Analysis of 3D flow data in the aorta: Optimised dual-venc flow-sensitive MRI and statistical data analysis for automated flow classification

该研究项目将医学图像的统计分析和分类方法与功能性心血管磁共振成像（MRI）的开发和应用相结合。因此，将重点主要放在使用流量敏感的4D MRI的体内3D血流数据的基于MRI的采集和心血管系统的3D流特性的分类上。计划的工作将包括1）基于特征的分类算法的开发和2）MRI方法的开发，用于优化3D血流数据的体内采集。因此，MRI方法与计划的数据分析及其体内3D血流采集的先决条件直接相关，涉及对所有速度范围进行高质量的高脉动流速范围（动态范围）测量。临床应用将集中在胸主动脉数据的采集和评价上。目的是全面分析常见的主动脉血管疾病（主动脉斑块、动脉瘤和峡部狭窄）的3D流动特征，以研究血流动力学变化与病理发展和进展之间的关系。

The research project combines statistical analysis and classification methods of medical images with the development and application of functional cardiovascular magnetic resonance imaging (MRI). Thereby will be the focus mainly put on the MRI-based acquisition of in vivo 3D blood flow data using flow-sensitive 4D MRI and on the classification of the 3D flow properties of the cardiovascular system. The planned work will include 1) the development of algorithms for feature-based classification and 2) MRI method development for optimised in vivo acquisition of 3D blood flow data. The MRI methods are thereby directly connected with the planned data analysis and its prerequisites on the in vivo acquisition of 3D blood flow concerning measurement of the high pulsatile flow velocity range (dynamic range) with high quality for all velocity ranges. The clinical applications will be focused on the acquisition and evaluation of thoracic aorta data. The aim will be to characterise comprehensively the 3D flow characteristics of frequently occurring vascular diseases of the aorta (plaques in the aorta, aneurysms and isthma stenosis) in order to investigate the relationship between changed hemodynamics and development and progression of pathologies.