Multi-dimensional spectroscopic NMR and MRI using marginal distributions
Inventors
Basser, Peter J. • Benjamini, Dan H.
Assignees
US Department of Health and Human Services
Publication Number
US-11415652-B2
Publication Date
2022-08-16
Expiration Date
2037-08-11
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Abstract
Multi-dimensional spectra associated with a specimen are reconstructed using lower dimensional spectra as constraints. For example, a two-dimensional spectrum associated with diffusivity and spin-lattice relaxation time is obtained using one-dimensional spectra associated with diffusivity and spin-lattice relaxation time, respectively, as constraints. Data for a full two dimensional spectrum are not acquired, leading to significantly reduced data acquisition times.
Core Innovation
The invention provides novel magnetic resonance (MR) methods and systems that reconstruct multi-dimensional spectra associated with a specimen using lower dimensional spectra, specifically one-dimensional marginal distributions, as constraints. A key example presented is obtaining a two-dimensional spectrum related to diffusivity and spin-lattice relaxation time by applying one-dimensional spectra for each characteristic as constraints, which significantly reduces data acquisition times by avoiding acquisition of the full two-dimensional dataset.
The disclosed methods, referred to as marginal distributions constrained optimization (MADCO), stabilize and accelerate reconstruction of two-dimensional spectra by leveraging a priori information from one-dimensional measurements. This approach reduces the number of acquisitions required for accurate multidimensional spectroscopy, making feasible biological, preclinical, and clinical applications previously limited due to long acquisition times and significant computational resource demands.
The problem addressed is the ill-conditioned nature of inverting Fredholm integrals of the first kind inherent in multidimensional NMR and MRI relaxometry, which traditionally requires large data sets and long acquisition times. Conventional multidimensional experiments, particularly two-dimensional diffusion/relaxation measurements, have been largely infeasible in clinical settings due to limitations in achievable pulse sequences and safety concerns such as specific absorption rate.
Claims Coverage
The patent contains multiple independent claims that define methods and systems for reconstructing two-dimensional magnetic resonance spectra using marginal distributions as constraints.
Acquisition of MR specimen data with varying dual acquisition parameters
Acquiring a selected set of magnetic resonance specimen data by varying at least a first and a second MR acquisition parameter across respective ranges, such that the data are associated with two specimen characteristics.
Determination of one-dimensional marginal distributions dependent on acquisition parameters
Determining first and second marginal distributions associated with the first and second specimen characteristics based on the acquired MR data, where these marginal distributions depend on a selected combination of the first and second MR acquisition parameters.
Reconstruction of two-dimensional spectrum using marginal distribution constraints
Reconstructing a two-dimensional spectrum associated with the specimen using the first and second marginal distributions as constraints, improving stability and reducing data acquisition requirements.
Use of 1 regularization in determining marginal distributions
Applying 1 regularization in the determination of the first and second marginal distributions to promote sparsity and accuracy, especially for specimens comprising discrete components.
System configuration for MR data acquisition and spectral reconstruction
An MR system comprising a data acquisition system and a data processor operable to acquire MR data based on first and second acquisition parameters and reconstruct two-dimensional MR spectra using marginal distributions as constraints.
Applicability to various specimen characteristics and acquisition parameters
The invention applies to specimen characteristics such as diffusivity, spin-lattice relaxation time, and spin-spin relaxation time, and acquisition parameters including b-value and inversion time, with parameters possibly independent.
The independent claims collectively cover methods of acquiring magnetic resonance data by varying dual acquisition parameters, determining corresponding one-dimensional marginal distributions using 1 regularization, and reconstructing two-dimensional spectra using these marginal distributions as constraints, as well as systems configured to perform such acquisition and reconstruction, applicable to varied specimen characteristics and acquisition parameters.
Stated Advantages
Significantly reduced data acquisition times by using one-dimensional marginal distributions as constraints, enabling faster multidimensional spectrum reconstruction.
Improved stability and accuracy of multidimensional spectral reconstruction compared to conventional unconstrained methods.
Reduced computational requirements due to decreased data volume and improved inversion conditioning.
Feasibility of applying multidimensional NMR and MRI to biological, preclinical, and clinical applications previously unfeasible due to long scan times and safety concerns.
Capability to measure complex microstructural and molecular exchange dynamics in specimens with clinically applicable scan durations.
Documented Applications
In vivo microdynamic MRI scans of biological tissues to characterize nerve tissue microstructure and water exchange dynamics.
Clinical MRI applications including examination of inflammation, cancer, stroke, neuroplasticity, normal and injured ex vivo tissue samples.
Whole-body imaging of organs such as heart, placenta, liver, kidneys, spleen, colon, prostate, skeletal and other muscles, and peripheral nerves.
Genotype/phenotype studies and other animal model investigations.
Analysis of non-biological materials including foods, organic and synthetic polymers and gels, chemical engineering separation systems, soil, clay, rock, and other porous and non-porous media.
Evaluation of biological specimens ex vivo or in vitro, including animals, plants, microorganisms, or organs thereof.
Studies of developmental trajectories, disorders, diseases, trauma sequelae, inflammatory responses, wound healing, and cellular and tissue processes in living organisms.
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