Personalized Models of Human Atrial Electrophysiology Derived From Endocardial Electrograms

Objective : Computational models represent a novel framework for understanding the mechanisms behind atrial fibrillation (AF) and offer a pathway for personalizing and optimizing treatment. The characterization of local electrophysiological properties across the atria during procedures remains a cha...

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Vydané v:IEEE transactions on biomedical engineering Ročník 64; číslo 4; s. 735 - 742
Hlavní autori: Corrado, Cesare, Whitaker, John, Chubb, Henry, Williams, Steven, Wright, Matthew, Gill, Jaswinder, O'Neill, Mark D., Niederer, Steven A.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States IEEE 01.04.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Atria
Atrial fibrillation (AF)
Atrial Fibrillation - diagnosis
Atrial Fibrillation - physiopathology
Atrial Function
Atrium
Biological system modeling
Body Surface Potential Mapping - methods
catheter measurements
Catheters
computational model
Computational modeling
Computer applications
Computer Simulation
Conduction
conduction velocity
Customization
Diagnosis, Computer-Assisted - methods
Dimensional stability
effective refractory periods
Electric potential
Electrodes
electrograms
Electrophysiologic Techniques, Cardiac - methods
Electrophysiology
Endocardium - physiopathology
Errors
Fibrillation
Heart Conduction System - physiopathology
Humans
Mathematical models
Measurement methods
Medical instruments
model personalization
Models, Cardiovascular
Numerical models
Parameter estimation
Parameter identification
Parameterization
Properties (attributes)
Protocols
Refractory period
Reproducibility of Results
restitution curves
Sensitivity and Specificity
Sheet modelling
Two dimensional models
Velocity
ISSN:0018-9294, 1558-2531
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Shrnutí:Objective : Computational models represent a novel framework for understanding the mechanisms behind atrial fibrillation (AF) and offer a pathway for personalizing and optimizing treatment. The characterization of local electrophysiological properties across the atria during procedures remains a challenge. The aim of this work is to characterize the regional properties of the human atrium from multielectrode catheter measurements. Methods : We propose a novel method that characterizes regional electrophysiology properties by fitting parameters of an ionic model to conduction velocity and effective refractory period restitution curves obtained by a <inline-formula><tex-math notation="LaTeX">s_\text{1}\_ s_\text{2}</tex-math></inline-formula> pacing protocol applied through a multielectrode catheter. Using an in-silico dataset we demonstrate that the fitting method can constrain parameters with a mean error of <inline-formula><tex-math notation="LaTeX">21.9\pm 16.1\%</tex-math></inline-formula> and can replicate conduction velocity and effective refractory curves not used in the original fitting with a relative error of <inline-formula><tex-math notation="LaTeX">4.4\pm 6.9\%</tex-math></inline-formula>. Results : We demonstrate this parameter estimation approach on five clinical datasets recorded from AF patients. Recordings and parametrization took approx. 5 and 6 min, respectively. Models fitted restitution curves with an error of <inline-formula><tex-math notation="LaTeX">\sim 5\%</tex-math></inline-formula> and identify a unique parameter set. Tissue properties were predicted using a two-dimensional atrial tissue sheet model. Spiral wave stability in each case was predicted using tissue simulations, identifying distinct stable (2/5), meandering and breaking up (2/5), and unstable self-terminating (1/5) spiral tip patterns for different cases. Conclusion and significance : We have developed and demonstrated a robust and rapid approach for personalizing local ionic models from a clinically tractable protocol to characterize cellular properties and predict tissue electrophysiological function.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0018-9294
1558-2531
DOI:10.1109/TBME.2016.2574619