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Towards personalized clinical in-silico modeling of atrial anatomy and electrophysiology

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Abstract

Computational atrial models aid the understanding of pathological mechanisms and therapeutic measures in basic research. The use of biophysical models in a clinical environment requires methods to personalize the anatomy and electrophysiology (EP). Strategies for the automation of model generation and for evaluation are needed. In this manuscript, the current efforts of clinical atrial modeling in the euHeart project are summarized within the context of recent publications in this field. Model-based segmentation methods allow for the automatic generation of ready-to-simulate patient-specific anatomical models. EP models can be adapted to patient groups based on a-priori knowledge and to the individual without significant further data acquisition. ECG and intracardiac data build the basis for excitation personalization. Information from late enhancement (LE) MRI can be used to evaluate the success of radio-frequency ablation (RFA) procedures and interactive virtual atria pave the way for RFA planning. Atrial modeling is currently in a transition from the sole use in basic research to future clinical applications. The proposed methods build the framework for model-based diagnosis and therapy evaluation and planning. Complex models allow to understand biophysical mechanisms and enable the development of simplified models for clinical applications.

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Authors and Affiliations

  1. Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 76131, Karlsruhe, Germany

    Martin W. Krueger, Walther H. W. Schulze, Gunnar Seemann & Olaf Dössel

  2. Division of Imaging Sciences and Biomedical Engineering, King’s College London, London, UK

    Kawal S. Rhode & Reza Razavi

Authors
  1. Martin W. Krueger
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  2. Walther H. W. Schulze
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  3. Kawal S. Rhode
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  4. Reza Razavi
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  5. Gunnar Seemann
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  6. Olaf Dössel
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Corresponding author

Correspondence to Martin W. Krueger.

Additional information

The research leading to these results has received funding from the European Communitys Seventh Framework Programme (FP7/2007-2013) under grant agreement No. 224495 (euHeart project).

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Krueger, M.W., Schulze, W.H.W., Rhode, K.S. et al. Towards personalized clinical in-silico modeling of atrial anatomy and electrophysiology. Med Biol Eng Comput 51, 1251–1260 (2013). https://doi.org/10.1007/s11517-012-0970-0

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