Predicting Arrhythmias via Reentrant Vulnerability Index Mapping in Post-Infarction Hearts Under Stellate Ganglion Modulation

  • Javier Villar-Valero
  • , Lledo Nebot
  • , Juan F. Gomez
  • , David Soto-Iglesias
  • , Giulio Falasconi
  • , Antonio Berruezo
  • , Bastiaan J.D. Boukens
  • , Beatriz Trenor*
  • *Corresponding author for this work

Research output: Contribution to journalConference article in journalAcademicpeer-review

Abstract

Reentrant arrhythmias deriving from cardiac infarction scars can lead to sudden cardiac death. While implantable defibrillators are standard therapy, their limitations motivate alternative approaches such as autonomic modulation. This work sets computational ventricular models reconstructed from LGE-MRI data of two infarct cases, segmented into healthy tissue, border zone, and scar. Electrophysiological properties were assigned by tissue type, and sympathetic effects were modeled as IKs increases leading to 3~0% APD shortening in stellate innervated regions. Programmed stimulation and Reentrant Vulnerability Index (RVI) analysis revealed that arrhythmia risk increased when sympathetic remodeling overlapped with the scar, whereas mismatched distributions had little effect. Sites of negative RVI values predicted reentry initiation, supporting RVI as a noninvasive marker of post-MI arrhythmic risk and a potential tool to guide autonomic modulation strategies.
Original languageEnglish
JournalComputing in Cardiology
Volume52
DOIs
Publication statusPublished - 1 Jan 2025
Event52nd International Computing in Cardiology, CinC 2025 - Sao Paulo, Brazil
Duration: 14 Sept 202517 Sept 2025
https://cinc2025.eventos.ufabc.edu.br/

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