The United States of America, As Represented by the Secretary, Department of Health and Human Services

The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc.

Dan H Benjamini

Peter J Basser

Diego Iacono

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.

Multidimensional MRI signature for specific detection of traumatic brain injury in vivo

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.

Multi-dimensional spectroscopic NMR and MRI using marginal distributions

Described herein are exemplary methods for estimating a nonparametric joint radius-length (R-L) distribution of an ensemble of porous elements represented generally by finite cylinders. Some described methods comprise estimating an eccentricity distribution of a group of anisotropic porous elements. For example, disclosed methods can be applied to estimate a nonparametric joint R-L distribution of injured axons in nervous tissue, muscle tissue, plant elements, or other porous materials. Employing a novel three dimensional (3-D) double pulsed-field gradient (d-PFG) magnetic resonance (MR) acquisition scheme, both the marginal radius and length distributions of a population of generally cylindrical porous elements can be obtained. The marginal radius and length distributions can then b e used to constrain and stabilize the estimate of the joint radius-length distribution. Using the marginal distributions as constraints allows the joint R-L distribution to be reconstructed from an underdetermined system (i.e., more variables than equations).

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Dan H Benjamini