Effect of subject‐specific head morphometry on specific absorption rate estimates in parallel‐transmit MRI at 7 T

Autor: Hongbae Jeong, Jesper Andersson, Aaron Hess, Peter Jezzard
Rok vydání: 2023
Předmět:
Zdroj: Magnetic Resonance in Medicine. 89:2376-2390
ISSN: 1522-2594
0740-3194
Popis: Purpose:To assess the accuracy of morphing an established reference electromagnetic head model to a subject-specific morphometry for the estimation of specific absorption rate (SAR) in 7T parallel-transmit (pTx) MRI. Methods:Synthetic T1-weighted MR images were created from three high-resolution open-source electromagnetic head voxel models. The accuracy of morphing a “reference” (multimodal image-based detailed anatomical [MIDA]) electromagnetic model into a different subject's native space (Duke and Ella) was compared. Both linear and nonlinear registration methods were evaluated. Maximum 10-g averaged SAR was estimated for circularly polarized mode and for 5000 random RF shim sets in an eight-channel transmit head coil, and comparison made between the morphed MIDA electromagnetic models and the native Duke and Ella electromagnetic models, respectively. Results:The averaged error in maximum 10-g averaged SAR estimation across pTx MRI shim sets between the MIDA and the Duke target model was reduced from 17.5% with only rigid-body registration, to 11.8% when affine linear registration was used, and further reduced to 10.7% when nonlinear registration was used. The corresponding figures for the Ella model were 16.7%, 11.2%, and 10.1%. Conclusion:We found that morphometry accounts for up to half of the subject-specific differences in pTx SAR. Both linear and nonlinear morphing of an electromagnetic model into a target subject improved SAR agreement by better matching head size, morphometry, and position. However, differences remained, likely arising from details in tissue composition estimation. Thus, the uncertainty of the head morphometry and tissue composition may need to be considered separately to achieve personalized SAR estimation.
Databáze: OpenAIRE
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