Background:Progressive aortic valve disease has remained a persistent cause of concern in patients with left ventricular assist devices. Aortic incompetence (AI) is a known predictor of both mortality and readmissions in this patient population and remains a challenging clinical problem.Methods:Ten left ventricular assist device patients with de novo aortic regurgitation and 19 control left ventricular assist device patients were identified. Three-dimensional models of patients’ aortas were created from their computed tomography scans, following which large-scale patient-specific computational fluid dynamics simulations were performed with physiologically accurate boundary conditions using the SimVascular flow solver.Results:The spatial distributions of time-averaged wall shear stress and oscillatory shear index show no significant differences in the aortic root in patients with and without AI (mean difference, 0.67 dyne/cm² [95% CI, −0.51 to 1.85]; P=0.23). Oscillatory shear index was also not significantly different between both groups of patients (mean difference, 0.03 [95% CI, −0.07 to 0.019]; P=0.22). The localized wall shear stress on the leaflet tips was significantly higher in the AI group than the non-AI group (1.62 versus 1.35 dyne/cm²; mean difference [95% CI, 0.15–0.39]; P<0.001), whereas oscillatory shear index was not significantly different between both groups (95% CI, −0.009 to 0.001; P=0.17).Conclusions:Computational fluid dynamics serves a unique role in studying the hemodynamic features in left ventricular assist device patients where 4-dimensional magnetic resonance imaging remains unfeasible. Contrary to the widely accepted notions of highly disturbed flow, in this study, we demonstrate that the aortic root is a region of relatively stagnant flow. We further identified localized hemodynamic features in the aortic root that challenge our understanding of how AI develops in this patient population.

中文翻译：

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特定于患者的计算流体动力学揭示了可预测左心室辅助装置后主动脉瓣关闭不全的局部血流模式


背景：进行性主动脉瓣疾病仍然是使用左心室辅助装置的患者持续关注的一个问题。主动脉瓣关闭不全 (AI) 是该患者群体中死亡率和再入院的已知预测因素，并且仍然是一个具有挑战性的临床问题。方法：确定了 10 名患有新发主动脉瓣反流的左心室辅助装置患者和 19 名对照左心室辅助装置患者。根据计算机断层扫描创建患者主动脉的三维模型，然后使用 SimVascular 流解算器在生理学精确的边界条件下进行大规模患者特定的计算流体动力学模拟。结果：时间平均的空间分布壁剪切应力和振荡剪切指数显示，患有和不患有AI的患者的主动脉根部没有显着差异（平均差异，0.67 dyne/cm ² [95% CI，-0.51至1.85]； P = 0.23）。两组患者之间的振荡剪切指数也没有显着差异（平均差为 0.03 [95% CI，-0.07 至 0.019]； P = 0.22）。 AI 组小叶尖端的局部壁剪切应力显着高于非 AI 组（1.62 与 1.35 达因/cm ² ；平均差 [95% CI，0.15–0.39]； P <0 id=50> P = 0.17）。结论：计算流体动力学在研究左心室辅助装置患者的血流动力学特征方面发挥着独特的作用，而4维磁共振成像仍然不可行。与广泛接受的高度扰动的血流概念相反，在这项研究中，我们证明主动脉根部是血流相对停滞的区域。 我们进一步确定了主动脉根部的局部血流动力学特征，这挑战了我们对人工智能在该患者群体中如何发展的理解。