Spatial Coherence-Based Adaptive Acoustic Output Selection for Diagnostic Ultrasound

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2022

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Abstract

The US Food and Drug Administration (FDA) provides guidelines for maximum acoustic output for diagnostic ultrasound imaging through metrics such as intensity, Mechanical Index (MI), and Thermal Index (TI). However, even within these guideline values, if the acoustic exposure levels used do not benefit image quality, they represent an unnecessary risk to patient safety. Ultrasound users have control over many settings, including ones that directly and indirectly change the acoustic output, and the user is largely responsible for deciding how to manage the safety risks based on on-screen displays of MI and TI. The FDA and professional societies advise users to observe the ALARA (as low as reasonably achievable) principle with regard to acoustic exposure, but several studies have shown that the majority of ultrasound users do not monitor safety indices. To address this discrepancy, an adaptive ultrasound method has been developed that could be used to automatically adjust acoustic exposure in real-time in response to image quality feedback.

In this work, MI was used as the measure of acoustic output, and lag-one coherence (LOC) was the image quality feedback parameter. LOC is the average spatial correlation between backscattered echoes received on neighboring ultrasound transducer array elements. Previous work has shown that LOC is predictive of local signal-to-noise ratio (SNR), and that it is sensitive to incoherent acoustic clutter and temporally-incoherent noise. During B-mode ultrasound imaging, LOC was monitored as MI was adjusted, and the data consistently formed a sigmoid shape. At lower MI values, LOC increased quickly with increasing output, but at higher MI values, increases in acoustic output often did not translate to increased image quality. This relationship was consistent for other image quality metric-versus-MI data, including contrast, contrast-to-noise ratio (CNR), and generalized contrast-to-noise ratio (gCNR).

The MI value at which the LOC began to approach an asymptote was denoted the "ALARA MI.” In this work, ALARA MI values were calculated for a range of obstetric imaging targets that are scanned during anatomy exams, including placenta, fetal abdomen, heart, kidney, bladder, stomach, ventricles, and extremities. The placenta data had the lowest median ALARA MI (0.59) and the fetal heart data had the highest (0.83). There was considerable variation in the ALARA MI values, even for the same participant, so frequent updates to the acoustic output settings would be recommended during live scanning. Additionally, the correlation between the ALARA MI and the LOC achieved at that setting was found to be very weak.

Initially, a fixed region of interest (ROI) was used for acoustic output optimization. This would require the structure to be aligned with the ROI and the optimization process to be manually initiated. Considering the demands on the sonographer during clinical ultrasound scanning, it would not be feasible to add these steps every time a new imaging window is used. An automated ROI-selection algorithm was developed that would allow the entire adaptive acoustic output selection process to happen without user input. This algorithm used envelope-detected B-mode image data that are readily available on clinical scanners to identify where to perform the optimization. Testing on clinical placenta and fetal abdomen data showed that it reliably recommended good regions for acoustic output optimization.

The results of this work suggest that near-maximum image quality can be achieved with a lower acoustic output level than is currently used clinically, and automated acoustic output adjustments could enable more consistent observation of the ALARA principle. In the future, this could be extended to other ultrasound modes, such as Doppler imaging, and additional acoustic output metrics could be incorporated.

Preliminary assessment of temporal SNR was performed, and a wide range of temporal SNR levels is associated with the ALARA MI settings found in this study. Future work may also investigate using a temporal SNR threshold to determine the ALARA output level. Spatial coherence measurements, such as LOC, reflect the degradation in image quality from acoustic clutter and electronic noise, and temporal coherence is affected by motion and electronic noise. Although motion is an important factor in clinical imaging, temporal coherence does not require access to channel data, so these calculations would be easier to implement on existing scanners. These trade-offs are important to consider when attempting to capture the underlying electronic noise level to inform an automated ALARA ultrasound system.

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Flint, Katelyn Maureen (2022). Spatial Coherence-Based Adaptive Acoustic Output Selection for Diagnostic Ultrasound. Dissertation, Duke University. Retrieved from https://hdl.handle.net/10161/25254.

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