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开发
基本信息
- 批准号:RGPIN-2017-05349
- 负责人:
- 金额:$ 2.19万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2020
- 资助国家:加拿大
- 起止时间:2020-01-01 至 2021-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
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。异常的血流动力学极大地改变了这种平静的情况,导致疾病的发生和进展。心血管疾病是全球死亡的主要原因。在加拿大,四分之一的死亡是死于心血管疾病。血流定量对于准确和早期诊断非常有用,但我们仍然缺乏对许多心血管疾病的适当诊断方法。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着进步,但预测方法仍然很少。
该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病症:复杂的心室瓣膜相互作用(CVVI)。 CVVI代表多种瓣膜和心室病理相互之间存在机械相互作用的病症,其中与每种病理相关的物理现象放大了其他病理对心血管系统的影响。经导管瓣膜置换术 (TVR) 是一种针对严重瓣膜病变患者的微创且不断发展的替代干预措施。结果表明,许多患者在 TVR 后经历了显着改善,但许多其他患者 CVVI 恶化或改变为其他形式的 CVVI。由于 CVVI 中的病理本质上具有流体动力学性质,因此最好使用力学对其进行量化。事实上,即使是 TVR 等新兴疗法的创新本身也是机械性的。然而,迄今为止,很少有人使用基本机制来诊断这些病理并预测干预措施的反应。心脏位于复杂的血管网络中,其负荷对心脏功能施加边界条件。有效的诊断和预测取决于心脏工作负荷(全局效应)以及 CVVI 和 TVR 血流动力学(局部效应)的量化。
该提案解决了深刻的科学和工程挑战,以开发以下用于诊断和预测的创新计算力学方法:
(1) 计算力学和基于成像的诊断方法:
(a) 局部:使用拉格朗日相干结构 (LCS) 无创地量化 CVVI 和 TVR 中的涡流动力学、流体传输和混合;
(b) 整体:无创地量化整体血流动力学,以根据心脏工作负荷诊断 CVVI 中存在的病理。
(2) 多尺度预测计算力学框架,在干预前将局部血流动力学与全局循环心血管系统动态耦合,以预测 TVR 后的局部和全局血流动力学。
项目成果
期刊论文数量(0)
专著数量(0)
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KeshavarzMotamed, Zahra其他文献
KeshavarzMotamed, Zahra的其他文献
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{{ truncateString('KeshavarzMotamed, Zahra', 18)}}的其他基金
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开发
- 批准号:
RGPIN-2017-05349 - 财政年份:2022
- 资助金额:
$ 2.19万 - 项目类别:
Discovery Grants Program - Individual
Development of a patient-specific predictive tool and a regulatory testing machine for transcatheter heart valve replacement
开发用于经导管心脏瓣膜置换术的患者特异性预测工具和监管测试机
- 批准号:
537352-2018 - 财政年份:2021
- 资助金额:
$ 2.19万 - 项目类别:
Collaborative Research and Development Grants
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开发
- 批准号:
RGPIN-2017-05349 - 财政年份:2021
- 资助金额:
$ 2.19万 - 项目类别:
Discovery Grants Program - Individual
Development of a patient-specific predictive tool and a regulatory testing machine for transcatheter heart valve replacement
开发用于经导管心脏瓣膜置换术的患者特异性预测工具和监管测试机
- 批准号:
537352-2018 - 财政年份:2020
- 资助金额:
$ 2.19万 - 项目类别:
Collaborative Research and Development Grants
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 - 财政年份:2019
- 资助金额:
$ 2.19万 - 项目类别:
Discovery Grants Program - Individual
Development of a patient-specific predictive tool and a regulatory testing machine for transcatheter heart valve replacement
开发用于经导管心脏瓣膜置换术的患者特异性预测工具和监管测试机
- 批准号:
537352-2018 - 财政年份:2019
- 资助金额:
$ 2.19万 - 项目类别:
Collaborative Research and Development Grants
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 - 财政年份:2018
- 资助金额:
$ 2.19万 - 项目类别:
Discovery Grants Program - Individual
New cardiovascular simulator for coarctation of the aorta and coarctation-related devices
用于主动脉缩窄的新型心血管模拟器和缩窄相关设备
- 批准号:
516329-2017 - 财政年份:2017
- 资助金额:
$ 2.19万 - 项目类别:
Engage Grants Program
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 - 财政年份:2017
- 资助金额:
$ 2.19万 - 项目类别:
Discovery Grants Program - Individual
Development of a Doppler echocardiography method for left-ventricle flow-field quantification
左心室流场量化多普勒超声心动图方法的开发
- 批准号:
454819-2014 - 财政年份:2016
- 资助金额:
$ 2.19万 - 项目类别:
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