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Modulation of pressure overload in chronic animal and in vitro models to elucidate associated effects on hemodynamics and left ventricular plasticity

Modulation of pressure overload in chronic animal and in vitro models to elucidate associated effects on hemodynamics and left ventricular plasticity
调节慢性动物和体外模型中的压力超负荷,以阐明对血流动力学和左心室可塑性的相关影响
批准号:
10905164
负责人:
Ellen T. Roche
金额:
$36.15万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-09-01 至 2024-08-31

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中文摘要
翻译
项目摘要 心脏重构伴左心室顺应性丧失、充盈受损和舒张功能障碍, 继发于几种疾病,包括限制性心肌病和压力超负荷(即,主动脉 狭窄或高血压)。目前,尚无LV顺应性丧失的体外和体内模型 并且受损的填充是开发有效治疗的主要障碍。迄今为止, 存在LV顺应性丧失的生物力学体外模型,动物模型受到高死亡率的限制 速率和不能精细控制诱导压力过载的程度和动态。 由于缺乏可靠的左心室顺应性丧失和舒张功能障碍的动物模型, 了解这些条件的病理生理学。因此,没有可用的策略 治疗心脏舒张功能的潜在生物力学表现。缺乏洞察力 最佳干预计划,以靶向和逆转由于压力超负荷造成的不良重塑。 通过这个提议,我们的目标是利用可调动态机械植入物来创建疾病模型 的LV顺应性损失,并表征LV重塑过程的可塑性, 生物力学和血液动力学的观点,它们的进展和潜在的逆转。 我们最近开发了一种软机器人主动脉套管,以概括压力超负荷的急性血流动力学 在猪模型中。初步数据显示,我们可以重建压力超负荷的血流动力学, 使用软机器人工具在体外模型中受损的填充。在这里,我们的目标是重建慢性生物力学 以及LV顺应性丧失和继发于压力的充盈受损的血流动力学表现 超负荷与增强系统的传感和控制能力。具体而言,我们的目标是:(1)发展 心室顺应性压力超负荷损失的高保真度和患者特异性台式模型,以及 使用可调软机器人工具进行受损充盈;(2)通过 开发微创输送方法、MRI安全植入式系统和内置智能传感 用于闭环反馈控制以重建患者特异性疾病,以及(3)开发和评估临床 相关的慢性大型动物模型的心脏重塑由于压力超负荷的时间变化程度的 压力超负荷和评估疾病消退的可能性。 我们提出的工作将解决现有模型的局限性,以使研究的可逆性, 与慢性压力超负荷相关的重塑过程,提供了对 病理生理机制,指导干预的最佳类型和时机,并最终服务于 作为可调、高保真和患者特定的平台,用于培训、器械开发和 血流动力学结果预测用于临床介入计划。
英文摘要
PROJECT SUMMARY Cardiac remodeling with loss of left ventricular compliance, impaired filling, and diastolic dysfunction can be secondary to several conditions, including restrictive cardiomyopathies and pressure overload (i.e., aortic stenosis or hypertension). Currently, there is an absence of in vitro and in vivo models of loss of LV compliance and impaired filling representing a major barrier for the development of effective treatments. To date, no validated in vitro model of the biomechanics of loss of LV compliance exists and animal models are limited by high mortality rates and an inability to finely control the degree and dynamics of induced pressure overload. The lack of robust animal models of loss of LV compliance and diastolic dysfunction has hampered the general understanding of the pathophysiology of these conditions. As a result, there are no available strategies that treat the underlying biomechanical manifestations of diastolic function. There is a lack of insight into optimal intervention planning to target and reverse adverse remodeling due to pressure overload. Through this proposal, we aim to leverage tunable dynamic mechanical implants to create disease models of loss of LV compliance and to characterize the plasticity of LV remodeling processes from biomechanical and hemodynamic standpoints, their progression, and potential reversal. We recently developed a soft robotic aortic sleeve to recapitulate the acute hemodynamics of pressure overload in a porcine model. Preliminary data show that we can re-create the hemodynamics of pressure overload and impaired filling in an in vitro model using soft robotic tools. Here, we aim to re-create the chronic biomechanical and hemodynamic manifestations of loss of LV compliance and impaired filling secondary to pressure overload with an enhanced system with sensing and control abilities. Specifically, we aim to: (1) Develop high-fidelity and patient-specific benchtop models of pressure overload loss of ventricular compliance, and impaired filling using tunable soft robotic tools ; (2) Optimize the aortic sleeve for chronic studies through the development of a minimally invasive delivery approach, MRI-safe implantable system, and built-in smart sensing for closed-loop feedback control to re-create patient-specific disease and (3) Develop and evaluate a clinically relevant chronic large animal model of cardiac remodeling due to pressure overload for time-varied degrees of pressure overload and assessment of potential for disease regression. Our proposed work will address limitations with current models to enable studies of the reversibility of the remodeling processes associated with chronic pressure overload, provide insights into the pathophysiological mechanisms, guide the optimal type and timing of intervention, and ultimately serve as a tunable, high-fidelity, and patient-specific platform for training purposes, device development, and hemodynamic outcome prediction for interventional planning in the clinic.
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