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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
项目总结 伴左室顺应性丧失、充盈受损和舒张期功能障碍的心脏重塑 继发于几种情况,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,尚无体外和体内LV顺应性丧失的模型。 而填塞受损是开发有效治疗方法的主要障碍。到目前为止,没有经过验证的 体外存在LV顺应性丧失的生物力学模型,动物模型受限于高死亡率 以及无法很好地控制诱导压力过载的程度和动态。 缺乏强大的动物模型的丧失的左心顺应性和舒张期功能障碍阻碍了一般 了解这些疾病的病理生理学。因此,没有可用的策略 治疗舒张期功能的潜在生物力学表现。缺乏洞察力 进入最佳干预计划,以靶向和逆转由于压力超负荷造成的不良重塑。 通过这项提议,我们的目标是利用可调的动态机械植入物来创建疾病模型 左心室顺应性的丧失和表征左心室重塑过程的可塑性 生物力学和血流动力学的观点,它们的进展和潜在的逆转。 我们最近开发了一种软式机器人主动脉袖子,以重述压力超负荷的急性血流动力学。 在猪的模型中。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填充受损。在这里,我们的目标是重建慢性生物力学 左心室顺应性丧失和继发于压力的充盈受损的血流动力学表现 超载,具有传感和控制能力的增强型系统。具体来说,我们的目标是:(1)发展 高保真和患者特定的台式模型的压力过载损失的心室顺应性,以及 使用可调节的软机器人工具进行受损的充盈;(2)通过 开发一种微创分娩方法、MRI安全的植入系统和内置智能传感 用于闭环反馈控制以重新创建特定于患者的疾病以及(3)开发和评估临床 不同程度压力超负荷所致心脏重构的相关慢性大动物模型 压力过载和疾病消退潜力的评估。 我们提议的工作将解决当前模型的局限性,以便能够研究 与慢性压力超负荷相关的重构过程,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、高保真且特定于患者的平台,用于培训、设备开发和 血流动力学结果预测在临床介入计划中的应用。
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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