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The ultimate signal‐to‐noise ratio in realistic body models
Author(s) -
Guérin Bastien,
Villena Jorge F.,
Polimeridis Athanasios G.,
Adalsteinsson Elfar,
Daniel Luca,
White Jacob K.,
Wald Lawrence L.
Publication year - 2017
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.26564
Subject(s) - solver , physics , head (geology) , human head , computation , noise (video) , signal to noise ratio (imaging) , computer science , mathematical analysis , acoustics , mathematics , geology , algorithm , mathematical optimization , optics , artificial intelligence , geomorphology , absorption (acoustics) , image (mathematics)
Purpose We compute the ultimate signal‐to‐noise ratio (uSNR) and G‐factor (uGF) in a realistic head model from 0.5 to 21 Tesla. Methods We excite the head model and a uniform sphere with a large number of electric and magnetic dipoles placed at 3 cm from the object. The resulting electromagnetic fields are computed using an ultrafast volume integral solver, which are used as basis functions for the uSNR and uGF computations. Results Our generalized uSNR calculation shows good convergence in the sphere and the head and is in close agreement with the dyadic Green's function approach in the uniform sphere. In both models, the uSNR versus B 0 trend was linear at shallow depths and supralinear at deeper locations. At equivalent positions, the rate of increase of the uSNR with B 0 was greater in the sphere than in the head model. The uGFs were lower in the realistic head than in the sphere for acceleration in the anterior‐posterior direction, but similar for the left‐right direction. Conclusion The uSNR and uGFs are computable in nonuniform body models and provide fundamental performance limits for human imaging with close‐fitting MRI array coils. Magn Reson Med 78:1969–1980, 2017. © 2016 International Society for Magnetic Resonance in Medicine.