Computational electrophysiology of the coronary sinus branches based on electro-anatomical mapping for the prediction of the latest activated region

This work dealt with the assessment of a computational tool to estimate the electrical activation in the left ventricle focusing on the latest electrically activated segment (LEAS) in patients with left bundle branch block and possible myocardial fibrosis. We considered the Eikonal-diffusion equatio...

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Bibliographic Details
Published in:Medical & biological engineering & computing 2022-08, Vol.60 (8), p.2307-2319
Main Authors: Vergara, Christian, Stella, Simone, Maines, Massimiliano, Africa, Pasquale Claudio, Catanzariti, Domenico, Demattè, Cristina, Centonze, Maurizio, Nobile, Fabio, Quarteroni, Alfio, Del Greco, Maurizio
Format: Article
Language:English
Subjects:
Bioengineering
Biomedical and Life Sciences
Biomedical Engineering and Bioengineering
Biomedicine
Calibration
Clinical medicine
Computer Applications
Diffusion barriers
Electrophysiology
Error analysis
Fibrosis
Geometry
Human Physiology
Imaging
Laboratories
Mapping
Myocardium
Original
Original Article
Patients
Radiology
Software
Veins & arteries
Ventricle
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Summary:This work dealt with the assessment of a computational tool to estimate the electrical activation in the left ventricle focusing on the latest electrically activated segment (LEAS) in patients with left bundle branch block and possible myocardial fibrosis. We considered the Eikonal-diffusion equation and to recover the electrical activation maps in the myocardium. The model was calibrated by using activation times acquired in the coronary sinus (CS) branches or in the CS solely with an electroanatomic mapping system (EAMS) during cardiac resynchronization therapy (CRT). We applied our computational tool to ten patients founding an excellent accordance with EAMS measures; in particular, the error for LEAS location was less than 4 mm. We also calibrated our model using only information in the CS, still obtaining an excellent agreement with the measured LEAS. The proposed tool was able to accurately reproduce the electrical activation maps and in particular LEAS location in the CS branches, with an almost real-time computational effort, regardless of the presence of myocardial fibrosis, even when information only at CS was used to calibrate the model. This could be useful in the clinical practice since LEAS is often used as a target site for the left lead placement during CRT. Graphical abstract Overall picture of the computational pipeline for the estimation of LEAS
ISSN:0140-0118
1741-0444
DOI:10.1007/s11517-022-02610-3