Automatic mapping of atrial fiber orientations for patient‐specific modeling of cardiac electromechanics using image registration

By J. Hörmann, M. Pfaller, Linda Avena, Cristóbal Bertoglio, Wolfgang A. Wall. 2018

23 citations recorded by the source corpus.

Knowledge of appropriate local fiber architecture is necessary to simulate patient‐specific electromechanics in the human heart. However, it is not yet possible to reliably measure in vivo fiber directions especially in human atria. Thus, we present a method that defines the fiber architecture in arbitrarily shaped atria using image registration and reorientation methods based on atlas atria with fibers predefined from detailed histological observations. Thereby, it is possible to generate detailed fiber families in every new patient‐specific geometry in an automated, time‐efficient process. We demonstrate the good performance of the image registration and fiber definition on 10 differently shaped human atria. Additionally, we show that characteristics of the electrophysiological activation pattern that appear in the atlas atria also appear in the patients' atria. We arrive to analogous conclusions for coupled electro‐mechano‐hemodynamical computations.

Subfields: Biomedical Engineering, Cardiology and Cardiovascular Medicine

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Paris Perdikaris
2. F. Sahli Costabal
3. Ellen Kuhl
4. Daniel E. Hurtado
5. Yibo Yang

In Cardiology and Cardiovascular Medicine

1. Paris Perdikaris
2. F. Sahli Costabal
3. Daniel E. Hurtado
4. Ellen Kuhl
5. Yibo Yang

Citations in the corpus

• Physics-Informed Neural Networks for Cardiac Activation Mapping (2020, methodology): “There are several methodologies to incorporate this information with ruled-based approaches [38, 39] and mapping techniques [40, 41].”