DocumentCode :
3562242
Title :
Constructing human atrial electrophysiological models mimicking a patient-specific cell group
Author :
Muszkiewicz, A. ; Bueno-Orovio, A. ; Liu, X. ; Casadei, B. ; Rodriguez, B.
Author_Institution :
Dept. of Comput. Sci., Univ. of Oxford, Oxford, UK
fYear :
2014
Firstpage :
761
Lastpage :
764
Abstract :
Patient-specific modelling aims to produce computational models of human physiology tailored to a specific patient. In line with this, we construct multiple human atrial electrophysiological models mimicking the behaviour of single atrial myocytes extracted from a homogeneous patient group. We study cells with the action potential duration being 2-3 times lower than in human atrial electrophysiological models. Assuming such a difference can be rationalized by altering the values of ionic conductances, we generated 15000 models by simultaneously varying conductance values of the most important currents affecting the action potential (AP). We paced the models at different frequencies and conditions, probing the importance of ion concentrations and stimulus strength, and kept the models producing AP biomarkers consistent with experiments. We discovered that both the ionic conductances and external factors play a critical role in producing biomarker values consistent with experiments. By mimicking experimental conditions, we generated 604 models fully covering the experimental range of AP biomarkers. In conclusion, both the ionic conductances and external factors are vital in tailoring single-cell electrophysiological models to a narrow patient group. This has implications in understanding the propensity of subgroups of the total population to disease conditions.
Keywords :
bioelectric potentials; cellular biophysics; diseases; ionic conductivity; AP biomarkers; action potential; computational models; disease conditions; homogeneous patient group; human atrial electrophysiological model mimicking; human physiology; ionic conductances; patient-specific cell group; patient-specific modelling; single atrial myocyte extraction; single-cell electrophysiological models; Biological system modeling; Calcium; Computational modeling; Data models; Electric potential; Sociology; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing in Cardiology Conference (CinC), 2014
ISSN :
2325-8861
Print_ISBN :
978-1-4799-4346-3
Type :
conf
Filename :
7043154
Link To Document :
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