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  • Title: Development of three-dimensional MR neurography using an optimized combination of compressed sensing and parallel imaging.
    Author: Aoike T, Fujima N, Yoneyama M, Fujiwara T, Takamori S, Aoike S, Ishizaka K, Kudo K.
    Journal: Magn Reson Imaging; 2022 Apr; 87():32-37. PubMed ID: 34968698.
    Abstract:
    PURPOSE: To assess the cervical magnetic resonance neurography (MRN) imaging quality obtained with compressed sensing and sensitivity-encoding (compressed SENSE; CS-SENSE) technique in comparison to that obtained with the conventional parallel imaging (i.e., SENSE) technique. MATERIALS AND METHODS: Five healthy volunteers underwent a three-dimensional (3D) turbo spin-echo (TSE)-based cervical MRN examination using a 3.0 Tesla MR-unit. All MRN acquisitions were performed with CS-SENSE and conventional SENSE. We used four acceleration factors (4, 8, 16 and 32) in CS-SENSE. The image quality in MRN was evaluated by assessing the degree of cervical nerve depiction using the contrast ratio (CR) and contrast-noise ratio (CNR) between the cervical nerve and the background signal intensity and a visual scoring system (1: poor, 2: moderate, 3: good). In all of the CR, CNR and visual score, we calculated the ratio of the CS-SENSE-based MRN to that from SENSE-based MRN plus the 95% confidence intervals (CIs) of these ratios. RESULTS: In the multiple comparison of MRN images with the control of conventional SENSE-based MRN, both the quantitative CR values and the visual score for the CS-SENSE factors of 16 and 32 were significantly lower, whereas the CS-SENSE factors of 4 and 8 showed a non-significant difference. In addition, the quantitative CNR values obtained with the CS-SENSE factors of 4 and 8 were significantly higher than that obtained with the conventional SENSE-based MRN while the CS-SENSE factor of 32 was significantly lower, in contrast, the CS-SENSE factors of 16 showed a non-significant difference. For CS-SENSE factors of 4 and 8, all ratios of the CS-SENSE-based MRN values for CR, CNR and visual scores to those from SENSE-based MRN were above 0.95. CONCLUSION: CS-SENSE-based MRN can accomplish fast scanning with sufficient image quality when using a high acceleration factor.
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