Researchers from the Moscow Institute of Physics and Technology, Kazan Federal University, and George Washington University have proposed an algorithm for producing patient-specific mathematical models describing the electrical excitation of human heart cells. Published in PLOS One, the study looks at two possible approaches—one using experimental records of electrical activity and the other based on gene expression profiles.
Each heart contraction is caused by a preceding electrical excitation, the so-called action potential. The latter results from electrical currents through ion channels. The number of such channels forming ion currents varies with both pathological conditions and the individual properties of heart tissue in healthy patients. When the balance between various types of ion currents gets disrupted, this may lead to dangerous arrhythmias and death.
Since many factors are involved in excitation propagation, the studies investigating the basic principles underlying arrhythmia have relied on mathematical models over the past 50 years. Despite the effort behind developing these models, they are so far rarely used in the clinical practice, mainly because they describe a hypothesized average patient. The research reported in this story addresses the challenging task of applying such models to real individual patients.
The first approach discussed in the paper relies on experimental recordings of action potential and subsequent model optimization using dedicated computer algorithms. They employ evolutionary principles to find the parameters that make the model reproduce the experiment. Randomly generated models are subjected to selection, crossover, and mutation. Prior research by a number of scientific groups has identified the key challenge faced by this approach. Namely, it is hard to find the unique solution, because of the numerous distinct combinations of parameters that result in the same action potential waveform.
Study co-author Andrey Pikunov from the MIPT Laboratory of Human Physiology commented: “We have