ARFI Displacement Imaging Using Adaptive Time Instance Selection
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Solution Overview
Problem
Acoustic radiation force impulse (ARFI) imaging is biased by maximum tissue displacement, leading to errors in tissue elastic property determination due to accumulation of displacements over time, which affects diagnostic accuracy.
Innovation Solution
A cost function is used to identify the optimal time for tissue displacement measurement, considering contrast and signal-to-noise ratio, to generate an ARFI image that is less reliant on maximum displacement, thereby providing more accurate tissue elasticity information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If maximum displacement is used to generate ARFI images, then the imaging process is simple, but measurement precision deteriorates due to bias from displacement accumulation
Solution Approach 1:
The patent applies dynamics by transitioning from a static maximum displacement measurement to a dynamic time-dependent displacement measurement. The system measures displacement at multiple time points after ARFI application and selects the optimal time point based on cost function evaluation, allowing the measurement to adapt to the transient response characteristics of the tissue rather than relying on a fixed maximum value.
Solution Approach 2:
The patent changes the measurement parameter from maximum displacement magnitude to displacement at a specifically selected time point. The cost function evaluates multiple parameters including contrast, signal-to-noise ratio, and temporal characteristics to identify the optimal time point, thereby changing the measurement approach to eliminate bias from displacement accumulation while maintaining imaging simplicity.
2Duration of action of moving object
If displacement accumulation over time is allowed, then the transient response is captured completely, but measurement precision deteriorates due to biased maximum displacement values
Solution Approach 1:
The patent applies preliminary action by measuring displacement at multiple time points during the transient response and evaluating them using a cost function before finalizing the measurement. This preliminary evaluation allows the system to identify the optimal time point that avoids the bias of maximum displacement while capturing the essential tissue elastic properties, effectively preparing the measurement in advance to ensure accuracy.
Solution Approach 2:
The patent implements feedback through the cost function evaluation process, where the measured displacement data at different time points is systematically evaluated and compared. The feedback mechanism selects the optimal time point based on multiple criteria including contrast and signal-to-noise ratio, allowing the system to learn from the transient response characteristics and make an informed selection that eliminates measurement bias.
3Measurement precision
If time-dependent displacement measurement is implemented, then measurement precision improves, but device complexity increases due to multiple time point measurements
Solution Approach 1:
The patent applies universality by using a single cost function framework that can evaluate multiple time points and select the optimal one for various tissue types and imaging conditions. The cost function integrates multiple criteria (contrast, signal-to-noise ratio, temporal characteristics) into a unified evaluation mechanism, allowing the same system to handle different scenarios without requiring separate complex processing paths for each case.
Solution Approach 2:
The patent implements self-service through the automated cost function evaluation process, where the system independently analyzes the displacement data at different time points and selects the optimal measurement time without requiring external intervention. The cost function automatically balances the trade-off between capturing transient response characteristics and avoiding measurement bias, reducing the need for manual configuration or complex user input.
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 allows for the generation of ARFI images that better represent tissue elasticity, reducing diagnostic errors by selecting the appropriate time instance for displacement measurement, which enhances image quality and border definition.
Implementation Method 1
acoustic radiation force impulse (ARFI) imaging... a shear, longitudinal or other wave is generated with an ARFI transmitted as a push pulse. Ultrasound energy is transmitted to a focal region to generate the wave, resulting in displacement of tissue around the focal region
Implementation Method 2
Further ultrasound scanning tracks the displacement of tissue over time at locations around the focal region. For each location, the peak or maximum displacement is determined
Data Source
AI summary
In ARFI imaging, a cost function is used to identify a time of displacement that best or sufficiently indicates the desired information. For example, the displacements associated with a combination of contrast and signal-to-noise ratio are identified. The time at which the desired displacements occur may be other than the time of the maximum. Since the time is common to displacements for one or more scan lines, the displacement image may be assembled line-by-line or by groups of lines.