Deep Learning Reconstructed T2-weighted Dixon Imaging of the Spine: Impact on Acquisition Time and Diagnostic Performance

Magnetic resonance imaging of the spine is considered one of the most commonly performed examinations in clinical routine. The raising demand for high quality imaging of the spine creates the need for tailored examination protocols, especially with regard to increasingly limited scanner capacities. Deep Learning based imaging reconstruction has emerged as promising novel technique to accelerate MR imaging while maintaining image quality. This study analyzed a novel deep learning accelerated T2-weighted Dixon sequence of the spine in terms of diagnostic performance. The results suggest that the here presented sequence is feasible with a diagnostic performance comparable to standard imaging.