Ultrasound Shear Wave Velocity Estimation via Acceleration Integration
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Solution Overview
Problem
Current methods for quantifying tissue stiffness, such as biopsies and ARFI imaging, are invasive, limited in sampling, and computationally intensive, making them inefficient for frequent monitoring of liver fibrosis and other diseases.
Innovation Solution
Detecting shear waves generated by an applied shear wave source and determining the time of peak displacement at multiple sample positions to calculate mechanical parameters like shear elasticity modulus, allowing for non-invasive and efficient assessment of tissue stiffness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Helmholtz analysis based techniques are used to estimate shear wave velocity, then tissue stiffness can be characterized, but second order displacement derivatives must be taken in both space and time which amplifies noise and makes accurate estimates difficult
Solution Approach 1:
The patent inverts the traditional approach by not directly differentiating displacement data to get velocity, but rather integrating acceleration data (from piezoelectric sensors) to obtain velocity and position. This inversion avoids the noise amplification problem of differentiation while achieving the same measurement goal.
Solution Approach 2:
The patent replaces the mathematical differentiation operation (which amplifies noise) with direct mechanical measurement using piezoelectric sensors that naturally output acceleration data. This substitution of measurement methodology eliminates the need for numerical differentiation and its associated noise problems.
2Reliability
If significant filtering operations are performed on displacement data to reduce jitter, then noise can be reduced, but computational intensity increases and real-time processing becomes difficult
Solution Approach 1:
The patent performs preliminary action by capturing high-quality acceleration data directly from piezoelectric sensors at the source, rather than starting with noisy displacement data that requires filtering. The integration of acceleration to velocity and position is a straightforward mathematical operation that does not require iterative filtering, thus maintaining both signal quality and processing speed.
3Measurement precision
If biopsy is used to characterize liver fibrosis, then direct tissue sampling is obtained, but the procedure is invasive, samples only a small volume, and carries risks of bleeding and organ puncture
Solution Approach 1:
The patent replaces the mechanical biopsy procedure (physical needle insertion and tissue extraction) with a non-invasive acoustic radiation force impulse (ARFI) imaging technique that uses ultrasound waves to generate and detect shear waves in the liver tissue, thereby characterizing tissue stiffness without physical intrusion.
Solution Approach 2:
The patent introduces shear waves as an intermediary mechanism to indirectly measure tissue stiffness. Instead of directly extracting and analyzing tissue samples, the system generates shear waves that propagate through the liver and measures their velocity, which correlates with tissue stiffness, thus avoiding direct tissue contact and associated risks.
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
This approach provides a non-invasive, efficient method for quantifying tissue stiffness with improved signal-to-noise ratio and reduced computational complexity, enabling more frequent and accurate monitoring of liver fibrosis and other diseases.
Implementation Method 1
transmitting ultrasound energy into the sample in a first direction to provide a shear wave source that generates an extended shear wave
Implementation Method 2
detecting shear waves that have been generated in the sample by the shear wave source
Data Source
AI summary
Methods for determining a mechanical parameter of a sample include detecting shear waves that have been generated in the sample by an applied shear wave source. A time of peak displacement of the shear waves for a plurality of sample positions is determined. At least one mechanical parameter of the sample based on the time of peak displacement for the plurality of sample positions is determined.