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

本研究项目将医学图像的统计分析和分类方法与心血管功能磁共振成像（MRI）的开发和应用相结合。因此，重点将主要放在使用流量敏感的4D MRI以MRI为基础获取体内3D血流数据以及心血管系统3D血流特性的分类上。计划的工作将包括1)基于特征分类的算法开发和2)优化体内3D血流数据采集的MRI方法开发。因此，MRI方法与计划的数据分析及其在体内获取3D血流的先决条件直接相关，涉及测量所有速度范围的高脉动血流速度范围（动态范围），并具有高质量。临床应用将集中在胸主动脉数据的获取和评价上。目的是全面描述主动脉频繁发生的血管疾病（主动脉斑块、动脉瘤和峡部狭窄）的三维血流特征，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.