Electroanatomical mapping, a keystone diagnostic tool in cardiac electrophysiology studies, can provide high-density maps of the local electric properties of the tissue. It is therefore tempting to use such data to better individualize current patient-specific models of the heart through a data assimilation procedure and to extract potentially insightful information such as conduction properties. Parameter identification for state-of-the-art cardiac models is however a challenging task. In this work, we introduce a novel inverse problem for inferring the anisotropic structure of the conductivity tensor, that is fiber orientation and conduction velocity along and across fibers, of an eikonal model for cardiac activation. The proposed method, named PIEMAP, performed robustly with synthetic data and showed promising results with clinical data. These results suggest that PIEMAP could be a useful supplement in future clinical workflowss of personalized therapies.

PIEMAP: Personalized Inverse Eikonal Model from Cardiac Electro-Anatomical Maps / Grandits, T.; Pezzuto, S.; Lubrecht, J. M.; Pock, T.; Plank, G.; Krause, R.. - STAMPA. - 12592:(2021), pp. 76-86. (Intervento presentato al convegno STACOM tenutosi a Lima, Peru nel October 4, 2020) [10.1007/978-3-030-68107-4_8].

PIEMAP: Personalized Inverse Eikonal Model from Cardiac Electro-Anatomical Maps

Pezzuto S.;
2021-01-01

Abstract

Electroanatomical mapping, a keystone diagnostic tool in cardiac electrophysiology studies, can provide high-density maps of the local electric properties of the tissue. It is therefore tempting to use such data to better individualize current patient-specific models of the heart through a data assimilation procedure and to extract potentially insightful information such as conduction properties. Parameter identification for state-of-the-art cardiac models is however a challenging task. In this work, we introduce a novel inverse problem for inferring the anisotropic structure of the conductivity tensor, that is fiber orientation and conduction velocity along and across fibers, of an eikonal model for cardiac activation. The proposed method, named PIEMAP, performed robustly with synthetic data and showed promising results with clinical data. These results suggest that PIEMAP could be a useful supplement in future clinical workflowss of personalized therapies.
2021
Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges: 11th International Workshop, STACOM 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Revised Selected Papers
Cham
Springer
Grandits, T.; Pezzuto, S.; Lubrecht, J. M.; Pock, T.; Plank, G.; Krause, R.
PIEMAP: Personalized Inverse Eikonal Model from Cardiac Electro-Anatomical Maps / Grandits, T.; Pezzuto, S.; Lubrecht, J. M.; Pock, T.; Plank, G.; Krause, R.. - STAMPA. - 12592:(2021), pp. 76-86. (Intervento presentato al convegno STACOM tenutosi a Lima, Peru nel October 4, 2020) [10.1007/978-3-030-68107-4_8].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/360506
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