Automated MR Image Prescription of the Liver using Deep Learning: Development, Evaluation & Prospective Implementation

This work developed a novel automated AI-based method for liver image prescription from a localizer and evaluated it in a large retrospective patient cohort (1,039 patients for training/testing), across pathologies, field strengths, and against radiologists’ inter-reader reproducibility performance. AI-based 3D axial prescription achieved a S/I shift of <2.3 cm compared to manual prescription for 99.5% of test dataset. The AI method performed well across all sub-cohorts and better in 3D axial prescription than radiologists’ inter-reader reproducibility performance. We successfully implemented the AI method on a clinical MR system, which demonstrated robust performance across localizer sequences.