Cardiac adipose tissue (CAT), the fat layer surrounding the heart and vessels, can lead to serious heart issues when it is above a certain volume, causing the plaque to build-up in the walls of arteries and making the walls narrow and harden in time. Excessive cardiac adiposity has been associated with coronary atherosclerosis, cardiac dysfunction and myocardial infarction.
Observing CAT using echocardiographic imaging can potentially be a far more costeffective and more accessible option compared to magnetic resonance imaging (MRI). The purpose of this research is to identify the tools and parameters to reverse engineer threedimensional (3D) solid CAT models in order to investigate the potential of using echocardiographic imaging to analyze the volume and distribution of CAT.
A 3D modeling software, NX by Siemens, is used on synthetic and patient cardiac fat models to create cross-sectional spline curves in different levels of complexity to serve as registered inputs from echocardiographic images. These curves are then connected using two separate surface generation tools in order to create the CAT boundaries, which results in the constructed 3D solid model. The accuracy of CAT distribution is calculated by measuring the Boolean intersection volume between the original and constructed 3D models. Experimental results show a promising evidence that accurate 3DCAT models can be created from echocardiography images as a viable alternative to MRI, typically detecting at least 70% of true CAT distribution and at least 87% of the overall CAT volume.
|Advisor:||Lee, H. Felix|
|Commitee:||Klingensmith, Jon, Cho, Sohyung|
|School:||Southern Illinois University at Edwardsville|
|School Location:||United States -- Illinois|
|Source:||MAI 82/3(E), Masters Abstracts International|
|Subjects:||Industrial engineering, Medical imaging, Biomedical engineering|
|Keywords:||3D modeling, Cardiac fat, Echocardiography|
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