This work uses a highly detailed computational model of human atria to investigate the effect of spatial gradient and smoothing of atrial wall thickness on inducibility and maintenance of atrial fibrillation (AF) episodes. An atrial model with homogeneous thickness (HO) was used as baseline for the generation of different atrial models including either a low (LG) or high thickness gradient between left/right atrial free wall and the other regions. Since the model with high spatial gradient presented non-natural sharp edges between regions, either 1 (HG1) or 2 (HG2) Laplacian smoothing iterations were applied. Arrhythmic episodes were initiated using a rapid pacing protocol and long-living rotors were detected and tracked over time. Thresholds optimised with receiver operating characteristic analysis were used to define high gradient/curvature regions. Greater spatial gradients increased the atrial model inducibility and unveiled additional regions vulnerable to maintain AF drivers. In the models with heterogeneous wall thickness (LG, HG2 and HG1), 73.5 ± 8.7% of the long living rotors were found in areas within 1.5 mm from nodes with high thickness gradient, and 85.0 ± 3.4% in areas around high endocardial curvature. These findings promote wall thickness gradient and endocardial curvature as measures of AF vulnerability.