Discrimination of sustained VT in structural heart disease using LGE-CMR and computational simulation: moving beyond...

Area of Science:

• Cardiology
• Medical Imaging
• Computational Biology

Background:

• Sustained ventricular tachycardia (VT) is a significant cause of sudden cardiac death in patients with structural heart disease (SHD).
• Current risk stratification methods, primarily relying on left ventricular ejection fraction (LVEF), are suboptimal for identifying patients at high risk for VT.

Purpose of the Study:

• To develop and evaluate an exploratory model for discriminating sustained VT in SHD.
• To integrate late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) scar characteristics with computational VT simulation.
• To compare the predictive performance of this integrated model against LVEF.

Main Methods:

• A single-center retrospective study enrolled patients with suspected SHD who underwent LGE-CMR.
• Quantitative scar analysis, digital heart-twin reconstruction, and virtual electrophysiological simulation were performed on LGE-positive patients.
• An integrated LGE-VTsim index was derived from scar core, grey zone, VT inducibility, and inducible VT circuits.

Main Results:

• Lower LVEF and visual LGE positivity were associated with sustained VT.
• Among LGE-positive patients, those with sustained VT exhibited larger core scar, larger grey zone, higher VT inducibility, and more inducible VT circuits.
• The integrated LGE-VTsim index demonstrated superior discrimination of sustained VT (C-statistic: 0.816) compared to LVEF (C-statistic: 0.730) and remained an independent predictor.

Conclusions:

• The LGE-VTsim index, combining quantitative LGE-CMR scar assessment and computational simulation, shows promise for identifying patients at risk of sustained VT in SHD.
• This integrated approach offers improved risk stratification beyond traditional LVEF assessment.