Abstract
This work presents a mathematical model to describe perfusion dynamics in cardiac tissue. The new model extends a previous one and can reproduce clinical exams of contrast-enhanced cardiac magnetic resonance imaging (MRI) of the left ventricle obtained from patients with cardiovascular diseases, such as myocardial infarct. The model treats the extra- and intravascular domains as different porous media where Darcy’s law is adopted. Reaction-diffusion-advection equations are used to capture the dynamics of contrast agents that are typically used in MRI perfusion exams. The identification of the myocardial infarct region is modeled via adsorption of the contrast agent on the extracellular matrix. Different scenarios were simulated and compared with clinical images: normal perfusion, endocardial ischemia due to stenosis, and myocardial infarct. Altogether, the results obtained suggest that the models can support the process of non-invasive cardiac perfusion quantification.
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This work was supported by UFJF, CAPES, CNPq (Grants 310722/2021-7, 315267/2020-8), and FAPEMIG (Grants APQ-01340-18, APQ 02489/21).
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Gaio, E.D., Rocha, B.M., dos Santos, R.W. (2022). Modeling Contrast Perfusion and Adsorption Phenomena in the Human Left Ventricle. In: Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2022. ICCS 2022. Lecture Notes in Computer Science, vol 13351. Springer, Cham. https://doi.org/10.1007/978-3-031-08754-7_52
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