Breath-hold diffusion-weighted MR imaging (DWI) using deep learning reconstruction: Comparison with navigator triggered DWI in patients with malignant liver tumors

This study investigated the feasibility of single breath-hold (BH) diffusion-weighted MR imaging (DWI) using deep learning reconstruction (DLR) compared to navigator triggered (NT) DWI in patients with malignant liver tumors. This study included 91 patients who underwent both BH-DWI and NT-DWI with 3T MR system. Abdominal MR images were subjectively analyzed to compare visualization of liver edges, presence of ghosting artifacts, conspicuity of malignant liver tumors, and overall image quality. Then, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) values of malignant liver tumors were objectively measured using regions of interest. Image quality except conspicuity of malignant liver tumors were significantly better in BH-DW image than in NT-DW image (p