Received 26 February 2009; received in revised form 19 November 2009; accepted 22 November 2009. published online 21 December 2009.
Abstract
In a chamber of the heart, large-scale vortices are shown to exist as the result of the dynamic blood flow and unique morphological changes of the chamber wall. As the cardiovascular flow varies over a cardiac cycle, there is a need for a robust quantification method to analyze its vorticity and circulation. We attempt to measure vortex characteristics by means of two-dimensional vorticity maps and vortex circulation. First, we develop vortex component analysis by segmenting the vortices using an data clustering algorithm before histograms of their vorticity distribution are generated. The next stage is to generate the statistics of the vorticity maps for each phase of the cardiac cycle to allow analysis of the flow. This is followed by evaluating the circulation of each segmented vortex. The proposed approach is dedicated to examining vortices within the human heart chamber. The vorticity field can indicate the strength and number of large-scale vortices in the chamber. We provide the results of the flow analysis after vorticity map segmentation and the statistical properties that characterize the vorticity components. The success of the cardiac measurement and analysis is illustrated by a case study of the right atrium. Our investigation shows that it is possible to utilize a data clustering algorithm to segment vortices after vorticity mapping, and that the vorticity and circulation analysis of a chamber vorticity can provide new insights into the blood flow within the cardiovascular structure.
aSchool of Aerospace, Mechanical & Manufacturing Engineering, RMIT University, PO Box 71, Bundoora, VIC 3083, Australia
bCenter for Biomedical Engineering and School of Electrical & Electronics Engineering, University of Adelaide, SA 5005, Australia
cSchool of Mechanical Engineering, University of Adelaide, SA 5005, Australia
dSchool of Medicine, University of Adelaide, and Department of Cardiology, Royal Adelaide Hospital, SA 5005, Australia
Corresponding author at: School of Aerospace, Mechanical & Manufacturing Engineering, RMIT University, PO Box 71, Bundoora, VIC 3083, Australia. Tel.: +61 03 9925 6164.
☆ The authors developed and use a medical image processing software named Medflovan to produce the results displayed in this paper. This is a system entirely created using the C++ object-oriented programming platform to provide cardiac flow visualization and analysis. Cardiac flow computation and visualization is performed on a Pentium 4-class processor on a dedicated graphics card with 512MB of memory.