Doppler Ultrasound Bandwidth Imaging for Flow Instability Detection
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Solution Overview
Problem
Current methods for noninvasively detecting flow instability in blood vessels, such as Doppler ultrasound, face challenges in tracking fluctuations in flow velocities over multiple spatial positions and are prone to inaccuracies due to limitations in time resolution and data acquisition paradigms, making it difficult to accurately identify unstable flow regions.
Innovation Solution
The method involves insonating an area of interest with high-frame-rate ultrasound waves, acquiring and processing radio frequency data to derive Doppler bandwidth using autoregressive (AR) modeling, and generating Doppler ultrasound bandwidth imaging (DUBI) frames to visualize flow instability, which provides a more accurate and consistent estimation of flow instability by reducing random spectral spikes and improving spectral resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional Doppler ultrasound methods are used to detect flow instability, then the detection can be performed noninvasively, but the time resolution is insufficient and random spectral spikes reduce measurement precision
Solution Approach 1:
The patent applies periodic action by using high-frame-rate ultrasound imaging to capture flow velocity fluctuations at multiple time points throughout the cardiac cycle. This allows systematic sampling of flow instability characteristics across different phases, improving both reliability and measurement precision compared to conventional single-time-point Doppler methods.
Solution Approach 2:
The patent extracts only the necessary flow velocity information at specific time points during the cardiac cycle, rather than continuously processing all Doppler data. By selecting representative time points and using autoregressive modeling on these extracted samples, the method reduces computational complexity and random spectral spikes while maintaining measurement precision.
2Measurement precision
If high-frame-rate ultrasound imaging is used to capture flow fluctuations, then spectral resolution improves, but data processing complexity increases
Solution Approach 1:
The patent extracts a limited number of representative flow velocity samples at specific time points during the cardiac cycle, rather than processing the entire high-frame-rate dataset. This extraction approach maintains spectral resolution while significantly reducing data processing complexity.
Solution Approach 2:
The patent changes the processing approach from direct spectral analysis of raw high-frame-rate data to autoregressive modeling on selected time-point samples. This parameter change in the processing methodology improves spectral resolution while managing computational complexity through efficient mathematical modeling.
3Measurement precision
If autoregressive modeling is applied to process ultrasound data, then random spectral spikes are reduced and spectral resolution improves, but computational requirements increase
Solution Approach 1:
The patent extracts a limited set of representative flow velocity samples at key time points during the cardiac cycle for autoregressive modeling. This selective extraction reduces the computational burden while maintaining spectral estimation accuracy, as the model captures flow instability characteristics from these critical samples rather than processing all available data.
Solution Approach 2:
The patent applies autoregressive modeling to a subset of the available ultrasound data (specific time points) rather than the complete dataset. This partial application of the computationally intensive technique provides sufficient spectral resolution improvement while keeping computational power requirements manageable.
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 effectively detects flow instability by providing a triplex display scheme that synchronizes Doppler bandwidth maps with flow speckle patterns and anatomical structures, offering improved sensitivity and specificity in identifying unstable flow regions, even in conditions with rapid flow changes, thus enhancing the diagnosis of atherosclerotic plaque development and risk assessment.
Implementation Method 1
acquiring radio frequency data from echo pulses of the ultrasound wave pulses
Implementation Method 2
insonating an area of interest with ultrasound wave pulses
Data Source
AI summary
A method of detecting flow instability includes insonating an area of interest with ultrasound wave pulses, acquiring radio frequency (RF) data from echo pulses of the ultrasound wave pulses, processing the RF data, and deriving a Doppler band-width from the processed RF data by AR modeling. Also described herein is a device for detecting flow instability. The device includes an emitter configured to insonate ultrasound wave pulses on an area of interest, a receiver configured to acquiring radio frequency (RF) data from echo pulses of the ultrasound wave pulses, and a processor configured to process the RF data, and derive a Doppler band-width from the processed RF data by AR modeling.