Abstract
Myocardial stiffness is a clinical biomarker used to diagnose and stratify diseases such as heart failure. This biomechanical property can be inferred from the personalisation of computational cardiac models to clinical measures. Nevertheless, previous attempts have been unable to determine a unique set of material constitutive parameters. In this study we address this shortcoming by proposing a new cost function that allows us to uncouple key parameters and uniquely describe passive material properties in patients from available clinical data.
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Nasopoulou, A., Blazevic, B., Crozier, A., Shi, W., Shetty, A., Aldo Rinaldi, C., … Niederer, S. A. (2015). Myocardial stiffness estimation: A novel cost function for unique parameter identification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9126, pp. 355–363). Springer Verlag. https://doi.org/10.1007/978-3-319-20309-6_41
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