBM-based pressure gradients for 12 patients with CoA were simulated for the time point of peak systole using the open source library OpenLB. Four-dimensional (4D) flow-sensitive phase-contrast MRI at 1.5 Tesla was used to acquire flow and to setup the simulation. The vascular geometry was reconstructed using 3D whole-heart MRI. Patients underwent pre- and postinterventional pressure catheterization as a reference standard. RESULTS: There is a significant linear correlation between the pretreatment catheter pressure drops and those computed based on the LBM simulation, r=.85, P<.001. The bias was -0.58 ± 4.1 mmHg and was not significant ( P=0.64) with a 95% confidence interval (CI) of -3.22 to 2.06. For the posttreatment results, the bias was larger and at -2.54 ± 3.53 mmHg with a 95% CI of -0.17 to -4.91 mmHg. CONCLUSION: The results indicate a reasonable agreement between the simulation results and the catheter measurements. LBM-based computational hemodynamics can be considered as an alternative to more traditional computational fluid dynamics schemes for noninvasive pressure calculations and can assist in diagnosis and therapy planning. LEVEL OF EVIDENCE: 3 J. Magn. Reson. Imaging 2017;45:139-146.

Quantification of aortic stiffness in stroke patients using 4D flow MRI in comparison with transesophageal echocardiography.

To quantify stiffness of the descending aorta (DAo) in stroke patients using 4D flow MRI and compare results with transesophageal echocardiography (TEE). 48 acute stroke patients undergoing 4D flow MRI and TEE were included. Intima-media-thickness (IMT) was measured in the DAo and the aorta was scrutinized for atherosclerotic plaques using TEE. Stiffness of the DAo was determined by (a) 4D flow MRI at 3 T by calculating pulse wave velocity (PWV) and by (b) TEE calculating arterial strain, stiffness index, and distensibility coefficient. Mean IMT was 1.43 ± 1.75. 7 (14.6%) subjects had no sign of atherosclerosis, 10 (20.8%) had IMT-thickening or plaques < 4 mm, and 31 (66.7%) had at least one large and/or complex plaque in the aorta. Increased IMT significantly correlated (p < 0.001) with increased DAo stiffness in MRI (PWV r = 0.66) and in TEE (strain r = 0.57, stiffness index r = 0.64, distensibility coefficient r = 0.57). Patients with at least IMT-thickening had significantly higher stiffness values compared to patients without atherosclerosis. However, no difference was observed between patients with plaques < 4 mm and patients with plaques ≥ 4 mm. PWV and TEE parameters of stiffness correlated significantly [strain (r = - 0.36; p = 0.011), stiffness index (r = 0.51; p = 0.002), and distensibility coefficient (r = - 0.59; p < 0.001)]. 4D flow MRI and TEE-based parameters of aortic stiffness were associated with markers of atherosclerosis such as IMT-thickness and presence of plaques. We believe that 4D flow MRI is a promising tool for future studies of aortic atherosclerosis, due to its longer coverage of the aorta and non-invasiveness.