Computational electrophysiology to support the mapping of coronary sinus branches for cardiac resynchronization therapy

Keywords

Computational Medicine for the Cardiocirculatory System
Code:
84/2020
Title:
Computational electrophysiology to support the mapping of coronary sinus branches for cardiac resynchronization therapy
Date:
Wednesday 23rd December 2020
Author(s):
Vergara, C.; Stella, S.; Maines, M.; Catanzariti, D.; Demattè, C.; Centonze, M.; Nobile, F.; Quarteroni, A.; Del Greco, M.
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Abstract:
BACKGROUND This work dealt with the assessment of a computational tool to estimate the latest electrically activated segment (LEAS) of the left ventricle during cardiac resynchronization therapy (CRT). OBJECTIVE The aim of the work was to show that for patients with left bundle branch block (LBBB), possibly in presence of fibrosis, the proposed computational tool was able to accurately reproduce the epicardial activation maps and in particular LEAS location in the epicardial veins, often used as a target site for the left lead placement. METHODS We considered a computational tool based on Finite Elements used to recover the activation maps in all the myocardium. The model was calibrated by using activation times acquired in the epicardial veins with an electroanatomic mapping system (EAMS). RESULTS We applied our computational tool to predict LEAS in the epicardial veins of ten patients. We found an excellent accordance with LEAS measured by EAMS, the discrepancy being less than 4mm. We also calibrated our model using only the activation maps of the coronary sinus (CS), still obtaining an excellent agreement with the measured LEAS. CONCLUSION We showed that our computational tool is able to accurately predict the location of LEAS, even when information only at CS were used for calibration. This could be of utmost importance in view of CRT implantation, since LEAS could be determined by mapping only CS, saving time and avoiding the exposition of the patient to a deeper invasive procedure.