Document Detail


Optimization of encoding gradients for MR-ARFI.
MedLine Citation:
PMID:  20373406     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
MR acoustic radiation force imaging provides a promising method to monitor therapeutic ultrasound treatments. By measuring the displacement induced by the acoustic radiation force, MR acoustic radiation force imaging can locate the focal spot, without a significant temperature rise. In this work, the encoding gradient for MR acoustic radiation force imaging is optimized to achieve an enhanced accuracy and precision of the displacement measurement. By analyzing the sources of artifacts, bulk motion and eddy currents are shown to introduce errors to the measurement, and heavy diffusion-weighting is shown to result in noisy displacement maps. To eliminate these problems, a new encoding scheme is proposed, which utilizes a pair of bipolar gradients. Improved precision is achieved with robustness against bulk motion and background phase distortion, and improved accuracy is achieved with reduced diffusion-weighting and optimized encoding pulse width. The experiment result shows that the signal-to-noise ratio can be enhanced by more than 2-fold. These significant improvements are obtained at no cost of scan time or encoding sensitivity, enabling the detection of a displacement less than 0.l microm in a gel phantom with MR acoustic radiation force imaging.
Authors:
Jing Chen; Ron Watkins; Kim Butts Pauly
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural    
Journal Detail:
Title:  Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine     Volume:  63     ISSN:  1522-2594     ISO Abbreviation:  Magn Reson Med     Publication Date:  2010 Apr 
Date Detail:
Created Date:  2010-04-07     Completed Date:  2010-07-15     Revised Date:  2011-09-26    
Medline Journal Info:
Nlm Unique ID:  8505245     Medline TA:  Magn Reson Med     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1050-8     Citation Subset:  IM    
Affiliation:
State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.
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MeSH Terms
Descriptor/Qualifier:
Acoustics*
Algorithms
Artifacts
Diffusion Magnetic Resonance Imaging / methods*
Elasticity Imaging Techniques / methods*
Linear Models
Phantoms, Imaging
Ultrasonic Therapy / methods*
Grant Support
ID/Acronym/Agency:
P41 RR009784/RR/NCRR NIH HHS; R01 CA111981/CA/NCI NIH HHS; R01 CA121163/CA/NCI NIH HHS; R01 CA121163-04/CA/NCI NIH HHS
Comments/Corrections

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