Using Cardiac Ionic Cell Models to Interpret Clinical Data

Research output: Contribution to journalReview articlepeer-review


For over 100 years cardiac electrophysiology has been measured in the clinic. The electrical signals
that can be measured span from non-invasive 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.
Original languageEnglish
JournalPhilosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
Publication statusAccepted/In press - 2020


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