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Analysis and computer program for rupture-risk prediction of abdominal aortic aneurysms
BACKGROUND: Ruptured abdominal aortic aneurysms (AAAs) are the 13(th )leading cause of death in the United States. While AAA rupture may occur without significant warning, its risk assessment is generally based on critical values of the maximum AAA diameter (>5 cm) and AAA-growth rate (>0.5 cm...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2006
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1421417/ https://www.ncbi.nlm.nih.gov/pubmed/16529648 http://dx.doi.org/10.1186/1475-925X-5-19 |
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author | Kleinstreuer, Clement Li, Zhonghua |
author_facet | Kleinstreuer, Clement Li, Zhonghua |
author_sort | Kleinstreuer, Clement |
collection | PubMed |
description | BACKGROUND: Ruptured abdominal aortic aneurysms (AAAs) are the 13(th )leading cause of death in the United States. While AAA rupture may occur without significant warning, its risk assessment is generally based on critical values of the maximum AAA diameter (>5 cm) and AAA-growth rate (>0.5 cm/year). These criteria may be insufficient for reliable AAA-rupture risk assessment especially when predicting possible rupture of smaller AAAs. METHODS: Based on clinical evidence, eight biomechanical factors with associated weighting coefficients were determined and summed up in terms of a dimensionless, time-dependent severity parameter, SP(t). The most important factor is the maximum wall stress for which a semi-empirical correlation has been developed. RESULTS: The patient-specific SP(t) indicates the risk level of AAA rupture and provides a threshold value when surgical intervention becomes necessary. The severity parameter was validated with four clinical cases and its application is demonstrated for two AAA cases. CONCLUSION: As part of computational AAA-risk assessment and medical management, a patient-specific severity parameter 0 < SP(t) < 1.0 has been developed. The time-dependent, normalized SP(t) depends on eight biomechanical factors, to be obtained via a patient's pressure and AAA-geometry measurements. The resulting program is an easy-to-use tool which allows medical practitioners to make scientific diagnoses, which may save lives and should lead to an improved quality of life. |
format | Text |
id | pubmed-1421417 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-14214172006-04-01 Analysis and computer program for rupture-risk prediction of abdominal aortic aneurysms Kleinstreuer, Clement Li, Zhonghua Biomed Eng Online Research BACKGROUND: Ruptured abdominal aortic aneurysms (AAAs) are the 13(th )leading cause of death in the United States. While AAA rupture may occur without significant warning, its risk assessment is generally based on critical values of the maximum AAA diameter (>5 cm) and AAA-growth rate (>0.5 cm/year). These criteria may be insufficient for reliable AAA-rupture risk assessment especially when predicting possible rupture of smaller AAAs. METHODS: Based on clinical evidence, eight biomechanical factors with associated weighting coefficients were determined and summed up in terms of a dimensionless, time-dependent severity parameter, SP(t). The most important factor is the maximum wall stress for which a semi-empirical correlation has been developed. RESULTS: The patient-specific SP(t) indicates the risk level of AAA rupture and provides a threshold value when surgical intervention becomes necessary. The severity parameter was validated with four clinical cases and its application is demonstrated for two AAA cases. CONCLUSION: As part of computational AAA-risk assessment and medical management, a patient-specific severity parameter 0 < SP(t) < 1.0 has been developed. The time-dependent, normalized SP(t) depends on eight biomechanical factors, to be obtained via a patient's pressure and AAA-geometry measurements. The resulting program is an easy-to-use tool which allows medical practitioners to make scientific diagnoses, which may save lives and should lead to an improved quality of life. BioMed Central 2006-03-10 /pmc/articles/PMC1421417/ /pubmed/16529648 http://dx.doi.org/10.1186/1475-925X-5-19 Text en Copyright © 2006 Kleinstreuer and Li; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Kleinstreuer, Clement Li, Zhonghua Analysis and computer program for rupture-risk prediction of abdominal aortic aneurysms |
title | Analysis and computer program for rupture-risk prediction of abdominal aortic aneurysms |
title_full | Analysis and computer program for rupture-risk prediction of abdominal aortic aneurysms |
title_fullStr | Analysis and computer program for rupture-risk prediction of abdominal aortic aneurysms |
title_full_unstemmed | Analysis and computer program for rupture-risk prediction of abdominal aortic aneurysms |
title_short | Analysis and computer program for rupture-risk prediction of abdominal aortic aneurysms |
title_sort | analysis and computer program for rupture-risk prediction of abdominal aortic aneurysms |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1421417/ https://www.ncbi.nlm.nih.gov/pubmed/16529648 http://dx.doi.org/10.1186/1475-925X-5-19 |
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