From Complex B1 Mapping to Local SAR Estimation for Human Brain MR Imaging Using Multi-Channel Transceiver Coil at 7T

Xiaotong Zhang, Sebastian Schmitter, Pierre Francois Van De Moortele, Jiaen Liu, Bin He

Research output: Contribution to journalArticlepeer-review

53 Scopus citations


Elevated specific absorption rate (SAR) associated with increased main magnetic field strength remains a major safety concern in ultra-high-field (UHF) magnetic resonance imaging (MRI) applications. The calculation of local SAR requires the knowledge of the electric field induced by radio-frequency (RF) excitation, and the local electrical properties of tissues. Since electric field distribution cannot be directly mapped in conventional MR measurements, SAR estimation is usually performed using numerical model-based electromagnetic simulations which, however, are highly time consuming and cannot account for the specific anatomy and tissue properties of the subject undergoing a scan. In the present study, starting from the measurable RF magnetic fields B1 in MRI, we conducted a series of mathematical deduction to estimate the local, voxel-wise and subject-specific SAR for each single coil element using a multi-channel transceiver array coil. We first evaluated the feasibility of this approach in numerical simulations including two different human head models. We further conducted experimental study in a physical phantom and in two human subjects at 7T using a multi-channel transceiver head coil. Accuracy of the results is discussed in the context of predicting local SAR in the human brain at UHF MRI using multi-channel RF transmission.

Original languageEnglish (US)
Article number6477144
Pages (from-to)1058-1067
Number of pages10
JournalIEEE Transactions on Medical Imaging
Issue number6
StatePublished - 2013
Externally publishedYes


  • B-mapping
  • Electrical properties tomography (EPT)
  • magnetic resonance imaging (MRI)
  • parallel transmission
  • specific absorption rate (SAR)
  • ultra-high-field (UHF)

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering


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