Comparison of three dimensional gradient-echo sequences with conventional two dimensional sequences to assess the image quality of shoulder joint in magnetic resonance imaging

Abstract

Abstract Background: Three-dimensional gradient-echo (3D-GRE) sequences provide isotropic or nearly isotropic 3D images, leading to better visualization of smaller structures, compared to two-dimensional (2D) sequences. The aim of this study was to prospectively compare 2D and 3D-GRE sequences in terms of key imaging metrics, including signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), glenohumeral joint space, image quality, artifacts, and acquisition time in shoulder joint images, using 1.5 T MRI scanner. Methods: Thirty-five normal volunteers with no history of shoulder disorders underwent a shoulder MRI examination with conventional 2D sequences, including T1- and T2-weighted fast spin-echo (T1/T2w FSE) as well as proton density-weighted fast spin-echo with fat saturation (PD-FS) followed by 3D-GRE sequences including VIBE, TRUEFISP, DESS, and MEDIC techniques. Two independent reviewers assessed all images of the shoulder joints. Intra- and inter-observer agreement, were quantified using kappa statistics. Results: Among 3D-GRE sequences, TRUEFISP showed significantly the best CNR between cartilage-bone (30.12, p = 0.001) and cartilage-muscle (12.98, p = 0.01). TRUEFISP also showed the highest SNR for cartilage (41.40, p = 0.01) and muscle (28.33, p = 0.001). Furthermore, 3D-GRE sequences showed significantly higher image quality, compared to 2D sequences (p < 0.001). Moreover, the acquisition time of the 3D-GRE sequences was considerably shorter than the total acquisition time of PD-FS sequences in three orientations (p<0.01). Conclusions: 3D-GRE techniques provided shoulder joint imaging with significantly higher image quality, compared to 2D sequences. Among 3D sequences, TRUEFISP showed significantly the best CNR between cartilage-bone and cartilage-muscle, as well as the highest SNR for cartilage and muscle, compared to other sequences. Moreover, 3D-GRE could take a shorter acquisition time than the total acquisition time of 2D PD-FS techniques in three planes.