Key result
Cardiac force models balance subcellular accuracy against the number of parameters requiring experimental estimation.
Why the study?
Cardiac in silico numerical simulations require mathematical models of physical processes, prompting a survey of biophysically-detailed models of active force generation and the trade-off between subcellular accuracy and parameter estimation.
This review highlights mathematical models of cardiac actin-myosin interaction, emphasizing a generalized Huxley model that balances biophysical detail with parameter identifiability for multiscale cardiac simulations.
Cardiac model selection must weigh mechanistic detail against identifiability; leaves open optimal complexity for multiscale simulations.
Cardiac in silico numerical simulations are based on mathematical models describing the physical processes involved in the heart function. In this review paper, we critically survey biophysically-detailed mathematical models describing the subcellular mechanisms behind the generation of active force, that is the process by which the chemical energy of ATP (adenosine triphosphate) is transformed into mechanical work, thus making the muscle tissue contract. While presenting these models, that feature different levels of biophysical detail, we analyze the trade-off between the accuracy in the description of the subcellular mechanisms and the number of parameters that need to be estimated from experiments. Then, we focus on a generalized version of the classic Huxley model, built on the basis of models available in the literature, that is able to reproduce the main experimental characterizations associated to the time scales typical of a heartbeat-such as the force-velocity relationship and the tissue stiffness in response to small steps-featuring only four independent parameters. Finally, we show how those parameters can be calibrated starting from macroscopic measurements available from experiments.
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Regazzoni et al. (2020) conducted a review in Cardiac muscle contraction. Mathematical models of active force generation in cardiac muscle cells require a trade-off between the accuracy of subcellular mechanisms and the number of parameters needing experimental estimation.
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