At the heart of computational modelling

Abstract

The link between experimental data and biophysically based mathematical models is key to computational simulation meeting its potential to provide physiological insight. However, despite the importance of this link, scrutiny and analysis of the processes by which models are parameterised from data are currently lacking. While this situation is common to many areas of physiological modelling, to provide a concrete context, we use examples drawn from detailed models of cardiac electro-mechanics. Using this biophysically detailed cohort of models we highlight the specific issues of model parameterization and propose this process can be separated into three stages: observation, fitting and validation. Finally, future research challenges and directions in this area are discussed.

Figure 1

Schematic showing the multi-scale relationship between cellular electrophysiology and contraction and whole organ activation and deformation

Figure 2. Example multi-scale excitation contraction models

Top and bottom panels show end diastolic and end systolic cardiac models, respectively. A, fibre strain patterns in human CRT patient heart, –0.15 blue to +0.15 red (Aguado-Sierra et al. 2011), B, regional work patterns in CRT patient case; yellow spheres correspond to scar, blue and red spheres correspond to shortening and elongating myocardium, and the size of the spheres correspond to the magnitude of the work rate (Niederer et al. 2011a). C, generic heart model, showing membrane potential, blue –80mV to red +20 mV (Nickerson et al. 2005). D, fibre orientation in the canine myocardium, where colours trace individual fibres (Gurev et al. 2011).

Figure 3. Computational model phylogenic tree showing the experimental data dependencies of the Bondorenko et al. (2004) (A) and Li et al. (2010) (B) models

Trapeziums correspond to modelling studies. Squares correspond to model components (ion channels, buffers, transporters, etc.). Ellipses correspond to experimental studies. The colour scheme corresponds to the temperature of the data and the letters correspond to the species where M is mouse, GP is guinea pig, H is human, Rat is rat, S is sheep, SF is starfish, X is Xenopus, C is canine, F is ferret, Ca is calf, Ne is neuron, BF is bullfrog, SA is squid axon, B is bovine, R is rabbit and NA is not defined.