Spatially-constrained probability distribution model of incoherent motion (SPIM) for abdominal diffusion-weighted MRI
Spatially-constrained probability distribution model of incoherent motion (SPIM) for abdominal diffusion-weighted MRI
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DOI：
10.1016/j.media.2016.03.009
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发表时间：
2016-08-01
影响因子：
10.9
通讯作者：
Warfield, Simon K.
中科院分区：
文献类型：
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作者：
Kurugol, Sila;Freiman, Moti;Warfield, Simon K.
人体的定量扩散加权磁共振成像(DW-MRI)能够通过测量水分子流动性的变化来表征组织微环境。扩散信号衰减模型参数越来越多地被用于评估肝、脾等腹部器官的各种疾病。然而，以前的信号衰减模型(即单指数、双指数体素内非相干运动(IVIM)和拉伸指数模型)只提供了信号衰减的平均分布，而不是显式地描述扩散尺度的整个范围。在这项工作中，我们提出了一个非相干运动的概率分布模型，该模型使用混合的Gamma分布来充分表征体素内扩散的多尺度性质。此外，我们通过在非相干运动概率分布模型(SPIM)中先验地集成空间同质性，并使用融合自助法(FBM)来估计模型参数，从而提高了分布参数估计的稳健性。我们评估了SPIM模型在模拟数据和68个腹部体内DW-MRI中参数估计的准确性、精确度和重复性方面所取得的改进。我们的结果表明，与以前的模型相比，SPIM模型不仅大大减少了参数估计误差高达26%，而且通过降低估计参数的变异系数(CV)，显著提高了参数估计(配对学生t检验，p<；0.0001)的稳健性。此外，与以前的模型相比，SPIM模型改进了参数估计的可重复性，包括会话内(高达47%)和会话间(高达30%)的估计。因此，SPIM模型有可能提高腹部DW-MRI定量分析的准确性、精密度和稳健性，用于临床应用。(C)2016爱思唯尔B.V.保留所有权利。
Quantitative diffusion-weighted MR imaging (DW-MRI) of the body enables characterization of the tissue microenvironment by measuring variations in the mobility of water molecules. The diffusion signal decay model parameters are increasingly used to evaluate various diseases of abdominal organs such as the liver and spleen. However, previous signal decay models (i.e., mono-exponential, bi-exponential intra-voxel incoherent motion (IVIM) and stretched exponential models) only provide insight into the average of the distribution of the signal decay rather than explicitly describe the entire range of diffusion scales. In this work, we propose a probability distribution model of incoherent motion that uses a mixture of Gamma distributions to fully characterize the multi-scale nature of diffusion within a voxel. Further, we improve the robustness of the distribution parameter estimates by integrating spatial homogeneity prior into the probability distribution model of incoherent motion (SPIM) and by using the fusion bootstrap solver (FBM) to estimate the model parameters. We evaluated the improvement in quantitative DW-MRI analysis achieved with the SPIM model in terms of accuracy, precision and reproducibility of parameter estimation in both simulated data and in 68 abdominal in-vivo DW-MRIs. Our results show that the SPIM model not only substantially reduced parameter estimation errors by up to 26%; it also significantly improved the robustness of the parameter estimates (paired Student's t-test, p < 0.0001) by reducing the coefficient of variation (CV) of estimated parameters compared to those produced by previous models. In addition, the SPIM model improves the parameter estimates reproducibility for both intra- (up to 47%) and inter-session (up to 30%) estimates compared to those generated by previous models. Thus, the SPIM model has the potential to improve accuracy, precision and robustness of quantitative abdominal DW-MRI analysis for clinical applications. (C) 2016 Elsevier B.V. All rights reserved.