Ultrasound Triggering for Image Quality and Energy Reduction
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Solution Overview
Problem
Sonographers face challenges in selecting optimal positions and times for ultrasound transducer placement to minimize patient acoustic energy exposure and improve image quality, often leading to increased exposure and discomfort due to the need to operate control panels while positioning the transducer.
Innovation Solution
The method involves acquiring a first type of ultrasound data, analyzing it to identify optimal acquisition times and positions for improved image quality metrics, and triggering a second type of ultrasound data acquisition at the identified parameters using a signal generated by the processor and ultrasound transducer array.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sonographers manually select acquisition time and position for ultrasound scans, then they can adjust imaging parameters, but patient acoustic energy exposure increases and image quality decreases
Solution Approach 1:
The system performs self-service by automatically analyzing B-mode ultrasound data to identify optimal acquisition times and positions for ARFI/SWEI imaging. The processor autonomously determines when tissue coherence is highest and triggers the high-energy acquisition without requiring manual intervention from the sonographer, thereby minimizing patient exposure while maximizing image quality.
Solution Approach 2:
The system uses feedback from real-time B-mode ultrasound data analysis to dynamically trigger high-energy acquisitions. By continuously monitoring tissue coherence metrics and comparing them against threshold values, the system provides feedback-based control that activates ARFI/SWEI imaging only when optimal conditions are detected, thus reducing unnecessary acoustic energy exposure.
2Ease of operation
If sonographers operate control panels while positioning transducer, then they can adjust imaging parameters, but operator discomfort and pain increase
Solution Approach 1:
The system performs self-service by automatically analyzing B-mode ultrasound data to identify optimal acquisition times and positions for ARFI/SWEI imaging. The processor autonomously determines when tissue coherence is highest and triggers the high-energy acquisition without requiring manual intervention from the sonographer, thereby minimizing patient exposure while maximizing image quality.
Solution Approach 2:
The system introduces an intermediary automated triggering mechanism that mediates between the B-mode imaging data and the high-energy ARFI/SWEI acquisition. This intermediary processor analyzes coherence metrics and automatically initiates acquisitions, eliminating the need for sonographers to manually coordinate control panel operations with transducer positioning.
3Measurement precision
If higher energy ultrasound pulses are used for ARFI and SWEI imaging, then tissue stiffness characterization improves, but patient acoustic energy exposure increases
Solution Approach 1:
The system implements periodic action by using low-energy B-mode ultrasound pulses to continuously monitor tissue coherence and periodically triggering high-energy ARFI/SWEI pulses only when optimal conditions are detected. This periodic alternation between low-energy monitoring and high-energy characterization allows for improved tissue stiffness measurement while minimizing overall acoustic energy exposure to the patient.
Solution Approach 2:
The system performs preliminary action by acquiring and analyzing B-mode ultrasound data before initiating high-energy ARFI/SWEI acquisitions. This preliminary assessment of tissue coherence allows the system to predict optimal acquisition moments, ensuring that high-energy pulses are delivered only when they will yield the best tissue stiffness characterization, thereby reducing unnecessary energy exposure.
Data Source
AI summary
Methods of triggering an imaging acquisition of a target region in an ultrasound transducer include: acquiring a first type of ultrasound data with the ultrasound transducer using a first type of ultrasound acquisition; analyzing the first type of ultrasound data to identify an acquisition time and/or position having characteristics that increase an estimated amount of image quality metrics in the target region for a second type of ultrasound acquisition; and generating a signal to initiate acquiring a second type of ultrasound data by the ultrasound transducer at the identified acquisition time and/or position using a second type of ultrasound acquisition in response to the identified acquisition time and/or position identified from the first type of ultrasound data.