Shear Wave Imaging Tissue Viscosity Estimation
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Solution Overview
Problem
Accurate quantitative estimation of tissue elasticity and viscosity from shear-wave imaging in biological tissues is challenging due to the influence of viscosity on shear wave speed, which is not accounted for in existing methods that rely on relationships derived for homogenous isotropic solids.
Innovation Solution
A method that couples a direct model of shear-wave propagation in soft media with an optimizer algorithm to estimate patient-specific shear modulus and viscosity values from shear-wave images, using a computational model to simulate shear-wave propagation and minimize a cost function to match observed propagation, enabling spatial mapping of these properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing methods use relationships derived for homogenous isotropic solids to estimate tissue elasticity, then the estimation process is simple, but the accuracy deteriorates because viscosity effects are not accounted for
Solution Approach 1:
The patent transitions from using simple solid mechanics relationships to a viscoelastic model that incorporates both shear modulus and viscosity parameters. This parameter change allows accurate modeling of biological tissue behavior while maintaining computational feasibility through optimized estimation algorithms
Solution Approach 2:
The patent replaces the simple isotropic solid mechanical model with a viscoelastic mechanical model that better represents biological tissue. This substitution introduces viscosity effects into the shear wave propagation model, improving accuracy while using computational methods to manage the increased complexity
2Measurement precision
If a direct model of shear-wave propagation is coupled with an optimizer algorithm to estimate both shear modulus and viscosity, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent implements a feedback loop where the forward model predicts shear wave propagation based on estimated parameters, these predictions are compared with actual measurements, and the optimizer adjusts the parameters to minimize the difference. This feedback mechanism enables accurate estimation of both shear modulus and viscosity despite the increased computational complexity
Solution Approach 2:
The patent creates a computational copy of the shear wave propagation process through the forward model. This virtual model replicates the physical phenomenon, allowing the system to simulate and analyze wave propagation behavior without requiring complex physical measurement apparatus
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate, patient-specific estimation and spatial mapping of shear modulus and viscosity, improving diagnostic capabilities by providing quantitative assessment of tissue mechanics and constitution.
Implementation Method 1
Radiation force from an acoustic radiation force impulse (ARFI) generates the shear waves in the tissue
Implementation Method 2
The velocity of the shear wave propagation in the tissue is measured and a time sequence of images showing the displacement of the shear wave is captured
Data Source
AI summary
A method and system for automatic non-invasive estimation of shear modulus and viscosity of biological tissue from shear-wave imaging is disclosed. Shear-wave images are acquired to evaluate the mechanical properties of an organ of a patient. Shear-wave propagation in the tissue in the shear-wave images is simulated based on shear modulus and viscosity values for the tissue using a computational model of shear-wave propagation. The simulated shear-wave propagation is compared to observed shear-wave propagation in the shear-wave images of the tissue using a cost function. Patient-specific shear modulus and viscosity values for the tissue are estimated to optimize the cost function comparing the simulated shear-wave propagation to the observed shear-wave propagation.