Reci A, Ainte M I, Sederman A J, Mantle M D, Gladden L F
Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge CB3 0AS, United Kingdom.
Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge CB3 0AS, United Kingdom.
Magn Reson Imaging. 2019 Feb;56:14-18. doi: 10.1016/j.mri.2018.09.029. Epub 2018 Nov 6.
A recently reported method, based on the Cramér-Rao Lower Bound theory, for optimising sampling patterns for a wide range of nuclear magnetic resonance (NMR) experiments is applied to the problem of optimising sampling patterns for bi-exponentially decaying signals. Sampling patterns are optimised by minimizing the percentage error in estimating the most difficult to estimate parameter of the bi-exponential model, termed the objective function. The predictions of the method are demonstrated in application to pulsed field gradient NMR data recorded for the two-component diffusion of a binary mixture of methane/ethane in a zeolite. It is shown that the proposed method identifies an optimal sampling pattern with the predicted objective function being within 10% of that calculated from the experiment dataset. The method is used to advise on the number of sampled points and the noise level needed to resolve two-component systems characterised by a range of ratios of populations and diffusion coefficients. It is subsequently illustrated how the method can be used to reduce the experiment acquisition time while still being able to resolve a given two-component system.
一种最近报道的基于克拉美罗下界理论的方法，用于优化各种核磁共振（NMR）实验的采样模式，现应用于双指数衰减信号的采样模式优化问题。通过最小化双指数模型中最难估计参数（称为目标函数）估计中的百分比误差来优化采样模式。该方法的预测结果在应用于甲烷/乙烷二元混合物在沸石中的两组分扩散所记录的脉冲场梯度NMR数据中得到了验证。结果表明，所提出的方法识别出的最优采样模式，其预测目标函数与从实验数据集计算得出的目标函数相差在10%以内。该方法用于就分辨具有不同丰度和扩散系数比值的两组分系统所需的采样点数和噪声水平提供建议。随后说明了该方法如何用于减少实验采集时间，同时仍能分辨给定的两组分系统。
