University Grenoble Alpes, CNRS, Grenoble INP, 3SR, Grenoble, France.
Department of Mechanical Engineering, University of Washington, Seattle, WA, USA.
Ann Biomed Eng. 2023 Dec;51(12):2785-2801. doi: 10.1007/s10439-023-03340-9. Epub 2023 Aug 19.
Modeling blood flow in aneurysms treated with coils could be used to understand the complete embolization of the aneurysm, through thrombus formation that fills the entire sac. Modeling of the endovascular coil mass as a porous medium is a technique that allows for study of aneurysm hemodynamics, efficiently for patient-specific treatment outcome predictions. Models in the literature use mean porosity of coils in the aneurysmal volume, proving inadequate for outcome prediction. However, models that consider heterogeneous porosity distribution have shown more accurate hemodynamics. We recently published the porous crown model, considering the heterogeneous coil mass distribution, validated on two patients. This study aims (i) to validate the porous crown model for a larger cohort (eight patients), and (ii) to propose a porous medium model translatable to clinical practice in treatment planning. We analyzed the porosity distribution of the endovascular coils deployed inside the cerebral aneurysm phantoms of eight patients using 3D x-ray synchrotron images. The permeability and inertial factor of the porous crown model are calculated using previously published methodology. We propose a new "bilinear" porous model, that uses the same hypothesis, but the permeability and inertial factor can be defined from just basic information available in the neuro-suite, i.e., the aneurysmal sac volume and the coil volume fraction targeted by the neurosurgeon. These two models are compared to the coil-resolved simulations, considered as the gold standard. The results show that both the porous crown model and the bilinear model produce similarly accurate hemodynamics in the aneurysm. The error in the standard (mean porosity) porous model is 66%, whereas the error of the bilinear model is 26%, compared to the coil-resolved. The bilinear model is promising as a means of treatment outcome prediction at time of intervention.
对使用线圈治疗的动脉瘤中的血流进行建模,可以通过血栓形成来理解动脉瘤的完全栓塞,血栓充满整个囊腔。将血管内线圈团模拟为多孔介质是一种技术,可用于研究动脉瘤血液动力学,有效地预测针对特定患者的治疗效果。文献中的模型使用动脉瘤体积中线圈的平均孔隙率,这对于预测结果来说是不够的。但是,考虑到异质孔隙率分布的模型已经显示出更准确的血液动力学。我们最近发表了多孔冠模型,考虑了异质线圈质量分布,在两名患者中进行了验证。本研究旨在(i)对更大的队列(八名患者)验证多孔冠模型,(ii)提出一种可用于治疗计划的临床实践中的多孔介质模型。我们使用 3D 同步加速器 X 射线图像分析了在 8 名患者的脑动脉瘤模型中部署的血管内线圈的孔隙率分布。多孔冠模型的渗透率和惯性因子使用先前发表的方法进行计算。我们提出了一种新的“双线性”多孔模型,它使用相同的假设,但渗透率和惯性因子可以根据神经套房中可用的基本信息来定义,即动脉瘤囊体积和神经外科医生靶向的线圈体积分数。将这两种模型与被认为是金标准的线圈解析模拟进行比较。结果表明,多孔冠模型和双线性模型在动脉瘤中均产生类似准确的血液动力学。与线圈解析相比,标准(平均孔隙率)多孔模型的误差为 66%,而双线性模型的误差为 26%。双线性模型有望成为介入治疗时治疗效果预测的一种手段。