In silico simulations using patient-specific 3D models correctly predicted clinical reentry in 13 of 16 inducible virtual patients and absence of reentry in all 13 non-inducible patients.
Can patient-specific 3D computational models of scar anatomy and border zone properties predict ventricular arrhythmias in post-myocardial infarction patients?
Patient-specific 3D computational modeling of post-infarction scar anatomy and border zone properties can accurately predict clinical ventricular arrhythmia risk.
BACKGROUND: Ventricular arrhythmias are a significant risk for patients who have suffered a myocardial infarction, with cardiac scar remodeling playing a critical role in arrhythmia development. Understanding the structural and electrical properties of the scar and its surrounding tissue is essential for assessing arrhythmia risk. OBJECTIVE: This study aimed to investigate the role of scar anatomy and border zone properties in predicting ventricular arrhythmias, using patient-specific three-dimensional models derived from medical imaging. METHODS: The study involved 29 post-myocardial infarction patients. Comprehensive segmentation of the ventricles was performed to generate 3D models incorporating the scar, its core, and the border zone. Arrhythmia inducibility was assessed through in silico simulations using a clinical early-pacing protocol. Different configurations of the border zone were tested, varying fibroblast density and ionic current remodeling. RESULTS: Reentry was induced in 16 of the 29 virtual patients, 13 of whom also experienced clinical reentry. Conversely, the 13 virtual patients in whom reentry was not induced also did not show reentry clinically. The simulations demonstrated that varying fibrosis density within the same scar structure can lead to different arrhythmic scenarios. Key quantified parameters related to scar anatomy, including the extent of the border zone and conduction channels, were identified as strong predictors of arrhythmia risk. CONCLUSION: This study highlights the importance of scar anatomy in post-infarction arrhythmias and provides a novel approach to predicting arrhythmic risk. The findings support the use of patient-specific scar remodeling data for improving clinical risk assessments and guiding therapy to prevent future arrhythmias.
Villar‐Valero et al. (Fri,) conducted a other in Post-myocardial infarction ventricular arrhythmias (n=29). Patient-specific 3D computational modeling and in silico simulations vs. Clinical outcomes (clinical reentry) was evaluated on Arrhythmia inducibility (reentry). In silico simulations using patient-specific 3D models correctly predicted clinical reentry in 13 of 16 inducible virtual patients and absence of reentry in all 13 non-inducible patients.