Deep Learning–Accelerated 3D Vessel Wall MRI: Prospective Evaluation of Sonic DL with Substantial Scan Time Reduction

PURPOSE: While 3D vessel wall MRI (VW-MRI) is essential for characterizing vasculopathies, prolonged acquisition times limit its utility by increasing motion susceptibility. We aimed to evaluate Sonic DL, a next-generation AI-accelerated reconstruction technique, for VW-MRI by comparing it with a conventional protocol, using a comprehensive non-inferiority framework with a focus on diagnostic consistency. MATERIALS AND METHODS: ). Inter-reader agreement was assessed using Fleiss' kappa. RESULTS: remained comparable between protocols (P = 0.95), and Sonic DL improved CSF suppression (P = 0.002). Inter-reader agreement was good to excellent for all qualitative categories (κ = 0.79-0.88). CONCLUSION: Compared with the conventional protocol, Sonic DL-accelerated VW-MRI maintained non-inferior image quality and lesion assessment while reducing scan time to approximately 5 minutes. Excellent inter-protocol and inter-reader agreement demonstrated consistent lesion characterization across protocols, supporting the feasibility of Sonic DL as an accelerated vessel wall MRI technique.