Wall Stress and Geometry Measures in Electively Repaired Abdominal Aortic Aneurysms.
Wall Stress and Geometry Measures in Electively Repaired Abdominal Aortic Aneurysms.
复制标题
选择性修复腹主动脉瘤的壁应力和几何测量。
DOI：
10.1007/s10439-019-02261-w
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发表时间：
2019
影响因子：
3.8
通讯作者：
Finol,EnderA
中科院分区：
文献类型：
--
作者：
Wu,Wei;Rengarajan,Balaji;Thirugnanasambandam,Mirunalini;Parikh,Shalin;Gomez,Raymond;DeOliveira,Victor;Muluk,SatishC;Finol,EnderA
腹主动脉瘤（AAA）是一种以主动脉肾下段扩大为特征的血管性疾病。破裂的AAA可引起内出血，死亡率高，这就是为什么临床治疗的重点是预防动脉瘤破裂。AAA破裂风险是通过最大直径随时间的变化（即生长速率）或直径达到规定阈值来估计的。后者在大多数临床中心通常为5.5 cm，此时建议进行手术干预。虽然基于尺寸的标准适用于大多数在疾病早期诊断的患者，但众所周知，一些较小的AAA破裂或患者在最大直径为5.5 cm之前就出现症状。因此，主动脉壁的机械应力也可以作为基于生物力学的破裂风险评估策略的一个组成部分。在这项工作中，我们试图通过100个无症状、未破裂、选择性修复的AAA模型的样本空间来确定与壁面应力密切相关的几何特征。临床图像分割、体积网格划分以及每个AAA多达45个几何测量的量化使用内部Matlab脚本完成。有限元分析计算了第一个主应力分布，并由此计算了三个整体生物力学参数：峰值壁应力、第99百分位壁应力和空间平均壁应力。采用由Pearson’s相关矩阵、Bonferroni校正和线性回归组成的特征约简方法，进行多元逐步回归分析，找出与每个生物力学参数相关性最高的几何指标。我们的研究结果表明，当生成具有均匀壁厚的AAA模型时，壁应力可以通过几何指标预测，准确率高达94%，对于特定患者的非均匀壁厚AAA模型，准确率高达67%。这些壁应力的几何预测指标可以代替复杂的有限元模型，作为基于几何的破裂风险评估方案的一部分。
Abdominal aortic aneurysm (AAA) is a vascular disease characterized by the enlargement of the infrarenal segment of the aorta. A ruptured AAA can cause internal bleeding and carries a high mortality rate, which is why the clinical management of the disease is focused on preventing aneurysm rupture. AAA rupture risk is estimated by the change in maximum diameter over time (i.e., growth rate) or if the diameter reaches a prescribed threshold. The latter is typically 5.5 cm in most clinical centers, at which time surgical intervention is recommended. While a size-based criterion is suitable for most patients who are diagnosed at an early stage of the disease, it is well known that some small AAA rupture or patients become symptomatic prior to a maximum diameter of 5.5 cm. Consequently, the mechanical stress in the aortic wall can also be used as an integral component of a biomechanics-based rupture risk assessment strategy. In this work, we seek to identify geometric characteristics that correlate strongly with wall stress using a sample space of 100 asymptomatic, unruptured, electively repaired AAA models. The segmentation of the clinical images, volume meshing, and quantification of up to 45 geometric measures of each AAA were done using in-house Matlab scripts. Finite element analysis was performed to compute the first principal stress distributions from which three global biomechanical parameters were calculated: peak wall stress, 99th percentile wall stress and spatially averaged wall stress. Following a feature reduction approach consisting of Pearson’s correlation matrices with Bonferroni correction and linear regressions, a multivariate stepwise regression analysis was conducted to find the geometric measures most highly correlated with each of the biomechanical parameters. Our findings indicate that wall stress can be predicted by geometric indices with an accuracy of up to 94% when AAA models are generated with uniform wall thickness and up to 67% for patient specific, non-uniform wall thickness AAA. These geometric predictors of wall stress could be used in lieu of complex finite element models as part of a geometry-based protocol for rupture risk assessment.