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An Adaptive Spectral Estimation Technique to Detect Cavitation in HIFU With High Spatial Resolution.
MedLine Citation:
PMID:  21684454     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
In ultrasound-guided high-intensity focused ultrasound (HIFU) therapy, the changes observed on tissue are subtle during treatment; some ultrasound-guided HIFU protocols rely on the observation of significant brightness changes as the indicator of tissue lesions. The occurrence of a distinct hyperechogenic region ("bright-up") around the focus is often associated with acoustic cavitation resulting in microbubble formation, but it may indicate different physical events such as larger bubbles from boiling (known to alter acoustic impedance) or sometimes lesion formation. A reliable method to distinguish and spatially localize these causes within the tissue would assist the control of HIFU delivery, which is the subject of this paper. Spectral analysis of the radio frequency (RF) signal underlying the B-mode image provides more information on the physical cause, but the usual techniques that are methods on the Fourier transform require a long series for good spectral resolution and so they give poor spatial resolution. This paper introduces an active spectral cavitation detection method to attain high spatial resolution (0.15 × 0.15 mm per pixel) through a parametric statistical method (ARMA modeling) used on finite-length data sets, which enables local changes to be identified more easily. This technique uses the characteristics of the signal itself to optimize the model parameters and structure. Its performance is assessed using synthesized cavitation RF data, and it is then demonstrated in ex vivo bovine liver during and after HIFU exposure. The results suggest that good spatial and spectral resolution can be obtained by the design of suitable algorithms. In ultrasound-guided HIFU, the technique provides a useful supplement to B-mode analysis, with no additional time penalty in data acquisition.
Authors:
Chang-Yu Hsieh; Penny Probert Smith; Fares Mayia; Guoliang Ye
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Ultrasound in medicine & biology     Volume:  37     ISSN:  1879-291X     ISO Abbreviation:  Ultrasound Med Biol     Publication Date:  2011 Jul 
Date Detail:
Created Date:  2011-06-20     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0410553     Medline TA:  Ultrasound Med Biol     Country:  England    
Other Details:
Languages:  eng     Pagination:  1134-50     Citation Subset:  IM    
Copyright Information:
Copyright © 2011 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.
Affiliation:
Institute of Biomedical Engineering, Department of Engineering, University of Oxford, UK.
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