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Classification of cardiac adipose tissue using spectral analysis of ultrasound radiofrequency backscatter
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Paper Abstract

Cardiac Adipose Tissue (CAT) is a type of visceral fat that is deposited between the myocardium and pericardium. An increased volume of CAT has been recognized as a crucial contributor to cardiovascular and coronary artery diseases. This tissue is a metabolically active organ that affects the cardiac functioning by secreting inflammatory adipokines making it a hazard when present in excess amounts. Quantifying CAT, therefore, can be an important factor in understanding the level of cardiovascular risk. The study presented in this paper investigates the use of frequency content from echocardiography and spectral analysis techniques in differentiating three different cardiac tissue types, including the adipose tissue. Thirteen spectral parameters were computed from the power spectrum of the radio frequency data in three different bandwidth ranges, including 3, 6 and 20 dB. Autoregressive models of order 4 were used as they provide effective estimates of the power spectrum for short-time data. The derived spectral parameters were used in generating random forests for tissue classification. Out of the total 175 ROIs available, 70% of the data was divided into training data and the remaining used as test data. The random forest classifier with 50 classification trees resulted in an overall accuracy of 92.4%, sensitivity of 91.1%, specificity of 93.9%, and Youden’s index of 0.85 for a 20dB bandwidth. This result demonstrates the potential of echocardiography and spectral analysis techniques in differentiating CAT, myocardium, and blood.

Paper Details

Date Published: 15 March 2019
PDF: 8 pages
Proc. SPIE 10955, Medical Imaging 2019: Ultrasonic Imaging and Tomography, 109550F (15 March 2019); doi: 10.1117/12.2512972
Show Author Affiliations
Akhila Karlapalem, Southern Illinois Univ. Edwardsville (United States)
Amy H. Givan, Southern Illinois Univ. Edwardsville (United States)
Maria Fernandez-del-Valle, Southern Illinois Univ. Edwardsville (United States)
Miranda R. Fulton, Southern Illinois Univ. Edwardsville (United States)
Jon D. Klingensmith, Southern Illinois Univ. Edwardsville (United States)


Published in SPIE Proceedings Vol. 10955:
Medical Imaging 2019: Ultrasonic Imaging and Tomography
Brett C. Byram; Nicole V. Ruiter, Editor(s)

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