Guided qualitative and quantitative analysis of cardiac 4D PC-MRI blood flow data
The genesis and progression of cardiovascular diseases (CVDs) depend on various factors. A better comprehension of patient-specific blood flow hemodynamics has great potential to increase their diagnosis, support treatment decision-making and provide a realistic forecast of such pathologies, facilitating a better implementation of preventative measures. Four-dimensional phase-contrast magnetic resonance imaging (4D PC-MRI) gained increasing importance and clinical attention in recent years. It is a non-invasive imaging modality that allows for time-resolved, three-dimensional measurement of blood flow information. The resulting 4D grid data, which contain vectors that represent the blood flow direction and velocity, are of limited spatio-temporal resolution and suffer from multiple artifacts, making complex image processing methods a prerequisite. Qualitative data analysis aims to depict the course of the blood flow with emphasis on specific flow patterns, such as vortex flow, which can be an indicator for different cardiovascular diseases. For this purpose, flow visualization techniques can be adapted to the cardiac context. Quantitative data analysis facilitates assessment of, e.g., the cardiac function by evaluating stroke volumes, heart valve performances by evaluating percentaged back flows, and fluid-vessel wall interactions by evaluating wall shear stress. This thesis proposes both qualitative and quantitative data evaluation methods, embedded in a developed software prototype with a guided workflow. A semi-automatic extraction of vortex flow is presented that is based on the line predicates methodology and preserves visually appealing path lines with long and continuous courses. It was tailored towards our targeted user group: Radiologists focused on the cardiovascular system and cardiologists. The extracted path lines were used to establish an overview visualization of aortic vortex flow and to adapt the speed of videos so that the display vortical flow behavior is enhanced. Vortices were grouped into single entities (clustering) and subsequently analyzed according to different criteria that describe properties, such as their rotation direction and elongation. Based on this classification, a simplifying glyph visualization was established. Moreover, this thesis addresses an improved quantification of the flow rate-based measures, such as stroke volumes, which are prone to errors especially in case of pathologic vortex flow. A robust procedure is presented that analyzes multiple, systematically generated configurations of required measuring planes and evaluates the resulting sample distributions. Additionally, the flow rate calculation is influenced by the dynamic morphology. Therefore, a semi-automatic extraction of corresponding motion information was established and incorporated in an adapted quantification.