Evaluating Compressed SENSE (CS) MRI Metal Artifact Reduction Using Pig L-Spine Phantom and Transplant Patients: Focused on the CS-SEMAC (SPIR), mDixon(O-MAR) and STIR Techniques.

This study evaluates the clinical usefulness of the images obtained after applying mDixon (O-MAR), CS-SEMAC (SPIR), and STIR techniques to Pig L-Spine Phantom and transplant patients according to the difference in the reduction in metal artifacts and provides the optimal MAR image technique. This study was conducted with Phantom and 30 transplant patients who had an implant on the L-Spine (22 men, 8 women, mean age: 64.2 ± 12.98). All data analyzed were evaluated, using Philips Ingenia 3.0T CX. As pulse sequences, applied to the analysis, mDixon (O-MAR), CS-SEMAC (SPIR), and STIR were used. As the coil used to obtain data, the dStream Head Spine Coil was used. When tested directly applying to the transplant patients in the conditions the same as for the Phantom, as for the MAR effect of T1 and T2 images, the SNR value showed the highest effect on the increase in the signal in T1, T2 CS-SEMAC (SPIR), followed by mDixon (O-MAR) and STIR, which was the same result as the Phantom (p < 0.05). In addition, in the results of the histogram measurement in both of the subjects, Phantom and transplant patients, the count of T1, the T2 Sagittal image was the highest in T1, T2 STIR, followed by T1, T2 mDixon (O-MAR) and T1, and T2 CS-SEMAC (SPIR). As a result of the qualitative analysis, the quality was the best in T2 CS-SEMAC(SPIR) (c), followed by mDixon (O-MAR) (b) and T2 STIR (a). In conclusion, when the MAR effect on the Pig L-spine Phantom and Transplant patients was compared, it was noted that the CS-SEMAC (SPIR) technique was the most excellent in the following order: STIR < mDixon (O-MAR) < CS-SEMAC (SPIR).

Evaluating the Quality of Optimal MRCP Image Using RT-2D-Compressed SENSE(CS)Turbo Spin Echo: Comparing Respiratory Triggering(RT)-2D-SENSE Turbo Spin Echo and Breath Hold-2D-Single-Shot Turbo Spin Echo.

This study aimed to select the pulse sequence providing the optimal MRCP image quality by applying various reduction and denoising level parameters­which could improve image quality and shorten examination time­to BH-2D-SSh TSE, RT- 2D-SENSE TSE, and RT-2D-Compressed SENSE(CS) TSE and then comparing and analyzing the obtained images. This study was carried out using 30 subjects (15 men and 15 women with a mean age of 53 ± 8.76 years) who underwent an MRCP test using 3.0T MRI equipment. These 30 subjects were composed of 20 patients (CHDD: 7; LC: 6; and IPMN: 7) and 10 volunteers without a disease. When the CS technique was used, five reduction values (1.1, 1.2, 1.3, 1.4, and 1.5) were used and four denoising levels (No, Weak, Medium, and Strong) were used. The existing SENSE method was based on a reduction value of 1, and other parameters were set the same. The image data of BH-2D-SSh TSE, RT-2D-SENSE TSE, and RT-CS-2D TSE used for the analysis were acquired in the coronal plane, and the acquired data underwent MIP post-processing for analysis. To compare these techniques, SNR and CNR were measured for six biliary duct images for the purpose of quantitative analysis, and qualitative analysis was performed on the sharpness of the duct, the overall quality of the image, and the motion artifact. The results of the quantitative and standard analyses showed that the RT-2D-CS TSE technique had the highest results for all IPMN, LC, and CHDD diseases (p < 0.05). Moreover, SNR and CNR were the highest when the reduction value was set to 1.3 and the denoising level was set to medium as the CS setting values (p < 0.05). Compared with the conventional RT-2D-SENSE TSE, the test time decreased by 20% and SNR and CNR increased by 14% on average. When conducting RT-2D-CS TSE, we found that it shortened the examination time and improved the image quality compared to the existing RT-2D-SENSE TSE. Unlike previous studies, this study using the RT technique shows that it is a useful MRI Pulse Sequence technique able to replace the BH-2D-SSh TSE and BH-3D-SENSE GRASE techniques, which require the patient to hold their breath during the test.

Unravelling the intrinsic functional organization of the human striatum: a parcellation and connectivity study based on resting-state FMRI.

As the main input hub of the basal ganglia, the striatum receives projections from the cerebral cortex. Many studies have provided evidence for multiple parallel corticostriatal loops based on the structural and functional connectivity profiles of the human striatum. A recent resting-state fMRI study revealed the topography of striatum by assigning each voxel in the striatum to its most strongly correlated cortical network among the cognitive, affective, and motor networks. However, it remains unclear what patterns of striatal parcellation would result from performing the clustering without subsequent assignment to cortical networks. Thus, we applied unsupervised clustering algorithms to parcellate the human striatum based on its functional connectivity patterns to other brain regions without any anatomically or functionally defined cortical targets. Functional connectivity maps of striatal subdivisions, identified through clustering analyses, were also computed. Our findings were consistent with recent accounts of the functional distinctions of the striatum as well as with recent studies about its functional and anatomical connectivity. For example, we found functional connections between dorsal and ventral striatal clusters and the areas involved in cognitive and affective processes, respectively, and between rostral and caudal putamen clusters and the areas involved in cognitive and motor processes, respectively. This study confirms prior findings, showing similar striatal parcellation patterns between the present and prior studies. Given such striking similarity, it is suggested that striatal subregions are functionally linked to cortical networks involving specific functions rather than discrete portions of cortical regions. Our findings also demonstrate that the clustering of functional connectivity patterns is a reliable feature in parcellating the striatum into anatomically and functionally meaningful subdivisions. The striatal subdivisions identified here may have important implications for understanding the relationship between corticostriatal dysfunction and various neurodegenerative and psychiatric disorders.