E.N. Rubtsova1, A.A. Pugovkin2, A.V. Koroteev3, D.V. Telyshev4

1,4 Institute of Biomedical Systems, National Research University of Electronic Technology (Moscow, Russia)
1–4 I.M. Sechenov First Moscow State Medical University (Moscow, Russia)
1 rubtsova_e_n@staff.sechenov.ru, 2 pugovkin_a_a@staff.sechenov.ru, 3 koroteev_a_v@staff.sechenov.ru,
4 telyshev_d_v@staff.sechenov.ru

Univentricular palliation is performed in patients with congenital heart defects, such as single functional ventricle, hypoplasia, septal defects, valve defects, obstructive defects, etc. After the palliation, the single ventricle becomes systemic, and venae cavae are directly or indirectly connected to pulmonary arteries. Palliated patients may temporary lead a full life yet eventually need heart transplantation. Mechanical circulatory support (MCS) may be an alternative treatment for heart transplantation in patients having univentricular circulation. Personalized modeling of a biotechnical MCS system allows to forecast current and optimal system states and assess support advisability and efficacy before implanting a circulatory assist device. In this study, a mathematical model of univentricular circulation with possibility to connect a circulatory assist device is presented. An algorithm for efficacy forecast and assessment of personalized mechanical univenricular circulatory support was developed. The algorithm automatically determines circulatory model parameters based on patient’s hemodynamic data and a set of parameter templates for corresponding age groups and circulatory states. This first stage is based on genetic algorithm with model parameters used as a genotype. Criterion of obtaining personalized model parameters is a zero sum of relative deviations of patient’s hemodynamic data and simulated data after personalization given the acceptable ranges of deviations determined based on accuracy of clinical diagnostic devices. At the second stage, the developed algorithm simulates a personalized biotechnical system of mechanical univentricular circulatory support using personalized circulatory model and pressure head–flow rate characteristics of circulatory assist device. At the third stage, the algorithm assesses advisability of chosen control strategy with negative recommendation for inadvisable strategy. At the last stage, the algorithm forecasts optimal states of biotechnical system determined as sufficiently approximate to normal circulation. Verification of the developed algorithm was performed with patients’ hemodynamic data from literature. Distributions of hemodynamic parameters in simulated biotechnical systems for three patients are described along with forecast optimal states and corresponding values of control parameter for chosen methods of support. In these cases, pediatric rotary blood pump previously developed by our research group was used as circulatory assist device. Assessment of changes in biotechnical system after implantation of circulatory assist device revealed inefficacy of MCS in one of three considered patients.

Rubtsova E.N., Pugovkin A.A., Koroteev A.V., Telyshev D.V. Efficacy assessment of strategies for mechanical univentricular circulatory support. Dynamics of complex systems. 2024. V. 18. № 1. P. 41−50. DOI: 10.18127/j19997493-202401-04 (in Russian).

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