Performance evaluation of a 32-element head array with respect to the ultimate intrinsic SNR

Riccardo Lattanzi, Aaron K. Grant, Jonathan R. Polimeni, Michael A. Ohliger, Graham C. Wiggins, Lawrence L. Wald, Daniel K. Sodickson

Research output: Contribution to journalArticlepeer-review


The quality of an RF detector coil design is commonly judged on how it compares with other coil configurations. The aim of this article is to develop a tool for evaluating the absolute performance of RF coil arrays. An algorithm to calculate the ultimate intrinsic signal-to-noise ratio (SNR) was implemented for a spherical geometry. The same imaging tasks modeled in the calculations were reproduced experimentally using a 32-element head array. Coil performance maps were then generated based on the ratio of experimentally measured SNR to the ultimate intrinsic SNR, for different acceleration factors associated with different degrees of parallel imaging. The relative performance in all cases was highest near the center of the samples (where the absolute SNR was lowest). The highest performance was found in the unaccelerated case and a maximum of 85% was observed with a phantom whose electrical properties are consistent with values in the human brain. The performance remained almost constant for 2-fold acceleration, but deteriorated at higher acceleration factors, suggesting that larger arrays are needed for effective highly-accelerated parallel imaging. The method proposed here can serve as a tool for the evaluation of coil designs, as well as a tool to guide the development of original designs which may begin to approach the optimal performance.

Original languageEnglish (US)
Pages (from-to)142-151
Number of pages10
JournalNMR in Biomedicine
Issue number2
StatePublished - Feb 2010


  • Coil design
  • Coil performance
  • Electrodynamics
  • Magnetic resonance imaging
  • Parallel imaging
  • Phased-array
  • RF coils
  • Ultimate intrinsic SNR

ASJC Scopus subject areas

  • Molecular Medicine
  • Radiology Nuclear Medicine and imaging
  • Spectroscopy


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