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双脉冲场梯度弥散磁共振成像评估骨骼肌微观结构。

Double pulsed field gradient diffusion MRI to assess skeletal muscle microstructure.

机构信息

Department of Orthopedic Surgery, University of California, San Diego, California, USA.

Department of Nanoengineering, University of California, San Diego, San Diego, California, USA.

出版信息

Magn Reson Med. 2023 Oct;90(4):1582-1593. doi: 10.1002/mrm.29751. Epub 2023 Jul 1.

Abstract

PURPOSE

Preliminary study to determine whether double pulsed field gradient (PFG) diffusion MRI is sensitive to key features of muscle microstructure related to function.

METHODS

The restricted diffusion profile of molecules in models of muscle microstructure derived from histology were systematically simulated using a numerical simulation approach. Diffusion tensor subspace imaging analysis of the diffusion signal was performed, and spherical anisotropy (SA) was calculated for each model. Linear regression was used to determine the predictive capacity of SA on the fiber area, fiber diameter, and surface area to volume ratio of the models. Additionally, a rat model of muscle hypertrophy was scanned using a single PFG and a double PFG pulse sequence, and the restricted diffusion measurements were compared with histological measurements of microstructure.

RESULTS

Excellent agreement between SA and muscle fiber area (r  = 0.71; p < 0.0001), fiber diameter (r  = 0.83; p < 0.0001), and surface area to volume ratio (r  = 0.97; p < 0.0001) in simulated models was found. In a scanned rat leg, the distribution of these microstructural features measured from histology was broad and demonstrated that there is a wide variance in the microstructural features observed, similar to the SA distributions. However, the distribution of fractional anisotropy measurements in the same tissue was narrow.

CONCLUSIONS

This study demonstrates that SA-a scalar value from diffusion tensor subspace imaging analysis-is highly sensitive to muscle microstructural features predictive of function. Furthermore, these techniques and analysis tools can be translated to real experiments in skeletal muscle. The increased dynamic range of SA compared with fractional anisotropy in the same tissue suggests increased sensitivity to detecting changes in tissue microstructure.

摘要

目的

初步研究双脉冲梯度(PFG)弥散 MRI 是否能敏感地反映与功能相关的肌肉微观结构的关键特征。

方法

使用数值模拟方法,对源自组织学的肌肉微观结构模型中的分子受限扩散分布进行了系统模拟。对扩散信号进行了弥散张量子空间成像分析,并计算了各模型的各向异性度(SA)。采用线性回归确定 SA 对模型的纤维面积、纤维直径和表面积与体积比的预测能力。此外,对肌肉肥大的大鼠模型分别进行了单次 PFG 和双 PFG 脉冲序列扫描,并将受限扩散测量结果与微观结构的组织学测量结果进行了比较。

结果

在模拟模型中,SA 与肌肉纤维面积(r=0.71;p<0.0001)、纤维直径(r=0.83;p<0.0001)和表面积与体积比(r=0.97;p<0.0001)之间具有极好的一致性。在扫描的大鼠腿部中,从组织学测量得到的这些微观结构特征的分布较宽,表明观察到的微观结构特征存在广泛的差异,与 SA 分布相似。然而,同一组织中各向异性分数测量值的分布较窄。

结论

本研究表明,SA(弥散张量子空间成像分析的标量值)对可预测功能的肌肉微观结构特征具有高度敏感性。此外,这些技术和分析工具可以转化为骨骼肌的实际实验。在同一组织中,SA 的动态范围比各向异性分数大,表明其对检测组织微观结构变化的敏感性更高。

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