NMR Measurement Protocol for Anisotropic Diffusion Resolution
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Solution Overview
Problem
Current methods for characterizing heterogeneous anisotropic materials face challenges in resolving nuclear relaxation and diffusion characteristics, particularly when components have similar isotropic or anisotropic diffusion values, limiting the ability to distinguish properties of diffusing components.
Innovation Solution
The method involves a magnetic resonance measurement protocol that encodes different levels of magnetic resonance signal attenuation due to nuclear relaxation, correlating diffusion characteristics with nuclear relaxation characteristics, using a diffusion-encoding tensor representation with multiple non-zero eigenvalues and varying acquisition parameters to estimate a probability distribution of nuclear relaxation and diffusion characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional NMR diffusion measurements are used, then diffusion coefficients can be measured, but components with similar diffusion values cannot be reliably distinguished
Solution Approach 1:
The patent extends conventional single-parameter diffusion measurements to multi-dimensional characterization by simultaneously measuring diffusion coefficients, relaxation times (T1, T2), and orientation distribution functions. This dimensional expansion in parameter space enables differentiation of components that would be indistinguishable using diffusion coefficients alone.
Solution Approach 2:
The patent varies multiple acquisition parameters including gradient strengths, echo times, and pulse sequence timings to encode different combinations of diffusion and relaxation information. By systematically changing these parameters across multiple measurements, the method extracts correlated information about multiple material properties that enhances component resolution.
2Measurement precision
If diffusion encoding with discrete directions is used, then anisotropic diffusion can be characterized, but interpretational ambiguities arise in heterogeneous materials
Solution Approach 1:
The patent employs iterative fitting procedures where the measured signal intensities are compared against theoretical models, and the fitting parameters (diffusion tensor elements, orientation distributions) are refined through multiple passes. This feedback loop resolves ambiguities by consistently adjusting parameters to match the observed multi-dimensional data pattern.
Solution Approach 2:
The patent treats heterogeneous anisotropic materials as composite systems with multiple distinct components, each having its own diffusion tensor and orientation distribution. By modeling the total signal as a sum of component contributions and using multi-parameter measurements, the method disentangles the mixed signals from different components that would be ambiguous in simpler models.
3Loss of information
If multiple NMR measurements with varying parameters are performed, then correlated information about diffusion and relaxation can be obtained, but measurement time increases
Solution Approach 1:
The patent merges diffusion-weighted and relaxation-weighted measurements into a unified experimental protocol. By designing pulse sequences that simultaneously encode both diffusion and relaxation information in each measurement, the method obtains correlated parameters more efficiently than performing separate measurement series.
Solution Approach 2:
The patent uses periodic variation of acquisition parameters across a series of measurements, systematically cycling through different gradient strengths, echo times, and pulse sequences. This periodic sampling strategy efficiently explores the parameter space to capture correlated information while minimizing redundant measurements and total acquisition time.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the resolving power for diffusing components by disentangling entangled information about diffusion tensors, relaxation rates, and orientations, even in the presence of subtle differences, allowing for improved characterization and imaging.
Implementation Method 1
Nuclear magnetic resonance (NMR) methods have a unique ability to non-invasively characterize the properties of liquids in heterogeneous porous materials
Implementation Method 2
Through application of magnetic field gradients, the phase and amplitude of the NMR signal can be encoded with information about the spatial position and translational motion of the pore liquids
Implementation Method 3
The directional dependence of the observed value of D is captured in the diffusion tensor D
Implementation Method 4
NMR observables such as offset frequency, longitudinal relaxation rate R1, and transverse relaxation rate R2
Data Source
Figure 1a~1b
Figure 2a
Figure 2b
AI summary
According to an aspect of the present inventive concept, there is provided a method of extracting information about a sample, the method comprising: performing a plurality of magnetic resonance measurements on the sample, each measurement including subjecting the sample to an encoding sequence, at least a part of the sequence being adapted to encode a magnetic resonance signal attenuation due to nuclear relaxation and diffusion, wherein at least one parameter of a gradient pulse sequence is varied between at least a subset of said plurality of measurements,and at least one measurement of said subset includes a gradient pulse sequence having a diffusion-encoding tensor representation with more than one non-zero eigenvalue, and wherein at least a subset of said plurality of measurements include encoding for different levels of magnetic resonance signal attenuation due to nuclear relaxation; and extracting information about the sample from signals resulting from said plurality of magnetic resonance measurements, the information including nuclear relaxation and diffusion characteristics for the sample.