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; 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.

摘要 /摘要 主动脉瓣疾病可能导致多因素并发症，包括警报后3D血流 模式和严重的继发性主动脉疾病（主动脉膨胀，动脉瘤和解剖）。当前标准 - 但是，护理评估了主动脉瓣疾病的严重程度，从而评估治疗（手术VS。 保守管理）基于阀门本地的简化测量。矛盾的是，很好 已知类似地分类主动脉瓣疾病患者，表现出根本不同的临床表现 和结果。循证成像生物标志物超出主动脉直径能够具有风险分层的生物标志物是 因此迫切需要。 4D流量研究表明，主动脉瓣疾病表型对主动脉的变化具有很强的影响 血液动力学。在过去的几年中，我们组装了最大的主动脉4D MRI数据库之一 全球主动脉瓣疾病患者的1300多名患者检查（其中：> 880 BAV，> 420 与TAV）。此外，我们已经在广泛的年龄建立了一个大型健康的老龄化队列（n = 189 没有心血管疾病的控制，每个年龄段20-40：20-30，31-40，41-50，51-60，61 - 70年）和 分布在性别（83名男性，106名女性）之间。但是，大型队列的4D流量分析具有 受到大数据集的阻碍（每位患者4000-6000张图像），繁琐的手动分析限制 还原性，缺乏综合血液动力学信息的剥削（3D +时间 + 3方向 流动）。为了解决这些限制，我们最近开发了一种新颖的非侵入性4D虚拟导管 （VCATH）使用数学建模来模仿公认的侵入性导管 量化血液动力学。 4D VCATH利用完整的4D流MRI信息来灵活地定量主动脉 具有高度自动化的3D血流动力学。 4D VCATH概念比现有的优势 分析方法被评为同时探测不同基本（流量，峰值）和的内在能力 高级（动能KE，粘性能量损失EL，涡度）沿整个胸腔的血液动力学因子 主动脉。我们的大型队列加上全面的4D VCATH分析，使一个独特的机会 进行一项功能良好的回顾性研究，以鉴定与主动脉疾病相关的血液动力学因素 发展。 该项目将开发新的多参数基于血液动力学的主动脉疾病危险因素，这将提供 对主动脉疾病疾病机制的新见解，并为随后的纵向结果研究提供了信息。