Computational and Biological Approach to Flow Diversion

分流的计算和生物学方法

基本信息

  • 批准号:
    9750816
  • 负责人:
  • 金额:
    $ 49.36万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2011
  • 资助国家:
    美国
  • 起止时间:
    2011-09-20 至 2021-08-31
  • 项目状态:
    已结题

项目摘要

PROJECT SUMMARY This competitive renewal application focuses on advancing the rapidly-evolving field of intracranial flow diversion, which, over the span of less than 5 years, has grown to encompass up to one-third of intracranial aneurysm treatments in the US. We will address clinically-relevant, ongoing gaps in knowledge, including 1) what constitutes the primary mechanism of action of flow diverter efficacy, 2) what underlies the unusual, but devastating complications, including ipsilateral, intraparenchymal hemorrhage and spontaneous aneurysm rupture, and 3) what design features of these devices can be enhanced to optimize outcomes? Our translational, hypothesis-driven methodology traverses from computational/in vitro work (computational fluid dynamics and in vitro bioreactor studies) to in vivo experiments in a rabbit model and, finally, to clinical studies. Our statistically robust evaluations will directly address 1) the role of wall apposition in aneurysm healing and risk for complication, 2) downstream hemodynamic derangements caused by flow diverter implantation vis-à- vis risk for spontaneous hemorrhage, and 3) the relative impact of diversion of flow versus other factors, including thrombus formation and endothelialization, in healing. The discoveries from this competitive renewal will be directly applicable to clinicians treating patients with currently-approved devices and managing patients following flow diversion treatment in order to optimize outcomes and minimize complications, as well as to engineers and scientists focused on developing idealized, future devices, even those with patient-specific, individualized features.
项目总结 这一竞争性更新应用侧重于推进快速发展的颅内血流领域 分流,在不到5年的时间里,已经增长到覆盖多达三分之一的颅内 美国的动脉瘤治疗。我们将解决与临床相关的持续知识差距,包括1) 是什么构成了分流装置功效的主要作用机制,2)是什么导致了不寻常的,但 破坏性并发症,包括同侧、实质内出血和自发性动脉瘤 以及3)这些设备的哪些设计功能可以增强以优化结果?我们的 翻译、假设驱动的方法论从计算/体外工作(计算流体 从动力学和体外生物反应器研究)到兔模型的活体实验,最后是临床研究。 我们的统计稳健的评估将直接解决1)壁对置在动脉瘤愈合和修复中的作用 并发症风险,2)植入分流器引起的下游血流动力学紊乱。 与自发性出血的风险,以及3)分流相对于其他因素的相对影响, 包括血栓形成和内皮化,在愈合中。从这次竞争性更新中获得的发现 将直接适用于临床医生使用当前批准的设备治疗患者和管理患者 在分流治疗之后,以优化结果和最大限度地减少并发症 工程师和科学家专注于开发理想化的、未来的设备,即使是那些具有特定患者的设备, 个性化特征。

项目成果

期刊论文数量(0)
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Juan R Cebral其他文献

Juan R Cebral的其他文献

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{{ truncateString('Juan R Cebral', 18)}}的其他基金

Computational and Biological Approach to Flow Diversion
分流的计算和生物学方法
  • 批准号:
    10363267
  • 财政年份:
    2021
  • 资助金额:
    $ 49.36万
  • 项目类别:
Computational and Biological Approach to Flow Diversion
分流的计算和生物学方法
  • 批准号:
    10540708
  • 财政年份:
    2021
  • 资助金额:
    $ 49.36万
  • 项目类别:
Improving Cerebral Aneurysm Risk Assessment through Understanding Wall Vulnerability and Failure Modes
通过了解壁的脆弱性和失效模式改进脑动脉瘤风险评估
  • 批准号:
    10398949
  • 财政年份:
    2016
  • 资助金额:
    $ 49.36万
  • 项目类别:
Improving Cerebral Aneurysm Risk Assessment through Understanding Wall Vulnerability and Failure Modes
通过了解壁的脆弱性和失效模式改进脑动脉瘤风险评估
  • 批准号:
    10621168
  • 财政年份:
    2016
  • 资助金额:
    $ 49.36万
  • 项目类别:
Improved Evaluation of PCOM Aneurysms: Angio-Architecture, Hemodynamics and Shape
改进 PCOM 动脉瘤的评估:血管结构、血流动力学和形状
  • 批准号:
    9144876
  • 财政年份:
    2015
  • 资助金额:
    $ 49.36万
  • 项目类别:
The link between hemodynamics and wall structure in cerebral aneurysms
脑动脉瘤血流动力学与壁结构之间的联系
  • 批准号:
    8609084
  • 财政年份:
    2013
  • 资助金额:
    $ 49.36万
  • 项目类别:
The link between hemodynamics and wall structure in cerebral aneurysms
脑动脉瘤血流动力学与壁结构之间的联系
  • 批准号:
    8512060
  • 财政年份:
    2013
  • 资助金额:
    $ 49.36万
  • 项目类别:
Computational and Biological Approach to Flow Diversion
分流的计算和生物学方法
  • 批准号:
    9284516
  • 财政年份:
    2011
  • 资助金额:
    $ 49.36万
  • 项目类别:
Computational and Biological Approach to Flow Diversion
分流的计算和生物学方法
  • 批准号:
    9175421
  • 财政年份:
    2011
  • 资助金额:
    $ 49.36万
  • 项目类别:
Computational Analysis of Cerebral Aneurysm Evolution
脑动脉瘤演化的计算分析
  • 批准号:
    7617027
  • 财政年份:
    2007
  • 资助金额:
    $ 49.36万
  • 项目类别:

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