Discovery (Lead Identification)
Measuring and mapping nervous tissue microstructure noninvasively is a long sought-after goal in neuroscience. Several neuropathologies – such as cancer and stroke – are associated with changes in tissue microstructure. Changes in material properties, such as stiffness, represent a sensitive measure of
underlying changes in tissue architecture, organization, and microstructure. Elastography techniques used to map material stiffness typically involves measuring displacement resulting from shear waves of known frequency imposed on the material by an external actuator or tamper. Material stiffness is estimated from measured displacement by inverting a model relating the material’s strain to its stress. A minimal description of a constitutive law relating the stress and strain in the anisotropic material requires a rank-4 anisotropic elasticity tensor (E-tensor). The E-tensor has a number of free parameters ranging from 2 to 21 depending on the degree of material symmetry – instead of the 1-parameter isotropic scalar shear modulus used in conventional methods. Reconstructing the full E-tensor from a single mechanical excitation is an ill-posed inverse problem since the number of unknowns typically exceeds the number of available equations.
The disclosure describes elastography methods permitting measurement of small physiological tissue displacements using spin echo MRI, ultrasound, or other techniques. It allows reconstruction of a full rank-4 anisotropic elasticity tensor (E-tensor). It includes strategies that denoise the measured displacement field using physically motivated compatibility conditions. Also, it includes a family of new intrinsic, invariant stains or parameters to characterize different features of the measured E-tensor. The disclosed E-tensor estimation pipelines are evaluated using simulated 3D displacement data in the presence of noise which confirm the applicability of the disclosed approaches. With the selected E-tensor and associated stains, physiological disorders – such as Alzheimer’s disease and traumatic brain injury (TBI) – is more readily detected versus conventional methods not utilizing the full E-tensor.
The Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) seeks research co-development partners and/or licensees for the development of tamper-less tensor elastography imaging in assessing disease (e.g., cancer), normal and abnormal developmental processes, degeneration and trauma in the brain and other soft tissues, and other applications.