Literature DB >> 30969919

Detection of Regional Mechanical Activation of the Left Ventricular Myocardium Using High Frame Rate Ultrasound Imaging.

Kaja F Kvale, Jorn Bersvendsen, Espen W Remme, Sebastien Salles, John M Aalen, Pal H Brekke, Thor Edvardsen, Eigil Samset.   

Abstract

We have investigated the feasibility of noninvasive mapping of mechanical activation patterns in the left ventricular (LV) myocardium using high frame rate ultrasound imaging for the purpose of detecting conduction abnormalities. Five anesthetized, open-chest dogs with implanted combined sonomicrometry and electromyography (EMG) crystals were studied. The animals were paced from the specified locations of the heart, while crystal and ultrasound data were acquired. Isochrone maps of the mechanical activation patterns were generated from the ultrasound data using a novel signal processing method called clutter filter wave imaging (CFWI). The isochrone maps showed the same mechanical activation pattern as the sonomicrometry crystals in 90% of the cases. For electrical activation, the activation sequences from ultrasound were the same in 92% of the cases. The coefficient of determination between the activation delay measured with EMG and ultrasound was R 2 = 0.79 , indicating a strong correlation. These results indicate that high frame rate ultrasound imaging processed with CFWI has the potential to be a valuable tool for mechanical activation detection.

Entities:  

Year:  2019        PMID: 30969919     DOI: 10.1109/TMI.2019.2909358

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  2 in total

1.  Electromechanical Wave Imaging With Machine Learning for Automated Isochrone Generation.

Authors:  Lea Melki; Melina Tourni; Elisa E Konofagou
Journal:  IEEE Trans Med Imaging       Date:  2021-08-31       Impact factor: 11.037

2.  Stepwise local stitching ultrasound image algorithms based on adaptive iterative threshold Harris corner features.

Authors:  Hongfei Sun; Jianhua Yang; Rongbo Fan; Kai Xie; Conghui Wang; Xinye Ni
Journal:  Medicine (Baltimore)       Date:  2020-09-11       Impact factor: 1.889

  2 in total

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