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PMID: 17425468 Published · ppublish English Journal Article Review

Acoustic detection of coronary artery disease.

Annual review of biomedical engineering ·Vol. 9 ·2007-00-00 ·Pages 449-69

Semmlow J, Rahalkar K

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.

MeSH Terms
Acoustics Animals Blood Flow Velocity Computer Simulation Coronary Artery Disease/diagnosis,physiopathology Heart Auscultation/methods Humans Models, Cardiovascular Signal Processing, Computer-Assisted Sound Spectrography/methods
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Semmlow John
Robert Wood Johnson Medical School, Rutgers University, Piscataway, New Jersey 08854, USA. [email protected]
Rahalkar Ketaki
Article Info
Journal
Annual review of biomedical engineering
Abbr.
Annu Rev Biomed Eng
ISSN
1523-9829
Published
2007-00-00
Pages
449-69
Language
English
Region
United States
NLM ID
100883581
Subset
IM
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