CFD validation using in-vitro MRI velocity data - Methods for data matching and CFD error quantification.

Predicting blood flow velocities in patient-specific geometries with Computational Fluid Dynamics (CFD) can provide additional data for diagnosis and treatment planning but the solution can be inaccurate. Therefore, it is crucial to understand the simulation errors and calibrate the numerical model. In-vitro velocity-encoded MRI is a versatile tool to validate CFD. The comparison between CFD and in-vitro MRI velocity data, and the analysis of the simulation error are the objectives of this study. A three-step routine is presented to validate medical CFD data. First, a properly scaled model of the patient-specific geometry is fabricated to achieve high relative resolution in the MRI experiment. Second, the measured flow geometry is matched with the CFD data using one of two algorithms, Coherent Point Drift and Iterative Closest Point. The aligned data sets are then interpolated onto a common grid to enable a point-to-point comparison. Third, the global and local deviations between CFD and MRI velocity data are calculated using different algorithms to reliably estimate the simulation error. The routine is successfully tested with a patient-specific model of a cerebral aneurysm. In conclusion, the methods presented here provide a framework for CFD validation using in-vitro MRI velocity data.

Impact of strut dimensions and vessel caliber on thrombosis risk of bioresorbable scaffolds using hemodynamic metrics.

Bioresorbable scaffolds (BRS) promise to be the treatment of choice for stenosed coronary vessels. But higher thrombosis risk found in current clinical studies limits the expectations. Three hemodynamic metrics are introduced to evaluate the thrombosis risk of coronary stents/scaffolds using transient computational fluid dynamics (CFD). The principal phenomena are platelet activation and effective diffusion (platelet shear number, PSN), convective platelet transport (platelet convection number, PCN) and platelet aggregation (platelet aggregation number, PAN) were taken into consideration. In the present study, two different stent designs (thick-strut vs. thin-strut design) positioned in small- and medium-sized vessels (reference vessel diameter, RVD=2.25 mm vs. 2.70 mm) were analyzed. In both vessel models, the thick-strut design induced higher PSN, PCN and PAN values than the thin-strut design (thick-strut vs. thin-strut: PSN=2.92/2.19 and 0.54/0.30; PCN=3.14/1.15 and 2.08/0.43; PAN: 14.76/8.19 and 20.03/10.18 for RVD=2.25 mm and 2.70 mm). PSN and PCN are increased by the reduction of the vessel size (PSN: RVD=2.25 mm vs. 2.70 mm=5.41 and 7.30; PCN: RVD=2.25 mm vs. 2.70 mm=1.51 and 2.67 for thick-strut and thin-strut designs). The results suggest that bulky stents implanted in small caliber vessels may substantially increase the thrombosis risk. Moreover, sensitivity analyses imply that PSN is mostly influenced by vessel size (lesion-related factor), whereas PCN and PAN sensitively respond to strut-thickness (device-related factor).