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人体前臂神经的弥散张量成像。

Diffusion tensor imaging of forearm nerves in humans.

机构信息

Diagnostic & Interventional Imaging, University of Texas Health Science Center at Houston, Houston, Texas, USA.

出版信息

J Magn Reson Imaging. 2012 Oct;36(4):920-7. doi: 10.1002/jmri.23709. Epub 2012 Jun 11.

Abstract

PURPOSE

To implement a diffusion tensor imaging (DTI) protocol for visualization of peripheral nerves in human forearm.

MATERIALS AND METHODS

This Health Insurance Portability and Accountability Act (HIPAA)-compliant study was approved by our Institutional Review Board and written informed consent was obtained from 10 healthy participants. T(1) - and T(2) -weighted turbo spin echo with fat saturation, short tau inversion recovery (STIR), and DTI sequences with 21 diffusion-encoding directions were implemented to acquire images of the forearm nerves with an 8 channel knee coil on a 3T MRI scanner. Identification of the nerves was based on T(1) -weighted, T(2) -weighted, STIR, and DTI-derived fractional anisotropy (FA) images. Maps of the DTI-derived indices, FA, mean diffusivity (MD), longitudinal diffusivity (λ(//) ), and radial diffusivity (λ(⟂) ) along the length of the nerves were generated.

RESULTS

DTI-derived maps delineated the forearm nerves more clearly than images acquired with other sequences. Only ulnar and median nerves were clearly visualized on the DTI-derived FA maps. No significant differences were observed between the left and right forearms in any of the DTI-derived measures. Significant variation in the DTI measures was observed along the length of the nerve. Significant differences in the DTI measures were also observed between the median and ulnar nerves.

CONCLUSION

DTI is superior in visualizing the median and ulnar nerves in the human forearm. The normative data could potentially help distinguish normal from diseased nerves.

摘要

目的

实施扩散张量成像(DTI)方案以可视化人体前臂的周围神经。

材料和方法

这项符合《健康保险流通与责任法案》(HIPAA)的研究获得了我们机构审查委员会的批准,并获得了 10 名健康参与者的书面知情同意。在 3T MRI 扫描仪上使用 8 通道膝关节线圈,采集前臂神经的 T(1) - 和 T(2) -加权涡轮自旋回波加脂肪饱和、短 tau 反转恢复(STIR)和 DTI 序列图像。根据 T(1) - 加权、T(2) - 加权、STIR 和 DTI 衍生的各向异性分数(FA)图像识别神经。生成 DTI 衍生指数、FA、平均扩散系数(MD)、纵向扩散系数(λ(//))和径向扩散系数(λ(⟂))沿神经长度的图谱。

结果

DTI 衍生图谱比其他序列获得的图像更清晰地描绘了前臂神经。只有尺神经和正中神经可以在 DTI 衍生 FA 图谱上清晰显示。在任何 DTI 衍生指标中,左右前臂之间均无显著差异。在神经长度上,DTI 指标有显著变化。在正中神经和尺神经之间,DTI 指标也有显著差异。

结论

DTI 在可视化人体前臂的正中神经和尺神经方面更具优势。这些规范数据有可能有助于区分正常和患病的神经。

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