NDLI: Multiobjective patient-specific estimation of a coronary circulation model for triple vessel disease

Content Provider	IEEE Xplore Digital Library
Author	Ojeda, D. Le Rolle, V. Drochon, A. Harmouche, M. Corbineau, H. Verhoye, J.-P. Hernandez, A.I.
Copyright Year	2013
Description	Author affiliation: INSERM, Rennes, France (Ojeda, D.; Le Rolle, V.; Harmouche, M.; Corbineau, H.; Verhoye, J.-P.; Hernandez, A.I.) \|\| Univ. of Technol. of Compiegne, Compiegne, France (Drochon, A.)
Abstract	Computational models can help understand the hemodynamics of the coronary circulation, which is of the upmost importance to help clinicians before, during and after a coronary artery bypass graft surgery. In this paper, we propose a multiobjective optimization method for parameter estimation of a computational model representing the coronary circulation on patients with a triple vessel disease. This estimation was not based on any assumption regarding the development of the collateral circulation, like in previous works. Indeed, the collateral development of a given patient is estimated through the model parameters. Parameter estimation was performed using clinical data from three patients, obtained before and during an off-pump coronary artery bypass graft surgery (CABG). Results showed a better performance when comparing the simulation with clinical data, since the total error estimation for three patients was reduced by 40 ± 22%. Moreover, the proposed method provides new insight regarding the heterogeneous configuration of the alternative collateral vessels.
Starting Page	3877
Ending Page	3880
File Size	333646
Page Count	4
File Format	PDF
ISBN	9781457702167
ISSN	1557170X
DOI	10.1109/EMBC.2013.6610391
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-03
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Arteries Sociology Statistics Solid modeling Estimation Diseases Computational modeling
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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