Applied Research Laboratory, The Pennsylvania State University, University Park, PA, USA.
Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, USA.
Biomech Model Mechanobiol. 2017 Dec;16(6):1957-1969. doi: 10.1007/s10237-017-0931-5. Epub 2017 Jun 27.
Embolus transport simulations are performed to investigate the dependence of inferior vena cava (IVC) filter embolus-trapping performance on IVC anatomy. Simulations are performed using a resolved two-way coupled computational fluid dynamics/six-degree-of-freedom approach. Three IVC geometries are studied: a straight-tube IVC, a patient-averaged IVC, and a patient-specific IVC reconstructed from medical imaging data. Additionally, two sizes of spherical emboli (3 and 5 mm in diameter) and two IVC orientations (supine and upright) are considered. The embolus-trapping efficiency of the IVC filter is quantified for each combination of IVC geometry, embolus size, and IVC orientation by performing 2560 individual simulations. The predicted embolus-trapping efficiencies of the IVC filter range from 10 to 100%, and IVC anatomy is found to have a significant influence on the efficiency results ([Formula: see text]). In the upright IVC orientation, greater secondary flow in the patient-specific IVC geometry decreases the filter embolus-trapping efficiency by 22-30 percentage points compared with the efficiencies predicted in the idealized straight-tube or patient-averaged IVCs. In a supine orientation, the embolus-trapping efficiency of the filter in the idealized IVCs decreases by 21-90 percentage points compared with the upright orientation. In contrast, the embolus-trapping efficiency is insensitive to IVC orientation in the patient-specific IVC. In summary, simulations predict that anatomical features of the IVC that are often neglected in the idealized models used for benchtop testing, such as iliac vein compression and anteroposterior curvature, generate secondary flow and mixing in the IVC and influence the embolus-trapping efficiency of IVC filters. Accordingly, inter-subject variability studies and additional embolus transport investigations that consider patient-specific IVC anatomy are recommended for future work.
进行了栓子输送模拟，以研究下腔静脉（IVC）滤器的栓子捕获性能对 IVC 解剖结构的依赖性。模拟使用解析的双向耦合计算流体动力学/六自由度方法进行。研究了三种 IVC 几何形状：直管 IVC、患者平均 IVC 和从医学成像数据重建的患者特异性 IVC。此外，还考虑了两种大小的球形栓子（直径为 3 和 5 毫米）和两种 IVC 方向（仰卧和直立）。通过进行 2560 次单独模拟，量化了 IVC 几何形状、栓子大小和 IVC 方向的每种组合的 IVC 滤器的栓子捕获效率。预测的 IVC 滤器的栓子捕获效率范围为 10%至 100%，发现 IVC 解剖结构对效率结果有重大影响（公式：见文本）。在直立的 IVC 方向，与理想化的直管或患者平均 IVC 相比，患者特异性 IVC 几何形状中的二次流增加了 22-30 个百分点，降低了滤器的栓子捕获效率。在仰卧位，理想 IVC 中的滤器的栓子捕获效率与直立位相比降低了 21-90 个百分点。相比之下，在患者特异性 IVC 中，栓子捕获效率对 IVC 方向不敏感。总之，模拟预测，通常在用于台架测试的理想化模型中被忽略的 IVC 的解剖特征，如髂静脉压迫和前后曲率，会在 IVC 中产生二次流和混合，并影响 IVC 滤器的栓子捕获效率。因此，建议进行考虑患者特异性 IVC 解剖结构的亚群间变异性研究和额外的栓子输送研究。
