Department of Biomedical Engineering, The Iby and Aladar Fleischman Faculty of Engineering, Tel-Aviv University, Tel-Aviv, Israel.
J Magn Reson. 2013 May;230:198-204. doi: 10.1016/j.jmr.2013.03.001. Epub 2013 Mar 14.
Estimation of pore size distribution of well calibrated phantoms using NMR is demonstrated here for the first time. Porous materials are a central constituent in fields as diverse as biology, geology, and oil drilling. Noninvasive characterization of monodisperse porous samples using conventional pulsed-field gradient (PFG) NMR is a well-established method. However, estimation of pore size distribution of heterogeneous polydisperse systems, which comprise most of the materials found in nature, remains extremely challenging. Concentric double pulsed-field gradient (CDPFG) is a 2-D technique where both q (the amplitude of the diffusion gradient) and φ (the relative angle between the gradient pairs) are varied. A recent prediction indicates this method should produce a more accurate and robust estimation of pore size distribution than its conventional 1-D versions. Five well defined size distribution phantoms, consisting of 1-5 different pore sizes in the range of 5-25 μm were used. The estimated pore size distributions were all in good agreement with the known theoretical size distributions, and were obtained without any a priori assumption on the size distribution model. These findings support that in addition to its theoretical benefits, the CDPFG method is experimentally reliable. Furthermore, by adding the angle parameter, sensitivity to small compartment sizes is increased without the use of strong gradients, thus making CDPFG safe for biological applications.
首次展示了使用 NMR 对校准良好的模型进行孔径分布估计的方法。多孔材料是生物学、地质学和石油钻探等领域的核心组成部分。使用传统的脉冲梯度场(PFG)NMR 对单分散多孔样品进行非侵入性表征是一种成熟的方法。然而,对由大多数天然存在的材料组成的异质多分散体系的孔径分布进行估计仍然极具挑战性。同心双脉冲梯度场(CDPFG)是一种 2D 技术,其中 q(扩散梯度的幅度)和 φ(梯度对之间的相对角度)都发生变化。最近的预测表明,与传统的 1D 版本相比,该方法应能更准确、更稳健地估计孔径分布。使用了五个具有明确定义的尺寸分布模型,这些模型包含在 5-25 μm 范围内的 1-5 个不同的孔径。估计的孔径分布与已知的理论尺寸分布非常吻合,并且在没有对尺寸分布模型进行任何先验假设的情况下获得。这些发现表明,除了具有理论优势外,CDPFG 方法在实验上也是可靠的。此外,通过添加角度参数,可以在不使用强梯度的情况下提高对小隔室尺寸的灵敏度,从而使 CDPFG 适用于生物应用。