...
首页> 外文期刊>NMR in biomedicine >The effect of noise and lipid signals on determination of Gaussian and non-Gaussian diffusion parameters in skeletal muscle
【24h】

The effect of noise and lipid signals on determination of Gaussian and non-Gaussian diffusion parameters in skeletal muscle

机译:噪声和脂质信号对骨骼肌肌肉高斯和非高斯扩散参数测定的影响

获取原文
获取原文并翻译 | 示例

摘要

This work characterizes the effect of lipid and noise signals on muscle diffusion parameter estimation in several conventional and non-Gaussian models, the ultimate objectives being to characterize popular fat suppression approaches for human muscle diffusion studies, to provide simulations to inform experimental work and to report normative non-Gaussian parameter values. The models investigated in this work were the Gaussian monoexponential and intravoxel incoherent motion (IVIM) models, and the non-Gaussian kurtosis and stretched exponential models. These were evaluated via simulations, and in vitro and in vivo experiments. Simulations were performed using literature input values, modeling fat contamination as an additive baseline to data, whereas phantom studies used a phantom containing aliphatic and olefinic fats and muscle-like gel. Human imaging was performed in the hamstring muscles of 10 volunteers. Diffusion-weighted imaging was applied with spectral attenuated inversion recovery (SPAIR), slice-select gradient reversal and water-specific excitation fat suppression, alone and in combination. Measurement bias (accuracy) and dispersion (precision) were evaluated, together with intra-and inter-scan repeatability. Simulations indicated that noise in magnitude images resulted in <6% bias in diffusion coefficients and non-Gaussian parameters (alpha, K), whereas baseline fitting minimized fat bias for all models, except IVIM. In vivo, popular SPAIR fat suppression proved inadequate for accurate parameter estimation, producing non-physiological parameter estimates without baseline fitting and large biases when it was used. Combining all three fat suppression techniques and fitting data with a baseline offset gave the best results of all the methods studied for both Gaussian diffusion and, overall, for non-Gaussian diffusion. It produced consistent parameter estimates for all models, except IVIM, and highlighted non-Gaussian behavior perpendicular to muscle fibers (alpha similar to 0.95, K similar to 3.1). These results show that effective fat suppression is crucial for accurate measurement of non-Gaussian diffusion parameters, and will be an essential component of quantitative studies of human muscle quality.
机译:这项工作表征了脂质和噪声信号对几种传统和非高斯模型的肌肉扩散参数估计的影响,最终目标是表征人类肌肉扩散研究的流行脂肪抑制方法,提供仿真,告知实验工作和报告规范的非高斯参数值。在这项工作中调查的模型是高斯单展型和椎间克拉尔非连贯的运动(IVIM)模型,以及非高斯峰和拉伸指数模型。这些通过模拟和体内和体内实验进行评估。使用文献输入值进行仿真,将脂肪污染为数据的添加基线进行模拟,而Phantom研究使用含有脂族和烯烃脂肪和肌肉状凝胶的幻影。人体成像在10名志愿者的腿筋肌肉中进行。施加扩散加权成像,用光谱衰减反演恢复(SPAIR),切片选择梯度反转和采用特异性激发脂肪抑制,单独和组合。评估测量偏差(精度)和分散(精度),以及跨扫描互补可重复性。模拟表明,幅度图像中的噪声导致扩散系数和非高斯参数(alpha,k)中的<6%偏差,而除Ivim之外,基线拟合最小化所有型号的脂肪偏差。在体内,流行的Spair脂肪抑制被证明是准确参数估计的不足,在使用时产生非生理参数估计而没有基线拟合和大偏差。结合所有三种脂肪抑制技术和拟合数据的基线偏移,对高斯扩散的所有方法进行了最佳结果,并且总的来说对于非高斯扩散。它为所有模型,除Ivim之外的所有模型产生了一致的参数估计,并突出显示垂直于肌肉纤维的非高斯行为(类似于0.95,k的alpha类似于3.1)。这些结果表明,有效的脂肪抑制对于准确测量非高斯扩散参数至关重要,并且将是人类肌肉质量的定量研究的重要组成部分。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号