Combining Volumetric and Wall Shear Stress Analysis from CT to Assess Risk of Abdominal Aortic Aneurysm Progression.

Background Despite known limitations, the decision to operate on abdominal aortic aneurysm (AAA) is primarily on the basis of measurement of maximal aneurysm diameter. Purpose To identify volumetric and computational fluid dynamics parameters to predict AAAs that are likely to progress in size. Materials and Methods This study, part of a multicenter prospective registry (NCT01599533), included 126 patients with AAA. Patients were sorted into stable (≤10-mL increase in aneurysm volume) and progression (>10-mL increase in aneurysm volume) groups. Initial AAA characteristics of the derivation cohort were analyzed (maximal diameter and surface, thrombus and lumen volumes, maximal wall pressure, and wall shear stress [WSS]) to identify relevant parameters for a logistic regression model. Model and maximal diameter diagnostic performances were assessed in both cohorts and for AAAs smaller than 50 mm by using area under the receiver operating characteristic curve (AUC). Results Eighty-one patients were included (mean age, 73 years ± 7 years [standard deviation]; 78 men). The derivation and validation cohorts included, respectively, 50 and 31 participants. In the derivation cohort, there was higher mean lumen volume and lower mean WSS in the progression group compared with the stable group (60 mL ± 14 vs 46 mL ± 18 [P = .005] and 66% ± 6 vs 53% ± 9 [P = .02], respectively). Mean lumen volume and mean WSS at baseline were correlated to total volume growth (r = 0.47 [P = .002] and -0.42 [P = .006], respectively). In the derivation cohort, a regression model including lumen volume and WSS to predict aneurysm enlargement was superior to maximal diameter alone (AUC, 0.78 vs 0.52, respectively; P = .003); although no difference was found in the validation cohort (AUC, 0.79 vs 0.71, respectively; P = .51). For AAAs smaller than 50 mm, a regression model that included both baseline WSS and lumen volume performed better than maximal diameter (AUC, 0.79 vs 0.53, respectively; P = .01). Conclusion Combined analysis of lumen volume and wall shear stress was associated with enlargement of abdominal aortic aneurysms at 1 year, particularly in aneurysms smaller than 50 mm in diameter. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Mitsouras and Leach in this issue.

Reconciling PC-MRI and CFD: An in-vitro study.

Several well-resolved 4D Flow MRI acquisitions of an idealized rigid flow phantom featuring an aneurysm, a curved channel as well as a bifurcation were performed under pulsatile regime. The resulting hemodynamics were processed to remove MRI artifacts. Subsequently, they were compared with CFD predictions computed on the same flow domain, using an in-house high-order low dissipative flow solver. Results show that reaching a good agreement is not straightforward but requires proper treatments of both techniques. Several sources of discrepancies are highlighted and their impact on the final correlation evaluated. While a very poor correlation (r2 = 0.63) is found in the entire domain between raw MRI and CFD data, correlation as high as r2 = 0.97 is found when artifacts are removed by post-processing the MR data and down sampling the CFD results to match the MRI spatial and temporal resolutions. This work demonstrates that, in a well-controlled environment, both PC-MRI and CFD might bring reliable and correlated flow quantities when a proper methodology to reduce the errors is followed.

Influence of calcium on choline measurements by 1H MR spectroscopy of thigh muscles.

OBJECTIVE: To study the effects of calcium on the choline peak measurements with 1H MR spectroscopy. MATERIAL AND METHODS: The thigh muscles of two cadaveric specimens were prospectively evaluated on a 3 T MR unit before and after the injection of calcium carbonate (up to 0.4322 g). The choline peaks of 147 spectra from 10 different anatomic locations were quantitatively evaluated. The influence of the calcium concentration and its disposition with respect to the main magnetic field were considered. B0 phase maps were used to evaluate field inhomogeneities. RESULTS: The presence of calcium led to a 43 % underestimation of the choline peak and the choline concentration (p = 0.0002 and 0.0036). The mean choline concentrations before and after CaCO3 injection were 3.53 ± 1.72 mmol/l and 1.58 ± 0.63 mmol/l. The influence of calcium carbonate on the choline peak estimations was proportional to the calcium concentration. There was a significant position-dependent difference in the estimation of the choline peak amplitude (p < 0.0154). Calcium injection led to a measurable increase in field inhomogeneities. CONCLUSION: There was a significant underestimation of the choline peak amplitude and concentration in the presence of calcium, which might cause misinterpretations of MR spectra. KEY POINTS: The presence of calcium led to significant underestimation of choline measurements. The influence of calcium is dependent on its concentration and distribution. Quantitative MR spectroscopy of calcified tumours should be interpreted with caution.

Numerical simulation of time-resolved 3D phase-contrast magnetic resonance imaging.

A numerical approach is presented to efficiently simulate time-resolved 3D phase-contrast Magnetic resonance Imaging (or 4D Flow MRI) acquisitions under realistic flow conditions. The Navier-Stokes and Bloch equations are simultaneously solved with an Eulerian-Lagrangian formalism. A semi-analytic solution for the Bloch equations as well as a periodic particle seeding strategy are developed to reduce the computational cost. The velocity reconstruction pipeline is first validated by considering a Poiseuille flow configuration. The 4D Flow MRI simulation procedure is then applied to the flow within an in vitro flow phantom typical of the cardiovascular system. The simulated MR velocity images compare favorably to both the flow computed by solving the Navier-Stokes equations and experimental 4D Flow MRI measurements. A practical application is finally presented in which the MRI simulation framework is used to identify the origins of the MRI measurement errors.