Improving SAR estimations in MRI using subject-specific models

Jin, Jin, Liu, Feng, Weber, Ewald and Crozier, Stuart (2012) Improving SAR estimations in MRI using subject-specific models. Physics in Medicine and Biology, 57 24: 8153-8171. doi:10.1088/0031-9155/57/24/8153

Author Jin, Jin
Liu, Feng
Weber, Ewald
Crozier, Stuart
Title Improving SAR estimations in MRI using subject-specific models
Journal name Physics in Medicine and Biology   Check publisher's open access policy
ISSN 0031-9155
Publication date 2012-12-21
Sub-type Article (original research)
DOI 10.1088/0031-9155/57/24/8153
Volume 57
Issue 24
Start page 8153
End page 8171
Total pages 19
Place of publication Temple Back, Bristol, United Kingdom
Publisher Institute of Physics Publishing
Collection year 2013
Language eng
Abstract To monitor and strategically control energy deposition in magnetic resonance imaging (MRI), measured as a specific absorption rate (SAR), numerical methods using generic human models have been employed to estimate worst-case values. Radiofrequency (RF) sequences are therefore often designed conservatively with large safety margins, potentially hindering the full potential of high-field systems. To more accurately predict the patient SAR values, we propose the use of image registration techniques, in conjunction with high-resolution image and tissue libraries, to create patient-specific voxel models. To test this, a matching model from the archives was first selected. Its tissue information was then warped to the patient's coordinates by registering the high-resolution library image to the pilot scan of the patient. Results from studying the models' 1 g SAR distribution suggest that the developed patient model can predict regions of elevated SAR within the patient with remarkable accuracy. Additionally, this work also proposes a voxel analytical metric that can assist in the construction of a patient library and the selection of the matching model from the library for a patient. It is hoped that, by developing voxel models with high accuracy in patient-specific anatomy and positioning, the proposed method can accurately predict the safety margins for high-field human applications and, therefore maximize the safe use of RF sequence power in high-field MRI systems.
Keyword Parallel transmission
7 T
Image registration
Field strength
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2013 Collection
School of Information Technology and Electrical Engineering Publications
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