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

• 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
• 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

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.

总结/摘要 主动脉瓣疾病可导致多因素并发症，包括报警的瓣后3D血流 模式和严重的继发性动脉瘤病（主动脉扩张、动脉瘤和夹层）。现行标准- 然而，护理外评估主动脉瓣疾病的严重程度，从而评估治疗管理（手术与 保守管理）。巧合的是， 已知类似分类的主动脉瓣疾病患者表现出完全不同的临床表现， 和结果。能够进行风险分层的超过主动脉直径的循证成像生物标志物是 因此迫切需要。 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，我们已经建立了一个最大的主动脉4D MRI数据库 在全球范围内，对1300多例主动脉瓣疾病患者进行了检查（其中：>880 BAV，>420 TAV）。此外，我们还建立了一个大型的健康老龄化队列（n=189 无心血管疾病的对照组，每10岁20-40人：20-30岁、31-40岁、41-50岁、51-60岁、61-70岁）， 性别分布均衡（男性83人，女性106人）。然而，大型队列的4D血流分析 受到大数据集（每位患者4000-6000张图像）、繁琐的手动分析限制 减少，缺乏对综合血流动力学信息（3D +时间+ 3-方向）的开发 流动）。为了解决这些局限性，我们最近开发了一种新型的非侵入性4D虚拟导管 （vCath）技术，该技术使用数学建模来模拟已确立的侵入性导管， 量化血液动力学。4D vCath利用完整的4D Flow MRI信息灵活量化主动脉 自动化程度高的3D血流动力学。4D vCath概念相对于现有技术的优势 分析方法被评为其内在的能力，同时探测不同的基本（流量，峰值速度）， 沿沿着整个胸廓的先进（动能KE、粘性能量损失EL、涡度）血流动力学因素 主动脉我们的大型队列加上全面的4D vCath分析，为以下方面提供了独特的机会： 进行一项有效的回顾性研究，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血液动力学的多参数动脉粥样硬化风险因素， 新的见解，以了解脊椎病的疾病机制，并告知随后的纵向结果研究。