Myocardial Contrast Echocardiography Replenishment Mapping for Perfusion
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Solution Overview
Problem
Myocardial contrast echocardiography (MCE) has limited adoption due to technical demands requiring specialized training and lack of quantification software for clinicians to interpret images effectively.
Innovation Solution
Methods and systems for analyzing and displaying myocardial contrast echocardiography data to visually assess normal and abnormal perfusion by determining blood replenishment time, using color-coding and curve fitting to create intuitive output images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If myocardial contrast echocardiography is performed with manual interpretation, then diagnostic information can be obtained, but the process requires specialized training and is time-consuming
Solution Approach 1:
The system performs automatic quantification and analysis of myocardial contrast echocardiography images, allowing the imaging system itself to process and interpret the data without requiring manual analysis by specialized clinicians. The automated algorithm calculates blood replenishment time and generates diagnostic outputs independently.
Solution Approach 2:
The patent replaces manual mechanical interpretation of ultrasound images with automated computational algorithms. The system automatically processes image data, performs curve fitting analysis, calculates replenishment parameters, and generates diagnostic reports through computer processing rather than human clinician analysis.
2Ease of operation
If quantitative analysis software is implemented, then interpretation is simplified, but device complexity increases
Solution Approach 1:
The patent combines multiple functions into a single integrated software system: image acquisition, curve fitting analysis, parameter calculation, and diagnostic output generation are merged into one unified quantification platform. This integration simplifies the user interface while consolidating the complexity into a single system rather than requiring multiple separate tools.
Solution Approach 2:
The system introduces an automated intermediary software layer between the ultrasound imaging hardware and the clinician. This intermediary automatically processes the raw image data, performs complex calculations, and presents simplified diagnostic results, shielding the user from the underlying computational complexity while maintaining accurate quantitative analysis.
3Productivity
If automated quantification is used, then analysis time is reduced, but measurement precision may be compromised
Solution Approach 1:
The automated quantification system incorporates feedback mechanisms where the algorithm continuously adjusts its analysis based on the quality and characteristics of the input ultrasound images. The system monitors the fit quality of curve models and can adapt its calculations to maintain precision while processing data automatically at high speed.
Solution Approach 2:
The system dynamically adjusts analysis parameters based on the specific characteristics of each patient's ultrasound data. The curve fitting algorithm adapts to individual image quality, tissue characteristics, and acquisition parameters, ensuring that measurement precision is maintained across different patients and imaging conditions while preserving automated high-speed processing.
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
Provides simplified, clinically relevant images that facilitate quick diagnostic interpretation of blood perfusion, aiding clinicians in identifying healthy and unhealthy tissue areas.
Implementation Method 1
The ultrasonic waves are reflected back from tissues and cells within the body, received by an ultrasonic transducer, and processed to produce an image
Implementation Method 2
Because the microbubbles reflect ultrasonic waves more strongly than do soft tissues and fluids of the body, use of contrast agents such as microbubbles enhance the contrast of the ultrasound
Implementation Method 3
The microbubbles in the myocardium are then destroyed with one or more high-energy ultrasound pulses
Data Source
AI summary
Methods for displaying blood replenishment time in a tissue may include determining a respective initial video intensity for each respective pixel of a plurality of pixels of an ultrasound image, determining a respective subsequent video intensity of each respective pixel at a plurality of subsequent timepoints, and using the data to determine a respective steady-state concentration of microbubbles in the blood volume, blood velocity, and time-to-target-replenishment for each respective pixel. The time-to-target-replenishment may be color-coded for each respective pixel using a colormap that assigns a first color to respective times-to-target-replenishment that are below a predetermined threshold time, and a second color to respective times-to-target-replenishment that are above the predetermined threshold time. An output image may then be created that displays the plurality of pixels color-coded according to the time-to-target-replenishment, thereby differentiating between portions of the tissue experiencing respective times-to-target-replenishment that are above and below the predetermined threshold time.