System and method for evaluating anisotropic viscoelastic properties of fibrous structures
Inventors
Assignees
Publication Number
US-9965852-B2
Publication Date
2018-05-08
Expiration Date
2034-04-11
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Abstract
System and method for diagnosing brain conditions including evaluating fiber pathways of white matter tracts using a diffusion tensor imaging (DTI) process, tracking the propagation of waves traveling at specific angles to the fiber pathways by performing a 3D magnetic resonance elastography (MRE) process at the same spatial resolution and voxel position as the DTI, analyzing the viscoelastic properties using an inversion having at least nine elastic coefficients, determining the curvature along the pathways, differentiating the spatial-spectral filter twice with respect to arc length along the pathways, and diagnosing a brain condition based on the viscoelastic properties.
Core Innovation
The invention provides a noninvasive system and method to evaluate the anisotropic viscoelastic properties of fibrous structures such as neuronal pathways in the human brain (white matter) and muscle for diagnostic purposes. The approach fuses diffusion tensor imaging (DTI) and magnetic resonance elastography (MRE) data at the same spatial resolution and voxel positions, applies spatial-spectral filtering and Helmholtz decomposition to identify elastic wave components traveling at specific angles to the fiber pathways, and uses an adaptive anisotropic inversion algorithm to analyze the viscoelastic properties through elastic coefficients evaluating complex biological media including the effects of curvature.
The problem addressed is that prior noninvasive methods generally assumed isotropic media using inversion algorithms with only two elastic coefficients. Biological media like muscle and white matter are anisotropic, characterized by multiple elastic constants dependent on wave propagation direction along fibrous structures, requiring more sophisticated inversion methods. Additionally, these methods require knowledge of waveguide orientation and appropriate anisotropic inversion algorithms, which existing techniques lack. Thus, an improved system to evaluate dynamic models and viscoelastic constants in arbitrarily curved anisotropic biological media is needed to provide accurate diagnostic information.
This system uses orthotropic, monoclinic, and triclinic inversion models to accommodate increasing levels of anisotropy. It includes novel procedures such as analytical evaluation of Laplacians incorporating curvature effects, global and local spatial-spectral filtering to reduce noise, sliding window band-limited filtering based on spectral analyses, calculation of a rotating reference frame using a point-normal plane representation to avoid ambiguity, and automated tractography algorithms for pathway continuation. These innovations enable comprehensive characterization of the viscoelastic properties of anisotropic fibrous structures for clinical diagnostics including neurological diseases.
Claims Coverage
The patent claims cover three independent inventions: a noninvasive computer-based method for diagnosing brain conditions, an alternative method for diagnosis of brain conditions, and a system for diagnosing a brain condition. The claims focus on novel techniques integrating imaging modalities, filtering processes, inversion algorithms, and accounting for curvature in fibrous anisotropic media.
Noninvasive computer-based method for brain diagnosis using spatial-spectral filtering and curvature-aware Laplacians
A method comprising measuring physical positions of fiber pathways within an anisotropic medium, measuring dynamic elastic displacements, applying a spatial-spectral filter to obtain elastic wave components traveling at specific angles relative to the pathways, applying a Helmholtz decomposition to determine longitudinal and transverse components, computing Laplacians by differentiating the components twice along parameterized fiber pathways including curvature effects, evaluating elastic coefficients by dividing acceleration by Laplacians, and diagnosing brain conditions based on those coefficients.
Extension of the method with global filtering, local reference frame calculation, and automated tractography
Including applying a global band-limited filter prior to spatial-spectral filtering, calculating local reference frames based on the global coordinate system and planes perpendicular to the fiber pathways, and using automated tractography for pathway extension.
Utilizing fusion of Magnetic Resonance Elastography (MRE) and Diffusion Tensor Imaging (DTI) for measurement and analysis
Measuring dynamic elastic displacements using MRE, determining fiber pathways with DTI, performing spatial-spectral filtering based on combined results from MRE and DTI, computing Laplacians incorporating data from both modalities to reflect curvature, and diagnosing brain conditions through extracted viscoelastic coefficients.
Inversion model determination including orthotropic, monoclinic, triclinic, hexagonal, and trigonal models
Determining and applying an appropriate inversion model for the fiber pathways based on spatial-spectral and Helmholtz output, supporting various symmetry levels including orthotropic, monoclinic, triclinic, hexagonal, and trigonal.
System for diagnosing brain condition integrating modular processing units
A system comprising measuring devices for physical fiber pathway positions, displacement processors for dynamic elastic displacement within volumes around fibers, filter processors applying spatial-spectral filters and Helmholtz decomposition, Laplacian processors computing curvature-aware Laplacians, stiffness processors evaluating elastic coefficients, and diagnosis processors diagnosing brain conditions based on those coefficients, with optional global band-limited filtering, local reference frame calculation, and automated tractography.
The claims collectively cover advanced methods and corresponding systems that integrate diffusion tensor imaging and magnetic resonance elastography data through spatial-spectral filtering, Helmholtz decomposition, curvature-inclusive Laplacian computation, anisotropic inversion models, and diagnostic evaluation of brain conditions involving anisotropic fibrous structures.
Stated Advantages
Provides a clinically relevant evaluation of complex, unknown biological media noninvasively within minutes without harmful X-ray techniques.
Capable of detecting neuropathologies such as Amyotrophic Lateral Sclerosis (ALS) that isotropic inversion methods cannot detect.
Enables evaluation of orthotropic myocardial muscle stiffness and other white matter structure properties in vivo.
Accurately includes effects of curvature of waveguides via analytical evaluation of Laplacians.
Reduces noise and improves inversion results through spatial-spectral filtering procedures including global band-limited filtering and sliding window band-limited filters.
Relieves ambiguity in local coordinate system calculation by using a point-normal reference frame representation instead of standard Frenet frames.
Automated tractography algorithms facilitate evaluation of Laplacians by pathway continuation using nearest neighbor fiber vectors.
Documented Applications
Diagnosis of neurological conditions such as Amyotrophic Lateral Sclerosis (ALS), Multiple Sclerosis (MS), Alzheimer's Disease (AD), and Traumatic Brain Injury (TBI).
Evaluation of muscle diseases including muscular degeneration and myocardial infarction in the heart.
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