Quantification of superparamagnetic iron oxide using inversion recovery balanced steady-state free precession

Cellular and molecular MRI trafficking studies using superparamagnetic iron oxide (SPIO) have greatly improved non-invasive investigations of disease progression and drug efficacy, but thus far, these studies have largely been restricted to qualitative assessment of hypo- or hyperintense areas near SPIO. In this work, SPIO quantification using inversion recovery balanced steady-state free precession (IR-bSSFP) was demonstrated at 3 T by extracting R-2 values from a monoexponential model (P. Schmitt et al., 2004). A low flip angle was shown to reduce the apparent recovery rate of the IR-bSSFP time course, thus extending the dynamic range of quantification. However, low flip angle acquisitions preclude the use of traditional methods for combining RF phase-cycled images to reduce banding artifacts arising from off-resonance due to B-0 inhomogeneity. To achieve R-2 quantification of SPIO, we present a new algorithm applicable to low flip angle IR-bSSFP acquisitions that is specifically designed to identify on-resonance acquisitions. We demonstrate in this work, using both theoretical and empirical methods, that the smallest estimated R-2 from multiple RF phase-cycled acquisitions correspond well to the on-resonance time course. Using this novel minimum R-2 algorithm, homogeneous R-2 maps and linear R-2 calibration curves were created up to 100 mu g(Fe)/mL with 20 degrees flip angles, despite substantial B-0 inhomogeneity. In addition, we have shown this technique to be feasible for pre-clinical research: the minimum R-2 algorithm was resistant to off-resonance in a single slice mouse R-2 map, whereas maximum intensity projection resulted in banding artifacts and overestimated R-2 values. With the application of recent advances in accelerated acquisitions, IR-bSSFP has the potential to quantify SPIO in vivo, thus providing important information for oncology, immunology, and regenerative medicine MRI studies. Crown Copyright (c) 2013 Published by Elsevier Inc. All rights reserved.