4D Virtual Catheter (vCath) Assessment of Hemodynamic Pathways in Aortopathy Pathogenesis

4D 虚拟导管 (vCath) 评估主动脉病发病机制中的血流动力学通路

基本信息

批准号：
10092217
负责人：
Mohammed Elbaz
金额：
$ 11.91万
依托单位：
NORTHWESTERN UNIVERSITY AT CHICAGO
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-02-01 至 2024-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10092217
关键词：
3-Dimensional 4D MRI Address Adult Affect Age Anatomy Aneurysm Aorta Aortic Diseases Aortic Valve Stenosis Automation Blood flow Caliber Cardiovascular Diseases Catheters Cessation of life Clinical Cohort Analysis Confidence Intervals Coupled Data Databases Detection Development Diagnostic Diagnostic Imaging Diagnostic tests Dilatation - action Dimensions Disease Dissection Exhibits Female Gender Goals Growth Guidelines Hypertension Image Intervention Kinetics Knowledge Life Longevity Longitudinal Studies Longterm Follow-up Magnetic Resonance Imaging Manuals Measurement Measures Methods Morphology Multivariate Analysis Operative Surgical Procedures Outcome Pathogenesis Pathology Pathway interactions Patient-Focused Outcomes Patients Pattern Performance Pharmaceutical Preparations Phenotype Physiological Population Race Reproducibility Retrospective Studies Risk Factors Severities Severity of illness Techniques Thoracic aorta Time age effect aortic valve aortic valve disorder base bicuspid aortic valve cohort congenital heart disorder data pipeline demographics disease phenotype evidence base flexibility frontier healthy aging hemodynamics imaging biomarker improved improved outcome in vivo insight large datasets male mathematical model novel novel diagnostics outcome prediction pressure repaired risk stratification sex standard of care tool virtual

项目摘要

SUMMARY / ABSTRACT Aortic Valve Disease can result in multi-factorial complications including alerted post-valvular 3D blood flow patterns and severe secondary aortopathy (aortic dilatation, aneurysm, and dissection). The current standard- of-care, however, assesses aortic valve disease severity and thus therapy management (surgery vs. conservative management) based on simplified measurements local to the valve. Paradoxically, it is well known that similarly classified aortic valve disease patients, exhibit radically divergent clinical presentations and outcomes. Evidence-based imaging biomarkers beyond aortic diameter capable of risk stratification are thus urgently needed. 4D flow studies have shown that the aortic valve disease phenotype has a strong effect on changes in aortic hemodynamics. Over the past years, we have assembled one of the largest aortic 4D MRI databases worldwide with over 1300 patient exams in patients with aortic valve disease (among these: >880 BAV, >420 with TAV). Also, we have established a large healthy aging cohort across a broad range of ages (n=189 controls free of cardiovascular disease, 20-40 per age decade: 20-30, 31-40, 41-50, 51-60, 61-70 years) and well distributed between genders (83 male, 106 female). However, 4D flow analysis across large cohorts has been hindered by large data sets (4000-6000 images per patient), cumbersome manual analysis limiting reducibility, and lack of exploitation of the comprehensive hemodynamic information (3D + time + 3-direction flow). To address these limitations, we have recently developed a novel non-invasive 4D virtual Catheter (vCath) technique that uses mathematical modeling to mimic the well-established invasive catheter in quantifying hemodynamics. 4D vCath utilizes the full 4D flow MRI information for flexible quantification of aortic 3D hemodynamic with high degree of automation. An advantage of the 4D vCath concept over existing analysis methods is rated to its intrinsic ability to simultaneously probe different basic (flow, peak velocity) and advanced (kinetic energy KE, viscous energy loss EL, vorticity) hemodynamic factors along the entire thoracic aorta. Our large cohort coupled with comprehensive 4D vCath analysis enables a unique opportunity to conduct a well-powered retrospective study to identify hemodynamic factors associated with aortopathy development. This project will develop new multi-parametric hemodynamic-based aortopathy risk factors, which will provide novel insights into aortopathy disease mechanisms and inform subsequent longitudinal outcome studies.

摘要/摘要主动脉瓣疾病可导致多因素并发症，包括瓣膜后 3D 血流警报模式和严重的继发性主动脉病变（主动脉扩张、动脉瘤和夹层）。现行标准—— 然而，护理后评估主动脉瓣疾病的严重程度，从而评估治疗管理（手术与非手术治疗）。保守管理）基于阀门本地的简化测量。矛盾的是，这很好已知相似分类的主动脉瓣疾病患者表现出截然不同的临床表现和结果。超出主动脉直径的基于证据的成像生物标志物能够进行风险分层因而迫切需要。 4D 血流研究表明，主动脉瓣疾病表型对主动脉瓣的变化有很强的影响。血流动力学。在过去的几年里，我们组建了最大的主动脉 4D MRI 数据库之一全球范围内对主动脉瓣疾病患者进行了超过 1300 次检查（其中：>880 BAV、>420 与 TAV）。此外，我们还建立了一个涵盖广泛年龄范围的大型健康老龄化队列（n=189）控制无心血管疾病，每个年龄20-40岁：20-30、31-40、41-50、51-60、61-70岁）和性别分布良好（83 名男性，106 名女性）。然而，跨大群体的 4D 流分析已经受到大数据集（每个患者 4000-6000 张图像）、繁琐的手动分析限制的阻碍可还原性，缺乏对综合血流动力学信息（3D + 时间 + 3 方向）的开发流动）。为了解决这些限制，我们最近开发了一种新型非侵入性 4D 虚拟导管 (vCath) 技术，使用数学模型来模拟成熟的侵入性导管量化血流动力学。 4D vCath 利用完整的 4D 血流 MRI 信息对主动脉进行灵活量化 3D血流动力学，自动化程度高。 4D vCath 概念相对于现有技术的优势分析方法根据其同时探测不同基本（流量、峰值速度）和整个胸部的高级血流动力学因素（动能 KE、粘性能量损失 EL、涡量）主动脉。我们的大型队列与全面的 4D vCath 分析相结合，为您提供了独特的机会进行一项强有力的回顾性研究，以确定与主动脉病相关的血流动力学因素发展。该项目将开发新的基于多参数血流动力学的主动脉病危险因素，这将提供对主动脉病疾病机制的新见解并为后续的纵向结果研究提供信息。