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Tube-shaped blood vessel models that mimic their geometries and mechanical properties can deliver reliable and realistic behavioral information such as deformation and rupture during procedures such as insertion of medical devices. Thickness of vessel walls is an important parameter for fabricating the blood vessel models owing to their strong influence on the model behavior, especially during deformation. The dip-coating method is used to fabricate blood vessel models; however, non-uniform wall thicknesses are observed using this method. This study aimed at finding the characteristics of stereo “angular control dip-coating” (ACDC) system to develop a dip-coating system that can produce tubular models with uniformed wall thickness. The system developed here enables an observation of the substrate behavior from two different views. The conditions of dip-coating used in this study produce 1.36–1.82 mm in the maximum and 0.188–0.435 mm in minimum wall thickness and the fabricated walls cover the realistic range of carotid arterial dimensions. The characteristics of the ACDC system indicate that ACDC is effective for fabricating the uniform wall thickness particularly in the strong curved parts.

An existence probability atlas has been used for automatic labeling of cerebral arteries. However, the number of arteries varies frequently because of image quality and individual variation of the artery structure. To moderate the influence of number imbalance on labeling accuracy, we propose a new normalized atlas for automatic labeling of cerebral artery centerlines. The number of arteries, which was obtained from magnetic resonance angiography, varies from 11 to 46 among the artery sites. Based on the centerline and diameter, the arterial volume was reconstructed into a voxel space for each subject. After superimposing arteries from 46 subjects, three normalization methods were compared: dividing by the number of subjects (N), by N and the arterial length (L), and by N and the arterial volume (V). To compare the labeling accuracy and precision, the summation of probability and labeling method was also used. The accuracy of all normalization methods was > 85% in all arteries. The precision improved in some parts, with the atlas normalized by N-L and by N-V. The use of N-L and N-V changed the relative value of the existence probability among the parts. Consequently, some normalization methods changed the tendency toward misclassification, which changed the precision.

Vertebrobasilar atherosclerosis is an arterial disease; without successful treatment, it has a mortality rate approximately 80%–95%. Thus, predicting risk factors of vertebrobasilar atherosclerosis is of utmost importance. Previous studies have demonstrated that wall shear stress (WSS) contributes to atherosclerosis. In addition, geometry and WSS are correlated. The present study focuses on the description of equation using detailed relationship between arterial geometry and WSS in the vertebrobasilar system (VBS); magnetic resonance (MR) imaging with computational fluid dynamics (CFD) was used for the analysis. Using constructed patient-specific models, WSS of basilar arteries (BAs) was calculated and then analyzed with morphological parameters. According to the statistical results, both the area and curvature of BAs are associated with WSS. Based on the relations, a liner fitted equation can be proposed. As this study is underway, more precise evaluation of the correlation between morphology and fluid shear stress could help predict risk factors and select treatment methods for this arterial disease.