1.
Joint 2D and 3D phase processing for quantitative susceptibility mapping: application to 2D echo-planar imaging.
Wei, H, Zhang, Y, Gibbs, E, Chen, NK, Wang, N, Liu, C
NMR in biomedicine. 2017;(4)
Abstract
Quantitative susceptibility mapping (QSM) measures tissue magnetic susceptibility and typically relies on time-consuming three-dimensional (3D) gradient-echo (GRE) MRI. Recent studies have shown that two-dimensional (2D) multi-slice gradient-echo echo-planar imaging (GRE-EPI), which is commonly used in functional MRI (fMRI) and other dynamic imaging techniques, can also be used to produce data suitable for QSM with much shorter scan times. However, the production of high-quality QSM maps is difficult because data obtained by 2D multi-slice scans often have phase inconsistencies across adjacent slices and strong susceptibility field gradients near air-tissue interfaces. To address these challenges in 2D EPI-based QSM studies, we present a new data processing procedure that integrates 2D and 3D phase processing. First, 2D Laplacian-based phase unwrapping and 2D background phase removal are performed to reduce phase inconsistencies between slices and remove in-plane harmonic components of the background phase. This is followed by 3D background phase removal for the through-plane harmonic components. The proposed phase processing was evaluated with 2D EPI data obtained from healthy volunteers, and compared against conventional 3D phase processing using the same 2D EPI datasets. Our QSM results were also compared with QSM values from time-consuming 3D GRE data, which were taken as ground truth. The experimental results show that this new 2D EPI-based QSM technique can produce quantitative susceptibility measures that are comparable with those of 3D GRE-based QSM across different brain regions (e.g. subcortical iron-rich gray matter, cortical gray and white matter). This new 2D EPI QSM reconstruction method is implemented within STI Suite, which is a comprehensive shareware for susceptibility imaging and quantification. Copyright © 2016 John Wiley & Sons, Ltd.
2.
Applying amide proton transfer-weighted MRI to distinguish pseudoprogression from true progression in malignant gliomas.
Ma, B, Blakeley, JO, Hong, X, Zhang, H, Jiang, S, Blair, L, Zhang, Y, Heo, HY, Zhang, M, van Zijl, PC, et al
Journal of magnetic resonance imaging : JMRI. 2016;(2):456-62
-
-
Free full text
-
Abstract
PURPOSE To assess amide proton transfer-weighted (APTW) imaging features in patients with malignant gliomas after chemoradiation and the diagnostic performance of APT imaging for distinguishing true progression from pseudoprogression. MATERIALS AND METHODS After approval by the Institutional Review Board, 32 patients with clinically suspected tumor progression in the first 3 months after chemoradiation were enrolled and scanned at 3T. Longitudinal routine magnetic resonance imaging (MRI) changes and medical records were assessed to confirm true progression versus pseudoprogression. True progression was defined as lesions progressing on serial imaging over 6 months, and pseudoprogression was defined as lesions stabilizing or regressing without intervention. The APTWmean and APTWmax signals were obtained from three to five regions of interests for each patient and compared between the true progression and pseudoprogression groups. The diagnostic performance was assessed with receiver operating characteristic curve analysis. RESULTS The true progression was associated with APTW hyperintensity (APTWmean = 2.75% ± 0.42%), while pseudoprogression was associated with APTW isointensity to mild hyperintensity (APTWmean = 1.56% ± 0.42%). The APTW signal intensities were significantly higher in the true progression group (n = 20) than in the pseudoprogression group (P < 0.001; n = 12). The cutoff APTWmean and APTWmax intensity values to distinguish between true progression and pseudoprogression were 2.42% (with a sensitivity of 85.0% and a specificity of 100%) and 2.54% (with a sensitivity of 95.0% and a specificity of 91.7%), respectively. CONCLUSION The APTW-MRI signal is a valuable imaging biomarker for distinguishing pseudoprogression from true progression in glioma patients. J. Magn. Reson. Imaging 2016;44:456-462.