<p>Although the blood flow velocity in a left ventricle (LV) has been considered to be sufficiently fast to prevent thrombus formation, internal wall structures, such as trabeculae carneae (TC) and papillary muscle, recently received attention as possible causes of reduced near-wall blood flow. As a fundamental consideration of this problem, this study established a method for constructing an unsteady LV model from magnetic resonance (MR) images and investigated the effect of a few simplified TC structures on the blood flow in the model. The LV model at arbitrary time steps was constructed by deforming a computational mesh generated from MR images at a reference time step. The validity of the proposed construction scheme was confirmed by comparison with the configuration of an LV model extracted from MR images. Numerical analysis was performed for the unsteady blood flow in LV models with and without two simplified TC structures. The flow field in the model with the internal structure differed from that in the model without the internal structure near the wall, and flow separation caused by the internal structure decreased wall shear stress on the rear of the internal structure. The computational results provide fundamental information for the complex interaction between the internal structures and the blood flow in an LV.</p> <div style="text-align:center;"> </div>

Keywords

Heart thrombus, Magnetic resonance imaging, Computational fluid dynamics, Trabeculae carneae, Wall shear stress

Paper information

Tomomi YAMADA, Toshiyuki HAYASE, Suguru MIYAUCHI, Kenichi FUNAMOTO, “Numerical analysis of the effect of trabeculae carneae models on blood flow in a left ventricle model constructed from magnetic resonance images”, Journal of Biomechanical Science and Engineering, Vol.13, No.2 (2018), p.17-00597. doi:10.1299/jbse.17-00597. Final Version Released on May 18, 2018, Advance Publication Released on February 02, 2018.

Mechanisms of development, growth, and rupture of a cerebral aneurysm have been studied by computational fluid dynamics (CFD), calculating hemodynamic parameters, such as wall shear stress, oscillatory shear index (OSI), and relative residence time (RRT). It is well known that the upstream velocity profile and upstream vessel shape influence the computational results. However, few studies have dealt with cases involving a bifurcation upstream of a cerebral aneurysm. Furthermore, the fluid-dynamic effects of multiple structural elements of upstream vessel shape, such as a bifurcation and a bend, on the results of CFD remain unknown. The purpose of this study was to elucidate the fluid-dynamic effects of multiple structural elements of upstream vessel shape such as bifurcation and bend on blood flow and hemodynamic parameters inside an aneurysm. Computations were performed for blood flow in a cerebral aneurysm with upstream sequential elements of a bifurcation, a bend, and a straight section, using four models with different upstream boundaries, i.e., before the bifurcation, after the bifurcation before the bend, after the bend, and after the straight section just before the cerebral aneurysm. The results were compared to elucidate the effect of each upstream structural element on the blood flow and hemodynamic parameters in the cerebral aneurysm. Differences in OSI and RRT resulting from changes in the velocity distribution were observed locally in the aneurysm between the models. It was also found that the effect of the bifurcation on the velocity distribution was greater than that of the bend.

Keywords

Hemodynamics, Cerebral aneurysm, Computational fluid dynamics, Upstream boundary, Hemodynamic parameters

Paper information

Daichi SUZUKI, Kenichi FUNAMOTO, Shin-ichiro SUGIYAMA, Toshiyuki HAYASE, Suguru MIYAUCHI, Teiji TOMINAGA, “Effects of upstream bifurcation and bend on the blood flow in a cerebral aneurysm”, Journal of Biomechanical Science and Engineering, Vol.12, No.4 (2017), p.17-00189. doi:10.1299/jbse.17-00189. Final Version Released on September 15, 2017, Advance Publication Released on August 25, 2017.