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Statistical simulation of SAR variability with geometric and tissue property changes by using the unscented transform
Author(s) -
Shao Yu,
Zeng Peng,
Wang Shumin
Publication year - 2015
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.25367
Subject(s) - specific absorption rate , monte carlo method , transformation (genetics) , property (philosophy) , unscented transform , computer science , algorithm , sensitivity (control systems) , set (abstract data type) , synthetic aperture radar , mathematics , statistics , artificial intelligence , telecommunications , electronic engineering , antenna (radio) , extended kalman filter , biochemistry , chemistry , philosophy , programming language , epistemology , engineering , gene , moving horizon estimation , kalman filter
Purpose The local specific absorption rate (SAR) is critical to the safety of radio frequency transmit coils. A statistical simulation approach is introduced to address the local SAR variability related to tissue property and geometric variations. Methods The local SAR is modeled as the output of a nonlinear transformation with factors that may affect its value being treated as random input variables. Instead of using the Monte Carlo method with a large number of sample points, the unscented transform is applied with a small set of deterministic sample points. A sensitivity analysis is further performed to determine the significance of each input variable. Electromagnetic simulations are carried out by the finite‐difference time‐domain method implemented on graphic processing unit. Results The local SAR variability of a 7 Tesla square loop coil for spine imaging and a 16‐element brain imaging array as the result of tissue property and geometric changes were examined respectively. SAR limits were determined based on their means and standard deviations. Conclusion The proposed approach is efficient and general for the study of local SAR variability. Magn Reson Med 73:2357–2362, 2015. © 2014 Wiley Periodicals, Inc.