The dependence of ultrasound contrast agents backscatter on acoustic pressure: theory versus experiment

Sboros, Vassilis; MacDonald, C.A.; Pye, S. D.; Moran, Carmel M.; Gomatam, Jagannathan; McDicken, W.N.

doi:10.1016/s0041-624x(02)00175-0

Cited by 38 publications

(23 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If linear proportionality between changes in the MI and changes in TIC amplitude values can be assumed, then simply normalizing the TIC with the applied MI will remove the variations. However, it is well known that bubble behaviour, including both scattering and attenuation, is nonlinear with respect to the ultrasound pressure and hence the MI [25][26][27]. In order to study the changes in the TICs caused by changes in the MI, a detailed examination of the relationship between bubble behaviour and the driving ultrasound pressure is required.…”

Section: Output Power (Mechanical Index)mentioning

confidence: 99%

Quantitative contrast-enhanced ultrasound imaging: a review of sources of variability

Tang

Mulvana

Gauthier³

et al. 2011

Interface Focus.

262

219

View full text Add to dashboard Cite

Ultrasound provides a valuable tool for medical diagnosis offering real-time imaging with excellent spatial resolution and low cost. The advent of microbubble contrast agents has provided the additional ability to obtain essential quantitative information relating to tissue vascularity, tissue perfusion and even endothelial wall function. This technique has shown great promise for diagnosis and monitoring in a wide range of clinical conditions such as cardiovascular diseases and cancer, with considerable potential benefits in terms of patient care. A key challenge of this technique, however, is the existence of significant variations in the imaging results, and the lack of understanding regarding their origin. The aim of this paper is to review the potential sources of variability in the quantification of tissue perfusion based on microbubble contrast-enhanced ultrasound images. These are divided into the following three categories: (i) factors relating to the scanner setting, which include transmission power, transmission focal depth, dynamic range, signal gain and transmission frequency, (ii) factors relating to the patient, which include body physical differences, physiological interaction of body with bubbles, propagation and attenuation through tissue, and tissue motion, and (iii) factors relating to the microbubbles, which include the type of bubbles and their stability, preparation and injection and dosage. It has been shown that the factors in all the three categories can significantly affect the imaging results and contribute to the variations observed. How these factors influence quantitative imaging is explained and possible methods for reducing such variations are discussed.

show abstract

Section: Output Power (Mechanical Index)mentioning

confidence: 99%

Quantitative contrast-enhanced ultrasound imaging: a review of sources of variability

Tang

Mulvana

Gauthier³

et al. 2011

Interface Focus.

262

219

View full text Add to dashboard Cite

show abstract

“…When the applied acoustic pressure is higher than the threshold, the gas escapes from the shell and forms free gas bubbles. These gas bubbles produce distinct echo signals, which can be used to detect the contrast agent (Bouakaz et al 2005;Frinking et al 2001;Sboros et al 2002).…”

Section: Introductionmentioning

confidence: 99%

The Onset of Microbubble Vibration

Emmer

Wamel

Goertz

et al. 2007

Ultrasound in Medicine & Biology

139

111

View full text Add to dashboard Cite

“…The strength and duration of microbubble volumetric oscillations is likely to depend upon properties of the transmit pulse, such as the number of cycles, transmit pressure and frequency, as well as properties of individual bubbles including the bubble's size [30], [31], [32], its location in the field of view [33], its proximity to neighboring objects or bubbles [34], [35], and its shell composition [36], [37]. However, while the spatially variant changes in PSF can be predicted and addressed, the unpredictable, stochastic behaviour of a polydispersed population of bubbles, each with a unique shell composition, makes it challenging to predict both their linear and non-linear signal response.…”

mentioning

confidence: 99%

Microbubble Axial Localization Errors in Ultrasound Super-Resolution Imaging

Christensen-Jeffries

Harput

Brown

et al. 2017

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

View full text Add to dashboard Cite

Abstract-Acoustic super-resolution imaging has allowed visualization of microvascular structure and flow beyond the diffraction limit using standard clinical ultrasound systems through the localization of many spatially isolated microbubble signals. The determination of each microbubble position is typically performed by calculating the centroid, finding a local maximum, or finding the peak of a 2-D Gaussian function fit to the signal. However, the backscattered signal from a microbubble depends not only on diffraction characteristics of the waveform, but also on the microbubble behavior in the acoustic field. Here, we propose a new axial localization method by identifying the onset of the backscattered signal. We compare the accuracy of localization methods using in vitro experiments performed at 7 cm depth and 2.3 MHz center frequency. We corroborate these findings with simulated results based on the Marmottant model. We show experimentally and in simulations that detecting the onset of the returning signal provides considerably increased accuracy for super-resolution. Resulting experimental crosssectional profiles in super-resolution images demonstrate at least 5.8 times improvement in contrast ratio and more than 1.8 reduction in spatial spread (provided by 90% of the localizations) for the onset method over centroiding, peak detection and 2D Gaussian fitting methods. Simulations estimate that these latter methods could create errors in relative bubble positions as high as 900 µm at these experimental settings, while the onset method reduced the interquartile range of these errors by a factor of over 2.2. Detecting the signal onset is therefore expected to considerably improve the accuracy of super-resolution.

show abstract

The dependence of ultrasound contrast agents backscatter on acoustic pressure: theory versus experiment

Cited by 38 publications

References 8 publications

Quantitative contrast-enhanced ultrasound imaging: a review of sources of variability

Quantitative contrast-enhanced ultrasound imaging: a review of sources of variability

The Onset of Microbubble Vibration

Microbubble Axial Localization Errors in Ultrasound Super-Resolution Imaging

Contact Info

Product

Resources

About