Literature DB >> 24770912

Automated aortic Doppler flow tracing for reproducible research and clinical measurements.

Massoud Zolgharni, Niti M Dhutia, Graham D Cole, M Reza Bahmanyar, Siana Jones, S M Afzal Sohaib, Sarah B Tai, Keith Willson, Judith A Finegold, Darrel P Francis.   

Abstract

In clinical practice, echocardiographers are often unkeen to make the significant time investment to make additional multiple measurements of Doppler velocity. Main hurdle to obtaining multiple measurements is the time required to manually trace a series of Doppler traces. To make it easier to analyze more beats, we present the description of an application system for automated aortic Doppler envelope quantification, compatible with a range of hardware platforms. It analyses long Doppler strips, spanning many heartbeats, and does not require electrocardiogram to separate individual beats. We tested its measurement of velocity-time-integral and peak-velocity against the reference standard defined as the average of three experts who each made three separate measurements. The automated measurements of velocity-time-integral showed strong correspondence (R(2) = 0.94) and good Bland-Altman agreement (SD = 1.39 cm) with the reference consensus expert values, and indeed performed as well as the individual experts ( R(2) = 0.90 to 0.96, SD = 1.05 to 1.53 cm). The same performance was observed for peak-velocities; ( R(2) = 0.98, SD = 3.07 cm/s) and ( R(2) = 0.93 to 0.98, SD = 2.96 to 5.18 cm/s). This automated technology allows > 10 times as many beats to be analyzed compared to the conventional manual approach. This would make clinical and research protocols more precise for the same operator effort.

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Year:  2014        PMID: 24770912     DOI: 10.1109/TMI.2014.2303782

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


  6 in total

1.  Intraoperative Renal Resistive Index as an Acute Kidney Injury Biomarker: Development and Validation of an Automated Analysis Algorithm.

Authors:  Benjamin Y Andrew; Elias Y Andrew; Anne D Cherry; Jennifer N Hauck; Alina Nicoara; Carl F Pieper; Mark Stafford-Smith
Journal:  J Cardiothorac Vasc Anesth       Date:  2018-04-04       Impact factor: 2.628

2.  Defining Coronary Flow Patterns: Comprehensive Automation of Transthoracic Doppler Coronary Blood Flow.

Authors:  Ian L Sunyecz; Patricia E McCallinhart; Kishan U Patel; Michael R McDermott; Aaron J Trask
Journal:  Sci Rep       Date:  2018-11-22       Impact factor: 4.379

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.  Improvement of automated analysis of coronary Doppler echocardiograms.

Authors:  Christopher W Bartlett; William C Ray; Aaron J Trask; Jamie Bossenbroek; Yukie Ueyama; Patricia E McCallinhart
Journal:  Sci Rep       Date:  2022-05-06       Impact factor: 4.996

5.  Elucidating tricuspid Doppler signal interpolation and its implication for assessing pulmonary hypertension.

Authors:  Seraina A Dual; Constance Verdonk; Myriam Amsallem; Jonathan Pham; Courtney Obasohan; Patrick Nataf; Doff B McElhinney; Alisa Arunamata; Tatiana Kuznetsova; Roham Zamanian; Jeffrey A Feinstein; Alison Marsden; François Haddad
Journal:  Pulm Circ       Date:  2022-07-01       Impact factor: 2.886

6.  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

  6 in total

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