Document Detail


In vivo MR-tracking based on magnetic signature selective excitation.
MedLine Citation:
PMID:  18270059     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
A novel magnetic resonance (MR)-tracking method specifically developed to locate the ferromagnetic core of an untethered microdevice, microrobot, or nanorobot for navigation or closed-loop control purpose is described. The tracking method relies on the application of radio-frequency (RF) excitation signals tuned to the equipotential magnetic curves generated by the magnetic signature of the object being tracked. Positive contrast projections are obtained with reference to the position of the magnetic source. A correlation function performed on only one k-space line for each of the three axes and corresponding to three projections, is necessary to obtain a 3-D location of the device. In this study, the effects of the sphere size and the RF frequency offset were investigated in order to find the best contrast noise ratio (CNR) for tracking. Resolution and precision were also investigated by proper measurement of the position of a ferromagnetic sphere by magnetic resonance imaging (MRI) acquisition and by comparing them with the real position. This method is also tested for a moving marker where the positions found by MRI projections were compared with the ones taken with a camera. In vitro and in vivo experiments show the operation of the technique in tortuous phantom and in animal models. Although the method was developed in the prospect of new interventional MR-guided endovascular operations based on miniature untethered devices, it could also be used as a passive tracking method using tools such as catheters or guide wires.
Authors:
O Felfoul; J B Mathieu; G Beaudoin; S Martel
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Publication Detail:
Type:  Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  IEEE transactions on medical imaging     Volume:  27     ISSN:  0278-0062     ISO Abbreviation:  IEEE Trans Med Imaging     Publication Date:  2008 Jan 
Date Detail:
Created Date:  2008-02-13     Completed Date:  2008-03-11     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8310780     Medline TA:  IEEE Trans Med Imaging     Country:  United States    
Other Details:
Languages:  eng     Pagination:  28-35     Citation Subset:  IM    
Affiliation:
Department of Computer Engineering, Ecole Polytechnique de Montreal, Montreal, Canada.
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Artificial Intelligence
Catheterization / methods*
Humans
Image Enhancement / methods
Image Interpretation, Computer-Assisted / methods*
Imaging, Three-Dimensional / methods*
Magnetic Resonance Imaging / instrumentation,  methods*
Pattern Recognition, Automated / methods*
Phantoms, Imaging
Reproducibility of Results
Sensitivity and Specificity
Surgery, Computer-Assisted / methods*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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