Biomedical NMR, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
J Magn Reson Imaging. 2012 Jul;36(1):237-48. doi: 10.1002/jmri.23608. Epub 2012 Feb 14.
To design a time-efficient patient-friendly clinical diffusion tensor MRI protocol and postprocessing tool to study the complex muscle architecture of the human forearm.
The 15-minute examination was done using a 3 T system and consisted of: T(1) -weighted imaging, dual echo gradient echo imaging, single-shot spin-echo echo-planar imaging (EPI) diffusion tensor MRI. Postprocessing comprised of signal-to-noise improvement by a Rician noise suppression algorithm, image registration to correct for motion and eddy currents, and correction of susceptibility-induced deformations using magnetic field inhomogeneity maps. Per muscle one to five regions of interest were used for fiber tractography seeding. To validate our approach, the reconstructions of individual muscles from the in vivo scans were compared to photographs of those dissected from a human cadaver forearm.
Postprocessing proved essential to allow muscle segmentation based on combined T(1) -weighted and diffusion tensor data. The protocol can be applied more generally to study human muscle architecture in other parts of the body.
The proposed protocol was able to visualize the muscle architecture of the human forearm in great detail and showed excellent agreement with the dissected cadaver muscles.
设计一种省时、方便患者的临床扩散张量 MRI 方案和后处理工具，以研究人体前臂复杂的肌肉结构。
该 15 分钟的检查在 3T 系统上进行，包括：T1 加权成像、双回波梯度回波成像、单次激发自旋回波平面成像（EPI）扩散张量 MRI。后处理包括通过 Rician 噪声抑制算法改善信噪比、图像配准以纠正运动和涡流、以及使用磁场不均匀性图校正感生变形。针对每条肌肉，使用一到五个感兴趣区进行纤维束追踪种子的设定。为了验证我们的方法，将来自活体扫描的单个肌肉重建与从人体尸体前臂解剖的照片进行了比较。
后处理对于基于 T1 加权和扩散张量数据的肌肉分割至关重要。该方案可更广泛地应用于研究人体其他部位的肌肉结构。
所提出的方案能够非常详细地可视化人体前臂的肌肉结构，并且与解剖的尸体肌肉显示出极好的一致性。
