T1 estimation for aqueous iron oxide nanoparticle suspensions using a variable flip angle SWIFT sequence

Luning Wang, Curtis A. Corum, Djaudat Idiyatullin, Michael Garwood, Qun Zhao

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

Purpose T1 quantification of contrast agents, such as super-paramagnetic iron oxide nanoparticles, is a challenging but important task inherent to many in vivo applications in magnetic resonance imaging. In this work, a sweep imaging with Fourier transformation using variable flip angles (VFAs-SWIFT) method was proposed to measure T1 of aqueous super-paramagnetic iron oxide nanoparticle suspensions. Methods T1 values of various iron concentrations (from 1 to 7 mM) were measured using VFA-SWIFT and three-dimensional spoiled gradient-recalled echo with VFAs (VFA-SPGR) sequences on a 7 T MR scanner. For validation, T1 values were also measured using a spectroscopic inversion-recovery sequence on a 7 T spectrometer. Results VFA-SWIFT demonstrated its advantage for quantifying T1 of highly concentrated aqueous super-paramagnetic iron oxide nanoparticle suspensions, but VFA-SPGR failed at the higher end of iron concentrations. Both VFA-SWIFT and VFA-SPGR yielded linear relationships between the relaxation rate and iron concentrations, with relaxivities of 1.006 and 1.051 s-1 mM-1 at 7 T, respectively, in excellent agreement with the spectroscopic measurement of 1.019 s-1 mM -1. Conclusion VFA-SWIFT is able to achieve accurate T1 quantification of aqueous super-paramagnetic iron oxide nanoparticle suspensions up to 7 mM.

Original languageEnglish (US)
Pages (from-to)341-347
Number of pages7
JournalMagnetic resonance in medicine
Volume70
Issue number2
DOIs
StatePublished - Aug 2013

Keywords

  • positive contrast
  • super-paramagnetic iron oxide nanoparticles
  • sweep imaging with Fourier transformation

Fingerprint Dive into the research topics of 'T<sub>1</sub> estimation for aqueous iron oxide nanoparticle suspensions using a variable flip angle SWIFT sequence'. Together they form a unique fingerprint.

Cite this