Department of Mechanical Engineering, University of Texas at San Antonio, One UTSA Circle, San Antonio, TX, 78249, USA.
UTSA/UTHSA Joint Graduate Program in Biomedical Engineering, University of Texas at San Antonio, One UTSA Circle, San Antonio, TX, 78249, USA.
Ann Biomed Eng. 2019 Jul;47(7):1611-1625. doi: 10.1007/s10439-019-02261-w. Epub 2019 Apr 8.
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.
腹主动脉瘤 (AAA) 是一种血管疾病,其特征为肾下段主动脉的扩大。AAA 的破裂会导致内部出血,死亡率很高,这就是为什么该疾病的临床管理侧重于预防动脉瘤破裂。AAA 破裂风险通过随时间变化的最大直径变化(即增长率)或直径达到规定阈值来估计。后者在大多数临床中心通常为 5.5cm,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被诊断出的患者,但众所周知,一些小的 AAA 会破裂,或者患者在最大直径达到 5.5cm 之前出现症状。因此,主动脉壁的机械应力也可以用作基于生物力学的破裂风险评估策略的整体组成部分。在这项工作中,我们试图使用 100 个无症状、未破裂、择期修复的 AAA 模型的样本空间,确定与壁应力密切相关的几何特征。临床图像的分割、体积网格划分以及每个 AAA 的多达 45 个几何测量值的量化都是使用内部编写的 Matlab 脚本完成的。进行有限元分析以计算第一主应力分布,从该分布中计算出三个全局生物力学参数:峰值壁应力、第 99 百分位数壁应力和空间平均壁应力。通过具有 Bonferroni 校正和线性回归的 Pearson 相关矩阵的特征减少方法,进行了多元逐步回归分析,以找到与每个生物力学参数最相关的几何测量值。我们的研究结果表明,当使用均匀壁厚生成 AAA 模型时,壁应力可以通过几何指数以高达 94%的准确率进行预测,而对于患者特定的非均匀壁厚 AAA,则准确率高达 67%。这些壁应力的几何预测因子可以替代复杂的有限元模型,作为基于几何形状的破裂风险评估协议的一部分。