Estimating cardiac contraction through high resolution data assimilation of a personalized mechanical model
Finsberg, Henrik Nicolay; Balaban, Gabriel; Ross, Stian Balnagown; Håland, Trine Synnøve Fink; Odland, Hans Henrik; Sundnes, Joakim; Wall, Samuel Thomas
Journal article, Peer reviewed
Published version
Date
2017Metadata
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Abstract
Cardiac computational models, individually personalized, can provide clinicians with useful diagnostic information and aid in treatment planning. A major bottleneck in this process can be determining model parameters to fit created models to individual patient data. However, adjoint-based data assimilation techniques can now rapidly estimate high dimensional parameter sets. This method is used on a cohort of heart failure patients, capturing cardiac mechanical information and comparing it with a healthy control group. Excellent fit (R2 ≥ 0.95) to systolic strains is obtained, and analysis shows a significant difference in estimated contractility between the two groups. Keywords Cardiac mechanics; Adjoint method; Data assimilation; PDE-constrained optimization; Contractility Estimating cardiac contraction through high resolution data assimilation of a personalized mechanical model