Development of diagnostic and predictive computational mechanics methods for cardiovascular system

心血管系统诊断和预测计算力学方法的发展

• 批准号: RGPIN-2017-05349
• 负责人: KeshavarzMotamed, Zahra
• 金额: $ 2.19万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=683424
• 关键词: Development; diagnostic; predictive; computational; mechanics

The main functions of the cardiovascular system are to transport, control and maintain blood flow in the entire body. Abnormal hemodynamics greatly alters this tranquil picture, leading to initiation and progression of disease. Cardiovascular disease is the leading cause of death globally. In Canada, one in every four deaths is from cardiovascular disease. Flow quantification can be greatly useful for accurate and early diagnosis but we still lack proper diagnostic methods for many cardiovascular diseases. Furthermore, as most interventions intend to recover the healthy condition, the ability to predict hemodynamics and biomechanics following a particular intervention can have significant impacts on saving lives. Despite remarkable advances in medical imaging, predictive methods remain rare.******The main objective of this proposal is developing computational-mechanics frameworks for diagnosis and prediction for the most fundamentally challenging condition: complex ventricular-valvular interactions (CVVI). CVVI represent conditions in which multiple valvular and ventricular pathologies have mechanical interactions with one another wherein physical phenomena associated with each pathology amplify effects of others on the cardiovascular system. Transcatheter valve replacement (TVR) is a minimally invasive and growing alternative intervention in patients with severe valvular pathologies. It was shown that many patients experience a significant improvement after TVR but in many others CVVI worsens or changes to other forms of CVVI. As pathologies in CVVI are essentially of fluid-dynamic nature, they are best quantified using mechanics. Indeed, even the emerging innovations in therapeutics such as TVR are themselves mechanical. Yet, few to date have used basic mechanics for diagnosis of these pathologies and for prediction of response to interventions. The heart resides in a sophisticated vascular network whose loads impose boundary conditions on the heart function. Effective diagnosis and prediction hinge on quantifications of the heart workload (global effect) and of hemodynamics of CVVI and TVR (local effect).******This proposal tackles profound scientific and engineering challenges to develop the following innovative computational-mechanics methods for diagnosis and prediction:******(1) Computational-mechanics and imaging-based diagnostic methods: *** (a) Local: to noninvasively quantify vortex dynamics, fluid transport, and mixing in CVVI and TVR using Lagrangian coherent structures (LCS); *** (b) Global: to noninvasively quantify global hemodynamics to diagnose pathologies present in CVVI in terms of heart workload.******(2) A multiscale predictive computational-mechanics framework that dynamically couples the local hemodynamics with the global circulatory cardiovascular system in pre-intervention condition to predict local and global hemodynamics post-TVR.

心血管系统的主要功能是运输、控制和维持全身的血液流动。血流动力学异常极大地改变了这一平静的图景，导致疾病的发生和发展。心血管疾病是全球主要的死亡原因。在加拿大，每四例死亡中就有一例死于心血管疾病。血流定量对于准确和早期诊断有很大帮助，但我们仍然缺乏对许多心血管疾病的正确诊断方法。此外，由于大多数干预措施旨在恢复健康状况，因此预测特定干预措施后的血流动力学和生物力学的能力可能对挽救生命产生重大影响。尽管医学成像取得了显著进展，但预测方法仍然很少。*本提案的主要目标是开发计算力学框架，用于诊断和预测最具挑战性的疾病：复杂的室-瓣膜相互作用(CVVI)。CVVI代表多种瓣膜和心室病变相互作用的情况，其中与每种病变相关的物理现象放大了其他病变对心血管系统的影响。经导管瓣膜置换术(TVR)是一种对严重瓣膜病变患者进行微创且日益增长的替代治疗方法。结果显示，许多患者在TVR后有明显的改善，但在许多其他患者中，CVVI恶化或改变为其他形式的CVVI。由于CVVI中的病理本质上是流体动力学性质的，它们最好用力学来量化。事实上，即使是TVR等治疗领域的新兴创新，本身也是机械的。然而，到目前为止，很少有人使用基本力学来诊断这些病理并预测对干预的反应。心脏位于一个复杂的血管网络中，其负荷对心脏功能施加了边界条件。有效的诊断和预测取决于对心脏负荷(全局效应)和CVVI和TVR血流动力学(局部效应)的量化。*这项建议解决了深刻的科学和工程挑战，以开发下列创新的诊断和预测计算力学方法：*(1)基于计算力学和成像的诊断方法：*(A)局部：使用拉格朗日相干结构(LCS)对CVVI和TVR中的涡旋动力学、流体传输和混合进行非侵入性量化；*(B)全局：非侵入性地量化全球血流动力学以根据心脏工作量诊断CVVI中存在的病理。*(2)多尺度预测计算力学框架，该框架动态地将介入前状态下的局部血流动力学与全球循环心血管系统相耦合，以预测TVR术后的局部和全局血流动力学。