Echocardiogram-based ventricular isogeometric cardiac analysis using multi-patch fitted NURBS
Monitoring the cardiac function often relies on non-invasive vital measurements, electrocardiograms, and low-resolution echocardiograms. The monitoring data can be augmented with numerical modeling results to support treatment-risk assessment. Often, medical images are not suitable for high-fidelity...
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Veröffentlicht in: | Computer methods in applied mechanics and engineering 2024-05, Vol.425, p.116958, Article 116958 |
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Sprache: | eng |
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Zusammenfassung: | Monitoring the cardiac function often relies on non-invasive vital measurements, electrocardiograms, and low-resolution echocardiograms. The monitoring data can be augmented with numerical modeling results to support treatment-risk assessment. Often, medical images are not suitable for high-fidelity modeling due to their spatial sparsity and low resolution. In this work, we present a workflow that converts a limited number of two-dimensional (2D) echocardiogram images into analysis-suitable left-ventricle geometries for isogeometric analysis (IGA). The image data is fitted by reshaping a multi-patch NURBS template. This fitting procedure results in a smooth interpolation with a limited number of degrees of freedom. In addition, a coupled 3D-0D cardiac model is extended with a pre-stressing method to perform ventricular-cardiac-mechanic analyses based on in vivo images. The workflow is benchmarked using population-averaged imaging data, which demonstrates that both the shape of the left ventricle and its mechanical response are well predicted in sparse-data scenarios. The case of a clinical patient is considered to demonstrate the suitability of the workflow in a real-data setting.
•We propose an isogeometric patient-specific workflow for ventricular cardiac mechanics.•We introduce a novel multi-patch fitting algorithm for sparse and irregular patient-specific data.•We accommodate pre-stressed in vivo images in the continuum formulation.•We show that the multi-patch fitting performs very well in an echocardiographic setting.•We demonstrate the suitability of the proposed workflow in a real-data setting. |
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ISSN: | 0045-7825 1879-2138 |
DOI: | 10.1016/j.cma.2024.116958 |