Quantitative chemical exchange saturation transfer (CEST) MRI of glioma using Image Downsampling Expedited Adaptive Least-squares (IDEAL) fitting.
Quantitative chemical exchange saturation transfer (CEST) MRI of glioma using Image Downsampling Expedited Adaptive Least-squares (IDEAL) fitting.
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DOI：
10.1038/s41598-017-00167-y
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发表时间：
2017-03-07
影响因子：
4.6
通讯作者：
Sun PZ
中科院分区：
文献类型：
--
作者：
Zhou IY;Wang E;Cheung JS;Zhang X;Fulci G;Sun PZ
化学交换饱和转移(CEST)磁共振成像对具有可交换质子的稀释代谢物敏感，可用于急性中风和肿瘤等疾病的组织定征。由于CEST对图像信噪比(SNR)、初始值和边界的强烈依赖，采用多池洛伦兹拟合的CEST量化是一个具有挑战性的问题。在这里，我们提出了一种图像下采样加速自适应最小二乘(Idea)拟合算法，该算法基于迭代较少的下采样图像的多池洛伦兹拟合的初始值来量化CEST图像，直到原始分辨率。在具有叠加噪声的体模数据中，理想的拟合提供了比传统拟合更快的拟合速度和更小的变异系数和更高的对比度噪声比。我们进一步将理想拟合法应用于大鼠脑胶质瘤CEST MRI的定量，并证实了其在体内CEST定量方面的优势。除了酰胺质子转移和半固态大分子磁化转移效应的显著变化外，理想的拟合在2 ppm和−1.6 ppm的拟合CEST图中显示出明显的负对比，可能是由于肌酸水平的变化和核Overhauser效应，这是常规方法所没有发现的。预计该方法可以推广到信噪比不是最优的情况下对MRI数据进行量化。
Chemical Exchange Saturation Transfer (CEST) MRI is sensitive to dilute metabolites with exchangeable protons, allowing tissue characterization in diseases such as acute stroke and tumor. CEST quantification using multi-pool Lorentzian fitting is challenging due to its strong dependence on image signal-to-noise ratio (SNR), initial values and boundaries. Herein we proposed an Image Downsampling Expedited Adaptive Least-squares (IDEAL) fitting algorithm that quantifies CEST images based on initial values from multi-pool Lorentzian fitting of iteratively less downsampled images until the original resolution. The IDEAL fitting in phantom data with superimposed noise provided smaller coefficient of variation and higher contrast-to-noise ratio at a faster fitting speed compared to conventional fitting. We further applied the IDEAL fitting to quantify CEST MRI in rat gliomas and confirmed its advantage for in vivo CEST quantification. In addition to significant changes in amide proton transfer and semisolid macromolecular magnetization transfer effects, the IDEAL fitting revealed pronounced negative contrasts of tumors in the fitted CEST maps at 2 ppm and −1.6 ppm, likely arising from changes in creatine level and nuclear overhauser effects, which were not found using conventional method. It is anticipated that the proposed method can be generalized to quantify MRI data where SNR is suboptimal.