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Current Directions in Biomedical Engineering

Joint Journal of the German Society for Biomedical Engineering in VDE and the Austrian and Swiss Societies for Biomedical Engineering

Editor-in-Chief: Dössel, Olaf

Editorial Board: Augat, Peter / Buzug, Thorsten M. / Haueisen, Jens / Jockenhoevel, Stefan / Knaup-Gregori, Petra / Kraft, Marc / Lenarz, Thomas / Leonhardt, Steffen / Malberg, Hagen / Penzel, Thomas / Plank, Gernot / Radermacher, Klaus M. / Schkommodau, Erik / Stieglitz, Thomas / Urban, Gerald A.


CiteScore 2018: 0.47

Source Normalized Impact per Paper (SNIP) 2018: 0.377

Open Access
Online
ISSN
2364-5504
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Monte-Carlo parameter variation study of cardiovascular pathologies to quantify parameter specific signal uncertainty

Stefan Krickl / Stefan Bernhard
Published Online: 2018-09-22 | DOI: https://doi.org/10.1515/cdbme-2018-0091

Abstract

Cardiovascular diseases are the leading cause of death worldwide. Early detection of abnormal vascular morphologies like aneurysms in the abdominal (abdominal aortic aneurysm, AAA) or thoracic aorta (thoracic aortic aneurysm, TAA) are essential to prevent fatal events. The aim of this study is the development of a patient-specific simulation model to obtain statistical information about ab- /normal pressure-flow conditions to improve the basic understanding and methods for the early detection of diseases. For this purpose, the numerical cardiovascular modeling tool SISCA was used, to generate a series of simulations by Monte- Carlo parameter variation. The considered variational scenario was built upon a control group of normal patients, deriving two pathological conditions for AAA and TAA with different severity and location. Therefore, the nominal diameters were enlarged between 200 % and 500 %, while the length of the aneurysms were modified within a range of 30 and 90 mm. Within each statistical set the convergence was tested by the bootstrap method ensuring that within a set of 3500 runs a 2 % deviation error of the mean value of the blood pressure was obtained compared to a set of 10000 runs.The parameter variation method allows the generation of disease specific data in the context of physiological/clinical findings and consequently the disease specific quantification of signal uncertainties and variances.

Keywords: Cardiovascular pathologies; aneurysms; pressure-flow signal; bootstrap; Monte-Carlo; latin hypercube sampling; sensitivity analysis

About the article

Published Online: 2018-09-22

Published in Print: 2018-09-01


Citation Information: Current Directions in Biomedical Engineering, Volume 4, Issue 1, Pages 379–383, ISSN (Online) 2364-5504, DOI: https://doi.org/10.1515/cdbme-2018-0091.

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