Aortic dissections, which split the aorta into a true lumen (TL) and a false lumen (FL), represent a serious medical condition, affecting otherwise healthy young people with an incidence between 5,000–10,000 cases per year in the United States and 3000 in Europe [1]. A recent study of the outcome of acute type III/ Stanford B aortic dissections (dissections confined to the descending aorta, B-AD) revealed that the long-term prognosis after hospital discharge of patients with B-AD is heterogeneous, with reported survival rates ranging from 56 to 92% at 1 year and from 48 to 82% at 5 years [2]. A partially thrombosed FL, results in a 2.7-fold increase in risk of death [3]. In a recent ex-vitro study, Tasi et al. investigated a chronic aortic dissection in three models [4]. The largest FL diastolic pressure was observed for the model simulating patients with partial false lumen thrombosis and occlusion of the distal entry tear. This study demonstrated that pressure differences between TL and FL are dependent on the geometry of the particular aortic dissection and the location and size of entry tears. A computational fluid dynamics (CFD) study on the effects of entry and exit tear coverage in B-AD based on a patient-derived geometry reported similar results [5]: In particular, occlusion of the exit tear caused increase FL pressure. Simulating thoracic endovascular repair (TEVAR) by occluding the entrance tear depressurized the FL. The capability of CFD to virtually simulate surgical interventions makes it an appealing method for use in pre-surgical planning. For general acceptance however, validation of the simulated results is needed. Catheter measurements of the pressures in the TL and FL are feasible but not very practicable as insertion of a catheter in the FL through the entry or exit tear bears unjustifiable risk to the patient. More recently, 7D phase contrast magnetic resonance imaging (pcMRI) methods (3 spatial directions, 3 velocity directions and time equal 7 dimensions) have been introduced that allow the acquisition of the 3D velocity field at several time points in the cardiac cycle, thereby providing information that can be directly compared with the velocity field simulated with CFD. Due to the large duration of the image acquisition, compromises in temporal and spatial resolution are made which need to be considered when performing such a comparison. Here we present a method based on interpolating the simulated velocity field onto a structured grid employing direct interpolation and spatial Fourier Fast Transformation (FFT) to replicate artifacts as they are present in the 7D pcMRI data. The interpolated velocity components are the then qualitatively compared using image correlation analysis.

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