Multidimensional MRI signature for specific detection of traumatic brain injury in vivo
Inventors
Benjamini, Dan Haim • Basser, Peter J. • Iacono, Diego
Assignees
Henry M Jackson Foundation for Advancedment of Military Medicine Inc • US Department of Health and Human Services
Publication Number
US-12343132-B2
Publication Date
2025-07-01
Expiration Date
2041-07-14
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Abstract
Multidimensional MRI-based methods permit identification and categorization of brain specimens to identify sub-voxel tissue components that are specific to traumatic axon injury or other lesions. Lower dimensional MR spectral data is acquired and processed to provide multidimensional MR data of higher dimensions. One or more spectral ranges are selected that define signatures for brain injury and evaluation of the multidimensional MR data in these ranges is used to locate voxels associated with brain injury. For example, partial one dimensional data sets such as T1, T2, and mean diffusion coefficient (MD) data sets can be combined to provide two dimensional data sets such as T1-T2, MD-T2, and MD-T1 data sets. Using the spectral signatures, a specimen image can be produced showing areas of lesser or greater injury.
Core Innovation
The invention provides multidimensional MRI-based methods for noninvasively assessing nervous system injury, particularly traumatic brain injury (TBI), including mild TBI. The method uses multidimensional MR spectral signatures, combining lower dimensional MR spectral data sets such as T1, T2, and mean diffusion coefficient (MD) to form higher dimensional spectra (e.g. T1-T2, MD-T2, MD-T1, or T1-T2-MD) for detailed tissue characterization. Specific portions of these multidimensional spectra define signatures associated with brain injury, particularly traumatic axonal injury (TAI), allowing for identification and categorization of sub-voxel tissue components specific to TAI lesions, producing images that depict injury distribution.
The problem addressed is the lack of specificity and sensitivity of conventional MRI and diffusion tensor imaging (DTI) methods in detecting subtle brain injuries such as mild TBI or TAI. Standard MRI approaches produce voxel-averaged scalar images limited by spatial resolution (around 1 mm3), often mixing signals from multiple tissue environments and thus failing to detect sparse and minor axonal injuries within a voxel. This limitation leads to low specificity in detecting mild TBI pathology. Existing imaging cannot adequately correlate MRI findings with histopathologic severity or identify injury at the microscopic level. The invention overcomes these limitations by employing multidimensional spectral MRI to isolate injury-specific spectral components corresponding to microscopic pathological alterations.
Claims Coverage
The patent contains several independent claims that define innovative features related to methods and systems for multidimensional MR spectral analysis for brain injury detection.
Multidimensional MR spectral specimen analysis for TBI categorization
Obtaining specimen images comprising voxels with multi-dimensional MR spectra; identifying specimen spectral regions of interest (sROIs); determining specimen signatures from sROIs; comparing specimen signatures to a library of reference signatures associated with different TBI types; and categorizing voxels based on the comparison to form categorized injury images.
Assigning data values based on spectral signature comparison
Assigning data values to specimen sROIs derived from spectral signature comparisons to facilitate categorization and visualization of injury within specimen images.
Use of partial lower dimensional MR spectra to construct multidimensional data
Constructing specimen multidimensional MR spectra from partial lower dimensional MR spectra to improve acquisition efficiency and data richness.
Use of various specific multidimensional MR spectra for categorization
Employing different multidimensional MR spectra including T1-T2, T1-MD, T2-MD, and T1-T2-MD spectra (and other combinations involving Diso, DΔ, θ, ϕ) to categorize brain injury within voxels.
Definition of spectral regions of interest by parameter ranges
Defining reference spectral regions of interest (sROIs) by specific T1, T2, and MD ranges, e.g., T1 about 90–350 ms, T2 about 6–40 ms, and MD about 0.004–0.150 μm2/ms, to specify injury-associated spectral signatures.
System comprising MRI apparatus with stored library of reference signatures and processing capabilities
MRI system including an apparatus for acquiring multidimensional MR spectra; memory storing reference signature libraries associated with different TBI types; and a processor configured to identify specimen sROIs, determine specimen signatures, compare to reference signatures, and produce categorized images showing brain injury.
The claims focus on innovative multidimensional MR spectral methods and systems enabling sensitive, specific detection and imaging of traumatic brain injuries through defined spectral signatures and their comparison to reference libraries, facilitating voxel-level injury categorization and visualization.
Stated Advantages
High specificity in detecting mild traumatic axonal injury (TAI) by isolating sub-voxel tissue components associated with injury.
Ability to produce detailed injury biomarker images that closely correspond to pathological APP histopathology, enabling noninvasive histology.
Improved sensitivity over conventional voxel-averaged MRI and DTI methods by resolving multiple components within a single voxel.
Capability to distinguish injury severity and differentiate between normal-appearing and injured white matter regions within the same brain.
Use of multidimensional spectral acquisition techniques such as MADCO reduces data acquisition time and enables in vivo application.
Documented Applications
Noninvasive identification and characterization of traumatic axonal injury (TAI) in brain specimens, particularly in the corpus callosum.
Assessment and imaging of diffuse axonal injury and other brain lesions associated with traumatic brain injury.
Diagnostic imaging of mild and severe TBI in clinical and research settings using multidimensional MR spectral signatures.
Potential use in guiding treatment decisions following identification and categorization of brain injury.
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