Impact of uncertainties in cardiac mechanics simulations
Resumo
As simulações do coração têm grande potencial de aplicações em diagnósticos e planejamento de terapias. Porém, tal uso clínico precisa conhecer a confiabilidade das predições devido a erros e incertezas nas entradas destes modelos. Os parâmetros do modelo são difíceis de ser medidos e estão associados a uma incerteza considerável. Além disso, geometrias para pacientes específicos são geradas a partir de imagens médicas envolvendo algum processamento manual, o que as tornam uma potencial fonte de incertezas. Com o objetivo de contribuir para a avaliação da confiabilidade de modelos da mecânica cardíaca, neste estudo foram realizadas análises de quantificação de incertezas e sensibilidade de simulações do ventrículo esquerdo durante o ciclo cardíaco.
Referências
Arevalo, H. J., Vadakkumpadan, F., Guallar, E., Jebb, A., Malamas, P., Wu, K. C., and Trayanova, N. A. (2016). Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models. Nature Com, 7.
Bayer, J. D., Blake, R. C., Plank, G., and Trayanova, N. A. (2012). A novel rule-based algorithm for assigning myocardial fiber orientation to computational heart models. Annals of biomedical engineering, 40(10):2243–2254.
Campos, J., Sundnes, J., Dos, R. S., and Rocha, B. (2019). Effects of left ventricle wall thickness uncertainties on cardiac mechanics. Biomechanics and modeling in mechanobiology, pages 1–13.
Campos, J., Sundnes, J., Dos, R. S., and Rocha, B. (2020). Uncertainty quantification and sensitivity analysis of left ventricular function during the full cardiac cycle. Philosophical Transactions A, 20190381:1–19.
Campos, J. O., Santos, R. W., Sundnes, J., and Rocha, B. M. (2017). Preconditioned augmented lagrangian formulation for nearly incompressible cardiac mechanics. International Journal for Numerical Methods in Biomedical Engineering, 34(4):e2948. e2948 cnm.2948.
Cerqueira, M. D., Weissman, N. J., Dilsizian, V., Jacobs, A. K., Kaul, S., Laskey, W. K., Pennell, D. J., Rumberger, J. A., Ryan, T., Verani, M. S., et al. (2002). Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. Circulation, 105(4):539–542.
Guccione, J. M., McCulloch, A. D., Waldman, L., et al. (1991). Passive material properties of intact ventricular myocardium determined from a cylindrical model. J Biomech Eng, 113(1):42–55.
Kerckhoffs, R., Bovendeerd, P., Kotte, J., Prinzen, F., Smits, K., and Arts, T. (2003). Homogeneity of cardiac contraction despite physiological asynchrony of depolarization: a model study. Annals of biomedical engineering, 31(5):536–547.
Reese, T. G.,Weisskoff, R. M., Smith, R. N., Rosen, B. R., Dinsmore, R. E., andWedeen, V. J. (1995). Imaging myocardial fiber architecture in vivo with magnetic resonance. Magnetic Resonance in Medicine, 34(6):786–791.
Rodríguez-Cantano, R., Sundnes, J., and Rognes, M. E. (2019). Uncertainty in cardiac myofiber orientation and stiffnesses dominate the variability of left ventricle deformation response. International journal for numerical methods in engineering, 79(11):1– 20.
Shavik, S. M., Wall, S. T., Sundnes, J., Burkhoff, D., and Lee, L. C. (2017). Organ-level validation of a cross-bridge cycling descriptor in a left ventricular finite element model: effects of ventricular loading on myocardial strains. Physiological reports, 5(21).
Suinesiaputra, A., Cowan, B. R., Al-Agamy, A. O., Elattar, M. A., Ayache, N., Fahmy, A. S., Khalifa, A. M., Medrano-Gracia, P., Jolly, M.-P., Kadish, A. H., et al. (2014). A collaborative resource to build consensus for automated left ventricular segmentation of cardiac mr images. Medical image analysis, 18(1):50–62.
Bayer, J. D., Blake, R. C., Plank, G., and Trayanova, N. A. (2012). A novel rule-based algorithm for assigning myocardial fiber orientation to computational heart models. Annals of biomedical engineering, 40(10):2243–2254.
Campos, J., Sundnes, J., Dos, R. S., and Rocha, B. (2019). Effects of left ventricle wall thickness uncertainties on cardiac mechanics. Biomechanics and modeling in mechanobiology, pages 1–13.
Campos, J., Sundnes, J., Dos, R. S., and Rocha, B. (2020). Uncertainty quantification and sensitivity analysis of left ventricular function during the full cardiac cycle. Philosophical Transactions A, 20190381:1–19.
Campos, J. O., Santos, R. W., Sundnes, J., and Rocha, B. M. (2017). Preconditioned augmented lagrangian formulation for nearly incompressible cardiac mechanics. International Journal for Numerical Methods in Biomedical Engineering, 34(4):e2948. e2948 cnm.2948.
Cerqueira, M. D., Weissman, N. J., Dilsizian, V., Jacobs, A. K., Kaul, S., Laskey, W. K., Pennell, D. J., Rumberger, J. A., Ryan, T., Verani, M. S., et al. (2002). Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. Circulation, 105(4):539–542.
Guccione, J. M., McCulloch, A. D., Waldman, L., et al. (1991). Passive material properties of intact ventricular myocardium determined from a cylindrical model. J Biomech Eng, 113(1):42–55.
Kerckhoffs, R., Bovendeerd, P., Kotte, J., Prinzen, F., Smits, K., and Arts, T. (2003). Homogeneity of cardiac contraction despite physiological asynchrony of depolarization: a model study. Annals of biomedical engineering, 31(5):536–547.
Reese, T. G.,Weisskoff, R. M., Smith, R. N., Rosen, B. R., Dinsmore, R. E., andWedeen, V. J. (1995). Imaging myocardial fiber architecture in vivo with magnetic resonance. Magnetic Resonance in Medicine, 34(6):786–791.
Rodríguez-Cantano, R., Sundnes, J., and Rognes, M. E. (2019). Uncertainty in cardiac myofiber orientation and stiffnesses dominate the variability of left ventricle deformation response. International journal for numerical methods in engineering, 79(11):1– 20.
Shavik, S. M., Wall, S. T., Sundnes, J., Burkhoff, D., and Lee, L. C. (2017). Organ-level validation of a cross-bridge cycling descriptor in a left ventricular finite element model: effects of ventricular loading on myocardial strains. Physiological reports, 5(21).
Suinesiaputra, A., Cowan, B. R., Al-Agamy, A. O., Elattar, M. A., Ayache, N., Fahmy, A. S., Khalifa, A. M., Medrano-Gracia, P., Jolly, M.-P., Kadish, A. H., et al. (2014). A collaborative resource to build consensus for automated left ventricular segmentation of cardiac mr images. Medical image analysis, 18(1):50–62.
Publicado
15/09/2020
Como Citar
CAMPOS, Joventino O.; SUNDNES, Joakim; SANTOS, Rodrigo W.; ROCHA, Bernardo M..
Impact of uncertainties in cardiac mechanics simulations. In: CONCURSO DE TESES E DISSERTAÇÕES - SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 20. , 2020, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 31-36.
ISSN 2763-8987.
DOI: https://doi.org/10.5753/sbcas.2020.11554.
