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WIREs Syst Biol Med
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Using cardiac ionic cell models to interpret clinical data

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Abstract For over 100 years cardiac electrophysiology has been measured in the clinic. The electrical signals that can be measured span from noninvasive ECG and body surface potentials measurements through to detailed invasive measurements of local tissue electrophysiology. These electrophysiological measurements form a crucial component of patient diagnosis and monitoring; however, it remains challenging to quantitatively link changes in clinical electrophysiology measurements to biophysical cellular function. Multi‐scale biophysical computational models represent one solution to this problem. These models provide a formal framework for linking cellular function through to emergent whole organ function and routine clinical diagnostic signals. In this review, we describe recent work on the use of computational models to interpret clinical electrophysiology signals. We review the simulation of human cardiac myocyte electrophysiology in the atria and the ventricles and how these models are being used to link organ scale function to patient disease mechanisms and therapy response in patients receiving implanted defibrillators, \cardiac resynchronisation therapy or suffering from atrial fibrillation and ventricular tachycardia. There is a growing use of multi‐scale biophysical models to interpret clinical data. This allows cardiologists to link clinical observations with cellular mechanisms to better understand cardiopathophysiology and identify novel treatment strategies. This article is categorized under: Cardiovascular Diseases > Computational Models Cardiovascular Diseases > Biomedical Engineering Cardiovascular Diseases > Molecular and Cellular Physiology
Left: representative noninvasive 12 lead ECG. Right: ECGi measurements showing the wireframe mesh of the torso electrodes and the epicardium of the ventricles, colored according to compute epicardial potentials
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Models of left atrial electrophysiology derived from invasive electroanatomical mapping (EAM) measurements using the modified Mitchell‐Schafer (Corrado & Niederer, 2016) cell model. Bi‐atrial models derived from cardiac MRI using the Courtemanche (Courtemanche et al., 1998) cell model. Ventricle models using the ten Tusscher and Panfilov (2006a) cell model for MRI derived left ventricle CRT models, bi‐ventricle CRT model derived from computed tomography (CT) and MRI derived left ventricle simulation of ventricle tachycardia
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Reprehensive membrane potential traces of human epicardial cardiac myocyte cell models at 1 Hz pacing frequency. All cells were stimulated at 1 Hz and paced for 2,000 s to reach a limit cycle. Models are presented from top left to bottom right in chronological order
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Representative membrane potential traces of human atrial cardiac myocyte cell model at 1 Hz pacing frequency. All cells were stimulated at 1 Hz and paced for 2,000 s to reach a limit cycle. Models are presented from top left to bottom right in chronological order
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Representative invasive measurements of intracardiac electrograms (EGM) and monophasic action potentials (MAP) in the atria and ventricles. Bipolar EGM (left column) are less sensitive to far field effect, when compared to unipolar EGM (central column), while MAP reproduces the shape of the action potential (right column). Differently from ventricular EGM (bottom row), atrial EGM (top row) do not present signal during repolarization
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