Literature DB >> 17425468

Acoustic detection of coronary artery disease.

John Semmlow1, Ketaki Rahalkar.   

Abstract

Coronary artery disease (CAD) occurs when the arteries to the heart (the coronary arteries) become blocked by deposition of plaque, depriving the heart of oxygen-bearing blood. This disease is arguably the most important fatal disease in industrialized countries, causing one-third to one-half of all deaths in persons between the ages of 35 and 64 in the United States. Despite the fact that early detection of CAD allows for successful and cost-effective treatment of the disease, only 20% of CAD cases are diagnosed prior to a heart attack. The development of a definitive, noninvasive test for detection of coronary blockages is one of the holy grails of diagnostic cardiology. One promising approach to detecting coronary blockages noninvasively is based on identifying acoustic signatures generated by turbulent blood flow through partially occluded coronary arteries. In fact, no other approach to the detection of CAD promises to be as inexpensive, simple to perform, and risk free as the acoustic-based approach. Although sounds associated with partially blocked arteries are easy to identify in more superficial vessels such as the carotids, sounds from coronary arteries are very faint and surrounded by noise such as the very loud valve sounds. To detect these very weak signals requires sophisticated signal processing techniques. This review describes the work that has been done in this area since the 1980s and discusses future directions that may fulfill the promise of the acoustic approach to detecting coronary artery disease.

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Year:  2007        PMID: 17425468     DOI: 10.1146/annurev.bioeng.9.060906.151840

Source DB:  PubMed          Journal:  Annu Rev Biomed Eng        ISSN: 1523-9829            Impact factor:   9.590


  14 in total

1.  The clinical evaluation of the CADence device in the acoustic detection of coronary artery disease.

Authors:  Joseph L Thomas; Michael Ridner; Jason H Cole; Jeffrey W Chambers; Sabahat Bokhari; Demetris Yannopoulos; Morton Kern; Robert F Wilson; Matthew J Budoff
Journal:  Int J Cardiovasc Imaging       Date:  2018-06-23       Impact factor: 2.357

2.  Model validation for a noninvasive arterial stenosis detection problem.

Authors:  H Thomas Banks; Shuhua Hu; Zackary R Kenz; Carola Kruse; Simon Shaw; John Whiteman; Mark P Brewin; Stephen E Greenwald; Malcolm J Birch
Journal:  Math Biosci Eng       Date:  2014-06       Impact factor: 2.080

Review 3.  A novel approach to diagnosing coronary artery disease: acoustic detection of coronary turbulence.

Authors:  Joseph L Thomas; Simon Winther; Robert F Wilson; Morten Bøttcher
Journal:  Int J Cardiovasc Imaging       Date:  2016-08-31       Impact factor: 2.357

4.  A coupled flow-acoustic computational study of bruits from a modeled stenosed artery.

Authors:  Jung Hee Seo; Rajat Mittal
Journal:  Med Biol Eng Comput       Date:  2012-05-21       Impact factor: 2.602

5.  Path length entropy analysis of diastolic heart sounds.

Authors:  Benjamin Griffel; Mohammad K Zia; Vladamir Fridman; Cesare Saponieri; John L Semmlow
Journal:  Comput Biol Med       Date:  2013-06-06       Impact factor: 4.589

6.  High-order space-time finite element schemes for acoustic and viscodynamic wave equations with temporal decoupling.

Authors:  H T Banks; Malcolm J Birch; Mark P Brewin; Stephen E Greenwald; Shuhua Hu; Zackary R Kenz; Carola Kruse; Matthias Maischak; Simon Shaw; John R Whiteman
Journal:  Int J Numer Methods Eng       Date:  2014-02-07       Impact factor: 3.477

7.  Detection of Coronary Artery Disease Using Multi-Domain Feature Fusion of Multi-Channel Heart Sound Signals.

Authors:  Tongtong Liu; Peng Li; Yuanyuan Liu; Huan Zhang; Yuanyang Li; Yu Jiao; Changchun Liu; Chandan Karmakar; Xiaohong Liang; Mengli Ren; Xinpei Wang
Journal:  Entropy (Basel)       Date:  2021-05-21       Impact factor: 2.524

8.  Danish study of Non-Invasive testing in Coronary Artery Disease (Dan-NICAD): study protocol for a randomised controlled trial.

Authors:  Louise Nissen; Simon Winther; Christin Isaksen; June Anita Ejlersen; Lau Brix; Grazina Urbonaviciene; Lars Frost; Lene Helleskov Madsen; Lars Lyhne Knudsen; Samuel Emil Schmidt; Niels Ramsing Holm; Michael Maeng; Mette Nyegaard; Hans Erik Bøtker; Morten Bøttcher
Journal:  Trials       Date:  2016-05-26       Impact factor: 2.279

9.  Network motif-based method for identifying coronary artery disease.

Authors:  Yin Li; Yan Cong; Yun Zhao
Journal:  Exp Ther Med       Date:  2016-04-27       Impact factor: 2.447

10.  Diagnosing coronary artery disease by sound analysis from coronary stenosis induced turbulent blood flow: diagnostic performance in patients with stable angina pectoris.

Authors:  Simon Winther; Samuel Emil Schmidt; Niels Ramsing Holm; Egon Toft; Johannes Jan Struijk; Hans Erik Bøtker; Morten Bøttcher
Journal:  Int J Cardiovasc Imaging       Date:  2015-09-03       Impact factor: 2.357

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