Laboratory of Biophysics, Wageningen University & Research, Wageningen, The Netherlands.
Wageningen NMR Centre, Wageningen University & Research, Wageningen, The Netherlands.
Sci Rep. 2017 Apr 13;7(1):861. doi: 10.1038/s41598-017-00864-8.
Quantitative magnetic resonance imaging (qMRI) is a versatile, non-destructive and non-invasive tool in life, material, and medical sciences. When multiple components contribute to the signal in a single pixel, however, it is difficult to quantify their individual contributions and characteristic parameters. Here we introduce the concept of phasor representation to qMRI to disentangle the signals from multiple components in imaging data. Plotting the phasors allowed for decomposition, unmixing, segmentation and quantification of our in vivo data from a plant stem, a human and mouse brain and a human prostate. In human brain images, we could identify 3 main T components and 3 apparent diffusion coefficients; in human prostate 5 main contributing spectral shapes were distinguished. The presented phasor analysis is model-free, fast and accurate. Moreover, we also show that it works for undersampled data.
定量磁共振成像（qMRI）是生命科学、材料科学和医学领域中一种通用的、非破坏性和非侵入性的工具。然而，当单个像素中的信号由多个分量组成时，很难量化它们各自的贡献和特征参数。在这里，我们将相位向量表示法引入到 qMRI 中，以分离成像数据中多个分量的信号。绘制相位向量可以对我们来自植物茎、人和鼠脑以及人前列腺的体内数据进行分解、混合、分割和量化。在人脑图像中，我们可以识别出 3 个主要的 T 分量和 3 个表观扩散系数；在人前列腺中，区分出了 5 个主要的贡献谱形状。所提出的相位向量分析是无模型的、快速和准确的。此外，我们还表明它适用于欠采样数据。
