Mechanics & High Performance Computing Group, Technische Universität München, Parkring 35, 85748, Garching b. München, Germany.
AdjuCor GmbH, Neumarkter Str. 18, 81673, München, Germany.
Int J Numer Method Biomed Eng. 2019 Oct;35(10):e3233. doi: 10.1002/cnm.3233. Epub 2019 Sep 1.
Advances in ventricular assist device (VAD) technology for the treatment of end-stage congestive heart failure (CHF) are needed to cope with the increasing numbers of patients that cannot be provided with donor hearts for transplantation. We develop and investigate a novel extravascular VAD technology that provides biventricular, epicardial pressure support for the failing heart. This novel VAD concept avoids blood contact that is accompanied with typical complications such as coagulation and infections. To date, in vivo porcine model results with a prototype of the implant exist, further studies to improve the implant's performance and promote its applicability in humans are needed. In this contribution, we present a personalised functional digital twin of the heart, the vascular system, and the novel VAD technology in terms of a calibrated, customized computational model. The calibration procedure is based on patient-specific measurements and is performed by solving an inverse problem. This in silico model is able to (a) confirm in vivo experimental data, (b) predict healthy and pathologic ventricular function, and (c) assess the beneficial impact of the novel VAD concept to a high level of fidelity. The model shows very good agreement with in vivo data and reliably predicts increases in stroke volume and left ventricular pressure with increasing ventricular support. Furthermore, the digital twin allows insight into quantities that are poorly or not at all amenable in any experimental setup. Conclusively, the model's ability to link integral hemodynamic variables to local tissue mechanical deformation makes it a highly valuable tool for the dimensioning of novel VAD technologies and future treatment strategies in heart failure. The presented in silico twin enhances in vivo studies by facilitating the accessibility and increasing the range of quantities of interest. Because of its flexibility in the assessment of design variants and optimization loops, it may substantially contribute to a reduction of the amount of animal experiments in this and similar settings.
需要在心室辅助装置 (VAD) 技术方面取得进展，以治疗终末期充血性心力衰竭 (CHF)，因为有越来越多的患者无法获得供移植的供体心脏。我们开发并研究了一种新型的血管外 VAD 技术，为衰竭的心脏提供双心室、心外膜压力支持。这种新型 VAD 概念避免了血液接触，而血液接触会伴随典型的并发症，如凝血和感染。迄今为止，该植入物的体内猪模型结果已经存在，需要进一步的研究来提高植入物的性能并促进其在人类中的适用性。在本研究中，我们提出了一种基于心脏、血管系统和新型 VAD 技术的个性化功能数字孪生体，它是一个经过校准的定制计算模型。校准过程基于患者的具体测量值，并通过求解反问题来完成。该计算模型能够：(a) 确认体内实验数据；(b) 预测健康和病理心室功能；(c) 高度准确地评估新型 VAD 概念的有益影响。该模型与体内数据非常吻合，能够可靠地预测随着心室支持的增加，心排量和左心室压力的增加。此外，该数字孪生体还允许深入了解在任何实验设置中都难以或无法获得的数量。总之，该模型将整体血液动力学变量与局部组织机械变形联系起来的能力使其成为一种非常有价值的工具，可用于新型 VAD 技术的设计和心力衰竭的未来治疗策略。该数字孪生体通过提高可访问性和增加感兴趣的数量范围，增强了体内研究。由于其在评估设计变体和优化循环方面的灵活性，它可能会大大减少在这种情况下和类似情况下进行动物实验的数量。
