Fast Myocardial Wall Thickness Estimation Using Morphological Sphere Propagation for Ventricular Tachycardia Substrate Detection

Abstract Accurate left ventricular (LV) wall thickness (WT) estimation can identify arrhythmogenic ventricular tachycardia (VT) channels, but Laplace-based method is limited by computational inefficiency. This study proposes the Morphological Sphere Propagation (MSP) framework, a rapid, spherebased approach for LV WT mapping. MSP employs isotropic resampling followed by sequential endocardial dilation and epicardial contraction using a spherical structuring element, with thickness derived from propagation iterations scaled to image resolution. The proposed method was validated against a Laplace-based solver using synthetic phantoms with known ground-truth thickness, assessing computation time and mean absolute error (MAE). Additional validation was performed on clinical cardiac CT datasets from 10 ventricular tachycardia (VT) patients by evaluating CT channel agreement. Results demonstrated comparable accuracy (mean absolute error: MSP 0.49 ± 0.01 mm vs. Laplace 0.37 ± 0.03 mm) but 25× faster computation (MSP: 1.8 ± 0.1 s vs. Laplace: 47.0 ± 19.3 s). MSP showed strong agreement with Laplace in CT channel detection (Sensitivity = 0.85, PPV = 0.85). MSP offers a practical, accessible alternative for rapid arrhythmia substrate characterization without sacrificing accuracy.