Enhanced Visualization of Intracranial Cortical Arteries Using Deep Learning Reconstruction in Vessel Wall MR Imaging

This study evaluated the utility of deep learning reconstruction (DLR) in vessel wall imaging (VWI) for visualizing the entire cerebral arterial system, including cortical arteries. Seventeen patients underwent post-contrast 3D T1WI-CUBE VWI with 0.5 mm isotropic resolution. Images with and without DLR were compared using qualitative and quantitative assessments. Qualitative image quality was rated on a 4-point scale across 29 arterial segments, including the internal carotid, vertebral, basilar, and the 1st to 4th segments of the major cerebral arteries. Quantitative evaluation of the vertebral artery wall assessed SNR and contrast-to-noise ratio (CNR). DLR significantly improved overall image quality compared to the without-DLR group, with cortical arteries rated as optimal in all cases with DLR (all P < 0.001). SNR and CNR were also significantly higher with DLR (P = 0.004). These results suggest that DLR enables high-resolution VWI of intracranial cortical arteries within a clinically acceptable scan time.