Chiu Peter, Lee Hong-Pyo, Dalal Alex R, Koyano Tiffany, Nguyen Marie, Connolly Andrew J, Chaudhuri Ovijit, Fischbein Michael P
Department of Cardiothoracic Surgery, Stanford University School of Medicine, Stanford University, Stanford, Calif.
Department of Mechanical Engineering, Stanford University, Stanford, Calif.
JVS Vasc Sci. 2021 Oct 8;2:235-246. doi: 10.1016/j.jvssci.2021.08.003. eCollection 2021.
Current guidelines for prophylactic replacement of the thoracic aorta, primarily based on size alone, may not be adequate in identifying patients at risk for either progression of disease or aortic catastrophe. We undertook the current study to determine whether the mechanical properties of the aorta might be able to predict aneurysmal dilatation of the aorta using a clinical database and benchtop mechanical testing of human aortic tissue.
Using over 400 samples from 31 patients, mechanical properties were studied in (a) normal aorta and then (b) between normal and diseased aorta using linear mixed-effects models. A machine learning technique was used to predict aortic growth rate over time using mechanical properties and baseline clinical characteristics.
Healthy aortic tissue under in vivo loading conditions, after accounting for aortic segment location, had lower longitudinal elastic modulus compared with circumferential elastic modulus: -166.8 kPa (95% confidence interval [CI]: -210.8 to -122.7, < .001). Fracture toughness was also lower in the longitudinal vs circumferential direction: -201.2 J/m (95% CI: -272.9 to -129.5, < .001). Finally, relative strain was lower in the longitudinal direction compared with the circumferential direction: -0.01 (95% CI: -0.02 to -0.004, = .002). Patients with diseased aorta, after accounting for segment location and sample direction, had decreased toughness compared with normal aorta, -431.7 J/m (95% CI: -628.6 to -234.8, < .001), and increased relative strain, 0.09 (95% CI: 0.04 to 0.14, = .003).
Increasing relative strain was identified as a novel independent predictor of aneurysmal degeneration. Noninvasive measurement of relative strain may aid in the identification and monitoring of patients at risk for aneurysmal degeneration. (JVS-Vascular Science 2021;2:1-12.).
Aortic aneurysm surveillance and prophylactic surgical recommendations are based on computed tomographic angiogram aortic dimensions and growth rate measurements. However, aortic catastrophes may occur at small sizes, confounding current risk stratification models. Herein, we report that increasing aortic relative strain, that is, greater distensibility, is associated with growth over time, thus potentially identifying patients at risk for dissection/rupture.
目前胸主动脉预防性置换的指南主要仅基于尺寸，可能不足以识别疾病进展或主动脉灾难风险的患者。我们进行了本研究，以确定使用临床数据库和人体主动脉组织的台式力学测试，主动脉的力学特性是否能够预测主动脉瘤样扩张。
使用来自31例患者的400多个样本，通过线性混合效应模型在（a）正常主动脉中，然后在（b）正常与病变主动脉之间研究力学特性。使用机器学习技术，利用力学特性和基线临床特征预测主动脉随时间的生长速率。
在考虑主动脉节段位置后，体内加载条件下的健康主动脉组织，其纵向弹性模量低于周向弹性模量：-166.8 kPa（95%置信区间[CI]：-210.8至-122.7，P<.001）。纵向的断裂韧性也低于周向：-201.2 J/m（95%CI：-272.9至-129.5，P<.001）。最后，纵向的相对应变低于周向：-0.01（95%CI：-0.02至-0.004，P=.002）。在考虑节段位置和样本方向后，病变主动脉患者与正常主动脉相比，韧性降低，为-431.7 J/m（95%CI：-628.6至-234.8，P<.001），相对应变增加，为0.09（95%CI：0.04至0.14，P=.003）。
相对应变增加被确定为动脉瘤退变的一种新的独立预测指标。相对应变的无创测量可能有助于识别和监测动脉瘤退变风险的患者。（《血管外科学杂志 - 血管科学》2021年；2：1 - 12）。
主动脉瘤监测和预防性手术建议基于计算机断层血管造影主动脉尺寸和生长速率测量。然而，主动脉灾难可能在较小尺寸时发生，使当前风险分层模型混淆。在此，我们报告主动脉相对应变增加，即更大的扩张性，与随时间的生长相关，从而可能识别有夹层/破裂风险的患者。
