Case report: Personalized computational model guided ablation for left atrial flutter.

Area of Science:

• Cardiovascular Electrophysiology
• Computational Biology
• Medical Imaging

Background:

• Atypical atrial flutter post-cardiac ablation presents mapping challenges due to scar formation in the left atrium.
• Magnetic Resonance Imaging (MRI) is effective in identifying left atrial scar tissue.

Observation:

• A personalized computational model was developed using patient-specific MRI scar data.
• The model, a monodomain simulation, adjusted conductivities for different tissue regions and induced flutter via premature pacing.
• The model's predictions were prospectively tested in patients undergoing atypical flutter ablation.

Findings:

• Simulation-predicted flutter circuits matched clinically observed atypical atrial flutter pathways.
• The computational model sometimes provided more accurate predictions than invasive electroanatomical mapping.
• Model predictions guided ablation to isthmus sites, leading to successful flutter termination.

Implications:

• Personalized computational modeling offers a novel, non-invasive tool for understanding and treating complex atrial arrhythmias.
• This approach has the potential to enhance the precision and efficacy of catheter ablation procedures.
• Integrating patient-specific imaging data into computational models can revolutionize personalized cardiac arrhythmia management.