Literature DB >> 16085094

Doppler echocardiography flow-velocity image analysis for patients with atrial fibrillation.

Hayit Greenspan1, Oron Shechner, Mickey Scheinowitz, Micha S Feinberg.   

Abstract

Currently, Doppler echocardiography analysis is performed manually. An automated method that analyzes the Doppler signal can potentially improve accuracy and result in a powerful tool for noninvasive evaluation of cardiac hemodynamics, especially for patients with atrial fibrillation, where multiple samples are needed to obtain an accurate averaged measurement. The aim of this study was to develop an automated method for Doppler analysis based on image processing and computer vision algorithms. Images were obtained from the mitral valve and the tricuspid valve Doppler tracings from 45 patients, 20 with normal sinus rhythm and 25 with atrial fibrillation. The proposed algorithm automatically detects the maximal velocity envelope of the spectral Doppler ultrasound tracings. Averaged values for the time velocity integral, peak mitral inflow velocity and peak tricuspid regurgitation velocity were calculated for multiple beats available in a single screen frame. Measurements extracted automatically from the maximal velocity envelope were compared to measurements obtained manually by two expert technicians. High linear correlation (r) was found between the automatically- and the manually-extracted parameters (0.95 < r < 0.99). A smaller variation was found in most cases between the manually-calculated average beat and the automated average beat (bias value between 3.8% and 5.2%) than between the manually-calculated average beat and the selection of a representative beat (bias value between 6.2% and -2.6%). The newly-developed automated method offers a new, accurate and reliable clinical tool, particularly for the assessment of patients with irregular heart rate.

Entities:  

Mesh:

Year:  2005        PMID: 16085094     DOI: 10.1016/j.ultrasmedbio.2005.04.016

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   2.998


  4 in total

Review 1.  Harnessing Machine Intelligence in Automatic Echocardiogram Analysis: Current Status, Limitations, and Future Directions.

Authors:  Ghada Zamzmi; Li-Yueh Hsu; Wen Li; Vandana Sachdev; Sameer Antani
Journal:  IEEE Rev Biomed Eng       Date:  2021-01-22

2.  A new automated system to identify a consistent sampling position to make tissue Doppler and transmitral Doppler measurements of E, E' and E/E'.

Authors:  Niti M Dhutia; Graham D Cole; Keith Willson; Daniel Rueckert; Kim H Parker; Alun D Hughes; Darrel P Francis
Journal:  Int J Cardiol       Date:  2010-11-20       Impact factor: 4.164

3.  Extraction of Peak Velocity Profiles from Doppler Echocardiography Using Image Processing.

Authors:  Amirtahà Taebi; Richard H Sandler; Bahram Kakavand; Hansen A Mansy
Journal:  Bioengineering (Basel)       Date:  2019-07-26

4.  Open-source, vendor-independent, automated multi-beat tissue Doppler echocardiography analysis.

Authors:  Niti M Dhutia; Massoud Zolgharni; Michael Mielewczik; Madalina Negoita; Stefania Sacchi; Karikaran Manoharan; Darrel P Francis; Graham D Cole
Journal:  Int J Cardiovasc Imaging       Date:  2017-02-20       Impact factor: 2.357

  4 in total

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