Non-invasive hemodynamic and biomechanic imaging methods for early risk prediction in aortic dissection

用于主动脉夹层早期风险预测的非侵入性血流动力学和生物力学成像方法

基本信息

项目摘要

PROJECT SUMMARY/ABSTRACT Aortic dissection (AD) is a disease characterized by sudden tearing of the inner layers of the aortic wall creating a false lumen (FL) channeling aortic blood flow. The vast majority of acute AD patients survive into the chronic phase, although long-term outcomes are poor with about 50% of patients experiencing aorta-related mortality or requiring surgical repair by 10 years. A major contributor to poor long-term outcomes is growth of the FL. Thoracic endovascular aortic repair (TEVAR) is a minimally invasive surgical therapy which can halt FL growth and reduce AD mortality; however, this treatment comes with cost, risk of procedural complications, and is less effective over time owing to increased tissue stiffness. Accurate prediction of disease trajectory at early phases is limited with current metrics but is highly desirable as this would allow TEVAR to be targeted to high-risk patients in a timely manner, sparing those at lower risk from potentially unnecessary procedures. Current methods for estimating risk in AD are largely based on anatomic metrics (e.g., aortic diameter), which poorly capture functional aspects of AD. To overcome these limitations, we propose to apply advanced imaging techniques, namely 4D Flow magnetic resonance imaging (MRI) and 4D computed tomography angiography (CTA), to characterize and quantify functional processes such as FL pressure and FL wall stiffness, which elude current imaging approches and have been implicated as important factors in predicting long-term behavior of AD. We hypothesize that assessments of these functional metrics will, improve our prediction of false lumen growth rate (FLGR) compared to standard anatomic metrics. We plan to prospectively recruit patients with either uncomplicated type B (n=30) or surgically repaired type A (n=45) aortic dissection to undergo baseline 4D Flow and 4D CTA imaging in the subacute period (1-3 months post-dissection) as well as follow-up studies at 1- and 2-years post-dissection, with the primary outcome being FLGR. To achieve these goals, the Aims of this proposal are: 1) Identify baseline hemodynamic and biomechanical metrics in the subacute period of AD that predict FL growth rate over time. FL pressure will be quantified from 4D Flow MRI using indirect and direct methods based on physics-based image analysis, with regional FL wall stiffness quantified by merging FL pressure with cyclic aortic wall deformation by 4D CT; 2) Determine the trajectories of functional metrics over time that best predict progressive FL growth. Longitudinal changes in pressure and wall stiffness between baseline and 1- and 2-year follow-up scans will be assessed to identify patients who achieve a new equilibrium versus those who continue to progress; 3) Develop a clinical assessment tool to predict risk of progressive FL growth combining functional metrics, anatomic parameters and patient characteristics with a focus on simplicity and accuracy for dissection-type specific prediction of the FLGR at the earliest possible time point. This work seeks to shift the paradigm of AD assessment from pure anatomic characterization by integrating functional imaging biomarkers to provide accurate predictions of disease trajectory and allow for optimal determination of surgical candidacy and timing.
项目总结/摘要 主动脉夹层(AD)是一种以主动脉壁内层突然撕裂为特征的疾病, 引导主动脉血流的假腔(FL)。绝大多数急性AD患者均存活至慢性AD 虽然长期结果很差,约50%的患者发生了与血栓相关的死亡, 需要手术修复的时间缩短了10年导致长期结局不佳的一个主要因素是FL的生长。 主动脉腔内修复术(TEVAR)是一种微创外科治疗,可阻止FL生长并减少 AD死亡率;然而,这种治疗伴随着成本、手术并发症的风险, 由于组织硬度增加而导致的时间。在早期阶段准确预测疾病轨迹是有限的, 目前的指标,但这是非常可取的,因为这将允许TEVAR及时针对高风险患者, 方式,使那些风险较低的人免受可能不必要的程序。目前的估算方法 AD的风险主要基于解剖学度量(例如,主动脉直径),其捕获功能方面较差 的AD。为了克服这些限制,我们建议应用先进的成像技术,即4D Flow 磁共振成像(MRI)和4D计算机断层扫描血管造影(CTA),以表征和 量化功能过程,如FL压力和FL壁刚度,这是目前成像方法所无法实现的 并已被认为是预测AD长期行为的重要因素。我们假设 这些功能指标的评估将改善我们对假腔生长率(FLGR)的预测, 到标准的解剖学指标。我们计划前瞻性招募单纯B型患者(n=30) 或手术修复的A型主动脉夹层(n=45)进行基线4D Flow和4D CTA成像, 亚急性期(剥离后1-3个月)以及剥离后1年和2年的随访研究, 主要结果是FLGR。为了达到这些目标,本提案的目的是:1)确定基线 AD亚急性期的血液动力学和生物力学指标,预测FL随时间的增长率。FL 将使用基于物理图像的间接和直接方法从4D Flow MRI中量化压力 分析,通过合并FL压力和周期性主动脉壁变形量化局部FL壁刚度, 4D CT; 2)确定功能指标随时间推移的轨迹,最好地预测进行性FL生长。 基线与1年和2年随访扫描之间的压力和室壁刚度的纵向变化将被 评估以识别达到新平衡的患者与继续进展的患者; 3)开发 一种临床评估工具,结合功能指标、解剖学指标, 参数和患者特征,重点是针对特定解剖类型的简单性和准确性 在尽可能早的时间点预测FLGR。这项工作旨在改变AD评估的范式 通过整合功能成像生物标志物,从纯粹的解剖学表征提供准确的预测 疾病的轨迹,并允许最佳的决定手术的候选人和时机。

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
lGeneralized super-resolution 4D Flow MRI-using ensemble learning to extend across the cardiovascular system.
l 广义超分辨率 4D Flow MRI - 使用集成学习扩展到整个心血管系统。
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Ericsson,Leon;Hjalmarsson,Adam;Akbar,MuhammadUsman;Ferdian,Edward;Bonini,Mia;Hardy,Brandon;Schollenberger,Jonas;Aristova,Maria;Winter,Patrick;Burris,Nicholas;Fyrdahl,Alexander;Sigfridsson,Andreas;Schnell,Susanne;Figueroa,CAlbe
  • 通讯作者:
    Figueroa,CAlbe
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Nicholas Scott Burris其他文献

Nicholas Scott Burris的其他文献

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{{ truncateString('Nicholas Scott Burris', 18)}}的其他基金

Vascular Deformation Mapping (VDM) for Automated, 3D Assessment of Thoracic Aortic Aneurysm
用于胸主动脉瘤自动 3D 评估的血管变形测绘 (VDM)
  • 批准号:
    10409547
  • 财政年份:
    2019
  • 资助金额:
    $ 68.84万
  • 项目类别:

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