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模拟骨骼肌中组织微观结构与扩散张量之间的关系。

Relationships between tissue microstructure and the diffusion tensor in simulated skeletal muscle.

机构信息

Department of Bioengineering, University of California San Diego, La Jolla, California, USA.

Institute of Engineering in Medicine, San Diego, California, USA.

出版信息

Magn Reson Med. 2018 Jul;80(1):317-329. doi: 10.1002/mrm.26993. Epub 2017 Oct 31.

Abstract

PURPOSE

To establish a series of relationships defining how muscle microstructure and diffusion tensor imaging (DTI) are related.

METHODS

The relationship among key microstructural features of skeletal muscle (fiber size, fibrosis, edema, and permeability) and the diffusion tensor were systematically simulated over physiologically relevant dimensions individually, and in combination, using a numerical simulation application. Stepwise multiple regression was used to identify which microstructural features of muscle significantly predict the diffusion tensor using single-echo and multi-echo DTI pulse sequences. Simulations were also performed in models with histology-informed geometry to investigate the relationship between fiber size and the diffusion tensor in models with real muscle geometry.

RESULTS

Fiber size is the strongest predictor of λ2, λ3, mean diffusivity, and fractional anisotropy in skeletal muscle, accounting for approximately 40% of the variance in the diffusion model when calculated with single-echo DTI. This increased to approximately 70% when diffusion measures were calculated from the short T component of the multi-echo DTI sequence. This nonlinear relationship begins to plateau in fibers with greater than 60-μm diameter.

CONCLUSIONS

As the normal fiber size of a human muscle fiber is 40 to 60 μm, this suggests that DTI is a sensitive tool to monitor muscle atrophy, but may be limited in measurements of muscle with larger fibers. Magn Reson Med 80:317-329, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

摘要

目的

建立一系列关系,定义肌肉微观结构和扩散张量成像(DTI)之间的关系。

方法

使用数值模拟应用程序,分别系统地模拟骨骼肌肉的关键微观结构特征(纤维大小、纤维化、水肿和通透性)与扩散张量之间的关系,并在生理相关维度上进行组合。逐步多元回归用于确定肌肉的哪些微观结构特征可以使用单回波和多回波 DTI 脉冲序列显著预测扩散张量。还在具有组织学信息的几何模型中进行了模拟,以研究纤维大小与具有真实肌肉几何形状的扩散张量之间的关系。

结果

纤维大小是骨骼肌中 λ2、λ3、平均扩散率和各向异性分数的最强预测因子,当使用单回波 DTI 计算时,占扩散模型方差的约 40%。当从多回波 DTI 序列的短 T 分量计算扩散测量值时,这一比例增加到约 70%。这种非线性关系在纤维直径大于 60 μm 时开始趋于平稳。

结论

由于人类肌肉纤维的正常纤维大小为 40 至 60 μm,这表明 DTI 是一种敏感的工具,可以监测肌肉萎缩,但在测量纤维较大的肌肉时可能会受到限制。磁共振医学 80:317-329,2018。© 2017 国际磁共振学会。

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