用于分析快速磁场循环核磁共振频散曲线的稳健算法

Villiam Bortolotti, Pellegrino Conte, Germana Landi, Paolo Lo Meo, Anastasiia Nagmutdinova, Giovanni Vito Spinelli, Fabiana Zama
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引用次数: 0

摘要

快速磁场循环(FFC)核磁共振(NMR)弛豫测量法是一种功能强大的非破坏性磁共振技术,可用于研究低磁场强度下的缓慢分子动力学。FFC-NMR 驰豫测量可在一次实验中深入了解分子在不同时间尺度上的运动。本研究采用无模型方法,将 NMRD 曲线 R1 表示为洛伦兹函数的线性组合,从而解决了在条件不佳的线性最小二乘法框架内拟合数据的难题。针对这一问题,我们对三种正则化方法进行了全面回顾和实验验证,以实现分析 NMRD 剖面的无模型方法。这些方法包括:(1) MF-UPen,利用局部调整的 L2 正则化;(2) MF-L1,基于 L1 惩罚;(3) 结合局部调整的 L2 和全局 L1 惩罚的混合方法。每种方法的正则化参数都是根据平衡和统一惩罚原则自动确定的。我们的贡献包括 MF-UPen 和 MF-MUPen 算法的实施和实验验证,以及 "离散分析 "技术的开发,以评估估计参数的存在范围。这项工作的目的是划定每种算法产生的拟合质量和相关时间分布的差异,从而拓宽用于分析 FFC-NMR 研究中样品结构的软件工具集。研究结果强调了这些算法在分析代表不同潜在情况的样品的 NMRD 图谱中的有效性和适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust Algorithms for the Analysis of Fast-Field-Cycling Nuclear Magnetic Resonance Dispersion Curves
Fast-Field-Cycling (FFC) Nuclear Magnetic Resonance (NMR) relaxometry is a powerful, non-destructive magnetic resonance technique that enables, among other things, the investigation of slow molecular dynamics at low magnetic field intensities. FFC-NMR relaxometry measurements provide insight into molecular motion across various timescales within a single experiment. This study focuses on a model-free approach, representing the NMRD profile R1 as a linear combination of Lorentzian functions, thereby addressing the challenges of fitting data within an ill-conditioned linear least-squares framework. Tackling this problem, we present a comprehensive review and experimental validation of three regularization approaches to implement the model-free approach to analyzing NMRD profiles. These include (1) MF-UPen, utilizing locally adapted L2 regularization; (2) MF-L1, based on L1 penalties; and (3) a hybrid approach combining locally adapted L2 and global L1 penalties. Each method’s regularization parameters are determined automatically according to the Balancing and Uniform Penalty principles. Our contributions include the implementation and experimental validation of the MF-UPen and MF-MUPen algorithms, and the development of a “dispersion analysis” technique to assess the existence range of the estimated parameters. The objective of this work is to delineate the variance in fit quality and correlation time distribution yielded by each algorithm, thus broadening the set of software tools for the analysis of sample structures in FFC-NMR studies. The findings underline the efficacy and applicability of these algorithms in the analysis of NMRD profiles from samples representing different potential scenarios.
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