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一种全面的颅内动脉瘤线圈放置数值方法:数学建模和计算机模拟分类。

A comprehensive numerical approach to coil placement in cerebral aneurysms: mathematical modeling and in silico occlusion classification.

机构信息

Department of Mathematics, Technical University of Munich, Boltzmannstr. 3/III, 85748, Garching b. München, Germany.

出版信息

Biomech Model Mechanobiol. 2024 Dec;23(6):2063-2089. doi: 10.1007/s10237-024-01882-y. Epub 2024 Aug 20.

DOI:10.1007/s10237-024-01882-y
PMID:39162857
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11554728/
Abstract

Endovascular coil embolization is one of the primary treatment techniques for cerebral aneurysms. Although it is a well-established and minimally invasive method, it bears the risk of suboptimal coil placement which can lead to incomplete occlusion of the aneurysm possibly causing recurrence. One of the key features of coils is that they have an imprinted natural shape supporting the fixation within the aneurysm. For the spatial discretization, our mathematical coil model is based on the discrete elastic rod model which results in a dimension-reduced 1D system of differential equations. We include bending and twisting responses to account for the coils natural curvature and allow for the placement of several coils having different material parameters. Collisions between coil segments and the aneurysm wall are handled by an efficient contact algorithm that relies on an octree based collision detection. In time, we use a standard symplectic semi-implicit Euler time stepping method. Our model can be easily incorporated into blood flow simulations of embolized aneurysms. In order to differentiate optimal from suboptimal placements, we employ a suitable in silico Raymond-Roy-type occlusion classification and measure the local packing density in the aneurysm at its neck, wall region and core. We investigate the impact of uncertainties in the coil parameters and embolization procedure. To this end, we vary the position and the angle of insertion of the micro-catheter, and approximate the local packing density distributions by evaluating sample statistics.

摘要

血管内线圈栓塞术是治疗脑动脉瘤的主要方法之一。尽管它是一种成熟的微创方法,但存在线圈放置不理想的风险,这可能导致动脉瘤不完全闭塞,从而导致复发。线圈的一个关键特征是它们具有固有形状的印痕,有助于在动脉瘤内固定。对于空间离散化,我们的数学线圈模型基于离散弹性杆模型,这导致了降维的 1D 微分方程组系统。我们包括弯曲和扭转响应,以考虑线圈的自然曲率,并允许放置具有不同材料参数的多个线圈。线圈段与动脉瘤壁之间的碰撞通过依赖于八叉树的碰撞检测的高效接触算法来处理。随着时间的推移,我们使用标准的辛半隐式 Euler 时间步长方法。我们的模型可以很容易地纳入栓塞动脉瘤的血流模拟中。为了区分最佳和次佳放置,我们采用了合适的基于 Raynaud-Roy 类型的仿真闭塞分类,并测量了动脉瘤颈部、壁区和核心处的局部堆积密度。我们研究了线圈参数和栓塞过程中的不确定性的影响。为此,我们改变微导管的位置和插入角度,并通过评估样本统计来近似局部堆积密度分布。

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Stiff coils enhance shape retention and pressure resistance in an aneurysm model even at low volume.在动脉瘤模型中,即使在低容量情况下,硬弹簧圈也能增强形状保持力和抗压力。
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