Characterizing the Left Ventricular Ultrasound Dynamics in the Frequency Domain to Estimate the Cardiac Function

Andrés Felipe Carrera-Pinzón, Leonard Toro-Quitian, Juan Camilo Torres, Alexander Cerón, Wilson J. Sarmiento, Arnold Mendez-Toro, Angel Cruz-Roa, R. E. Gutiérrez-Carvajal, Carlos Órtiz Davila, Fabio A. González, Eduardo Romero, Marcela Iregui Guerrero

Abstract: Assessment of cardiac function typically relies on the Left Ventricular Ejection Fraction (LVEF), i.e., the ratio between diastolic and systolic volumes. However, inconsistent LVEF values have been reported in many clinic situations. This study introduces a novel approach to quantify the cardiac function by analyzing the frequency patterns of the segmented Left Ventricle (LV) along the entire cardiac cycle in the four-chamber-image of echocardiography videos. After automatic segmentation of the left ventricle, the area is computed during a complete cycle and the obtained signal is transformed to the frequency space. A soft clustering of the spectrum magnitude was performed with 7.835 cases from the EchoNet-dynamic open database by applying spectral clustering with Euclidean distance and eigengap heuristics to obtain four dense groups. Once groups were set, the medoid of each was used as representant, and for a set of 99 test cases from a local collection with different underlying pathology, the magnitude distance to the medoid was replaced by the norm of the sum of vectors representing both the medoid and a particular case making an angle estimated from the dot product between the temporal signals obtained from the inverse Fourier transform of the spectrum phase of each and a constant magnitude. Results show the four clusters characterize different types of patterns, and while LVEF was usually spread within clusters and mixed up the clinic condition, the new indicator showed a narrow progression consistent with the particular pathology degree.