4D respiratory motion‐compensated image reconstruction of free‐breathing radial MR data with very high undersampling. Issue 3 (16th March 2016) - Rank, Christopher M.; Heußer, Thorsten; Buzan, Maria T. A.; Wetscherek, Andreas; Freitag, Martin T.; Dinkel, Julien; Kachelrieß, Marc
Abstract : Purpose: To develop four‐dimensional (4D) respiratory time‐resolved MRI based on free‐breathing acquisition of radial MR data with very high undersampling. Methods: We propose the 4D joint motion‐compensated high‐dimensional total variation (4D joint MoCo‐HDTV) algorithm, which alternates between motion‐compensated image reconstruction and artifact‐robust motion estimation at multiple resolution levels. The algorithm is applied to radial MR data of the thorax and upper abdomen of 12 free‐breathing subjects with acquisition times between 37 and 41 s and undersampling factors of 16.8. Resulting images are compared with compressed sensing‐based 4D motion‐adaptive spatio‐temporal regularization (MASTeR) and 4D high‐dimensional total variation (HDTV) reconstructions. Results: For all subjects, 4D joint MoCo‐HDTV achieves higher similarity in terms of normalized mutual information and cross‐correlation than 4D MASTeR and 4D HDTV when compared with reference 4D gated gridding reconstructions with 8.4 ± 1.1 times longer acquisition times. In a qualitative assessment of artifact level and image sharpness by two radiologists, 4D joint MoCo‐HDTV reveals higher scores ( P < 0.05) than 4D HDTV and 4D MASTeR at the same undersampling factor and the reference 4D gated gridding reconstructions, respectively. Conclusions: 4D joint MoCo‐HDTV enables time‐resolved image reconstruction of free‐breathing radial MR data with undersampling factors of 16.8 while achieving low‐streak artifact levels and high image sharpness. Magn Reson Med 77:1170–1183, 2017. © 2016 International Society for Magnetic Resonance in Medicine