Partners: Heart Center in Leipzig (Matthias Gutberlet, Matthias Grothoff)
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.
In this project both qualitative and quantitative data evaluation methods are developed, embedded in a developed software prototype with a guided workflow.
- A semi-automatic extraction of vortex flow was established 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, the improved quantification of flow rate-based measures was addressed, such as stroke volumes, which are prone to errors especially in case of pathologic vortex flow. A robust procedure was developed 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.
Automated quantitative extraction and analysis of 4D flow patterns in the ascending aorta -- an intraindividual comparison at 1.5 T and 3 T Journal Article
Scientific reports, 10.2020 , pp. 9 Seiten, 2020.
Comparison of two accelerated 4D-Flow sequences for aortic flow quantification Inproceedings
Scientific Reports, 2019.
Validation of two accelerated 4D flow MRI sequences at 3T: a phantom study Inproceedings
European Radiology Experimental, pp. 1–12, Springer International Publishing, 2019.
Bloodline: A system for the guided analysis of cardiac 4D PC-MRI data Journal Article
Computers & Graphics, 82 , pp. 32–43, 2019.
Visual and Quantitative Analysis of Great Arteries' Blood Flow Jets in Cardiac 4D PC-MRI Data Journal Article
Computer Graphics Forum, 37 (3), pp. 195-204, 2018.
Pressure-based vortex extraction in cardiac 4D PC-MRI blood flow data Inproceedings
EuroVis 2018: Eurographics / IEEE VGTC Conference on Visualization 2018, pp. to appear, 2018.
Comparison of Divergence-Free Filters for Cardiac 4D PC-MRI Data Inproceedings
Bildverarbeitung für die Medizin (BVM), pp. 139–144, Springer Verlag, Erlangen, 2018.
Visualization of Cardiac Blood Flow Using Anisotropic Ambient Occlusion for Lines Inproceedings
Vision, Modelling und Visualization (VMV), Bonn, 2017.
Semi-Automatic Vessel Boundary Detection in Cardiac 4D PC-MRI Data Using FTLE fields Inproceedings
Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM), pp. 41–46, Bergen, Norwegen, 2016.
Enhancing Visibility of Blood Flow in Volume Rendered Cardiac 4D PC-MRI Data Inproceedings
Bildverarbeitung für die Medizin (BVM), pp. 188–193, Berlin, 2016.
A Survey of Cardiac 4D PC-MRI Data Processing Journal Article
Computer Graphics Forum, 2016.
Adaptive Animations of Vortex Flow Extracted from Cardiac 4D PC-MRI Data Inproceedings
Bildverarbeitung für die Medizin (BVM), pp. 194–199, 2016.
Semi-automatic Vortex Flow Classification in 4D PC-MRI Data of the Aorta Inproceedings
EuroVis 2016: Eurographics / IEEE VGTC Conference on Visualization 2016, pp. 351–360, 2016.
Clustering of Aortic Vortex Flow in Cardiac 4D PC-MRI Data Inproceedings
Bildverarbeitung für die Medizin (BVM), pp. 182–187, 2016.
A Survey of Cardiac 4D PC-MRI Data Processing Inproceedings
Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM), pp. 139–148, Chester, UK, 2015.
Two-Dimensional Plot Visualization of Aortic Vortex Flow in Cardiac 4D PC-MRI Data Inproceedings
Proc. of Bildverarbeitung für die Medizin, pp. 257-261, 2015.
Robust Cardiac Function Assessment in 4D PC-MRI Data of the Aorta and Pulmonary Artery Journal Article
Comp Graph Forum, 2015.
Guided Analysis of Cardiac 4D PC-MRI Blood Flow Data Inproceedings
Eurographics Short Papers and Medical Prize Awards, 2015.
Motion-aware stroke volume quantification in 4D PC-MRI data of the human aorta Inproceedings
International Journal of Computer-Assisted Radiology and Surgery (IJCARS), pp. 1–11, Springer, 2015.
Robust Cardiac Function Assessment in 4D PC-MRI Data Inproceedings
Proc. of Eurographics Workshop on Visual Computing for Biology and Medicine (EG VCBM), pp. 1–10, Wien, 2014.
Semi-Automatic Vortex Extraction in 4D PC-MRI Cardiac Blood Flow Data using Line Predicates Journal Article
IEEE Transactions on Visualization and Computer Graphics (TVCG), 19(12) , pp. 2773–2782, 2013.
Surface-Based Seeding for Blood Flow Exploration Inproceedings
Bildverarbeitung für die Medizin, pp. 81–86, Berlin, 2012.