Aoike Takuya, Fujima Noriyuki, Yoneyama Masami, Fujiwara Taro, Takamori Sayaka, Aoike Suzuko, Ishizaka Kinya, Kudo Kohsuke
Department of Radiological Technology, Hokkaido University Hospital, Sapporo, Japan.
Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan.
Magn Reson Imaging. 2022 Apr;87:32-37. doi: 10.1016/j.mri.2021.12.002. Epub 2021 Dec 27.
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.
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.
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.
CS-SENSE-based MRN can accomplish fast scanning with sufficient image quality when using a high acceleration factor.
评估采用压缩感知和灵敏度编码（压缩感知灵敏度编码；CS-SENSE）技术获得的颈椎磁共振神经成像（MRN）图像质量，并与传统并行成像（即灵敏度编码）技术获得的图像质量进行比较。
5名健康志愿者使用3.0特斯拉磁共振设备进行基于三维（3D）快速自旋回波（TSE）的颈椎MRN检查。所有MRN采集均采用CS-SENSE和传统灵敏度编码。我们在CS-SENSE中使用了四个加速因子（4、8、16和32）。通过使用颈椎神经与背景信号强度之间的对比度（CR）和对比噪声比（CNR）以及视觉评分系统（1：差，2：中等，3：好）来评估颈椎神经的显示程度，从而对MRN中的图像质量进行评估。在所有的CR、CNR和视觉评分中，我们计算了基于CS-SENSE的MRN与基于灵敏度编码的MRN的比值以及这些比值的95%置信区间（CI）。
在以传统基于灵敏度编码的MRN为对照的MRN图像的多重比较中，16和32的CS-SENSE因子的定量CR值和视觉评分均显著较低，而4和8的CS-SENSE因子显示无显著差异。此外，4和8的CS-SENSE因子获得的定量CNR值显著高于传统基于灵敏度编码的MRN获得的值，而32的CS-SENSE因子则显著较低，相比之下，16的CS-SENSE因子显示无显著差异。对于4和8的CS-SENSE因子，基于CS-SENSE的MRN在CR、CNR和视觉评分方面的值与基于灵敏度编码的MRN的值的所有比值均高于0.95。
基于CS-SENSE的MRN在使用高加速因子时能够以足够的图像质量完成快速扫描。
