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Quantification of SPIO nanoparticles in vivo using the finite perturber method
Author(s) -
Langley Jason,
Liu Wei,
Jordan E. Kay,
Frank J. A.,
Zhao Qun
Publication year - 2011
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.22727
Subject(s) - imaging phantom , in vivo , contrast (vision) , nanoparticle , magnetic resonance imaging , gaussian , materials science , nuclear magnetic resonance , biomedical engineering , magnetic nanoparticles , biological system , chemistry , physics , nanotechnology , optics , radiology , biology , medicine , microbiology and biotechnology , computational chemistry
Abstract The susceptibility gradients generated by super‐paramagnetic iron oxide (SPIO) nanoparticles make them an ideal contrast agent in magnetic resonance imaging. Traditional quantification methods for SPIO nanoparticle‐based contrast agents rely on either mapping T 2 *values within a region or by modeling the magnetic field inhomogeneities generated by the contrast agent. In this study, a new model‐based SPIO quantification method is introduced. The proposed method models magnetic field inhomogeneities by approximating regions containing SPIOs as ensembles of magnetic dipoles, referred to as the finite perturber method. The proposed method was verified using data acquired from a phantom and in vivo mouse models. The phantom consisted of an agar solution with four embedded vials, each vial containing known but different concentrations of SPIO nanoparticles. Gaussian noise was also added to the phantom data to test performance of the proposed method. The in vivo dataset was acquired using five mice, each of which was subcutaneously implanted in the flanks with 1 × 10 5 labeled and 1 × 10 6 unlabeled C6 glioma cells. For the phantom data set, the proposed algorithm was generate accurate estimations of the concentration of SPIOs. For the in vivo dataset, the method was able to give estimations of the concentration within SPIO‐labeled tumors that are reasonably close to the known concentration. Magn Reson Med, 2011. © 2010 Wiley‐Liss, Inc.