Cardiac flow component analysis

• Published in: Medical engineering & physics Vol. 32; no. 2; pp. 174 - 188
• Main Authors: Wong, Kelvin K.L., Tu, Jiyuan, Kelso, Richard M., Worthley, Stephen G., Sanders, Prashanthan, Mazumdar, Jagannath, Abbott, Derek
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.03.2010; Elsevier
• Subjects: Algorithms; Atrial Function, Right; Biological and medical sciences; Biomechanical Phenomena; Biomechanics. Biorheology; Circulation; Component flow analysis; Coronary Circulation; Data clustering; Fundamental and applied biological sciences. Psychology; Hemodynamics. Rheology; Humans; Kinetics; Magnetic Resonance Imaging; Male; Phase contrast magnetic resonance imaging; Radiology; Segmentation; Tissues, organs and organisms biophysics; Vertebrates: cardiovascular system; Vorticity; Young Adult; Phase contrast magnetic resonance imaging; Segmentation; Component flow analysis; Circulation; Vorticity; Data clustering; Heart; Human; Image processing; Theoretical study; Experimental study; Algorithm; Nuclear magnetic resonance imaging; Blood flow; Biomechanics; Phase contrast; Medical imagery; Circulatory system; Hemodynamics; Measurement method; Mathematical model; Right atrium; Principal component analysis; Biomedical engineering
• ISSN: 1350-4533; 1873-4030; 1873-4030
• DOI: 10.1016/j.medengphy.2009.11.007

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.