Characterization of normal appearing brain structures using high-resolution quantitative magnetization transfer steady-state free precession imaging

Compared to standard spoiled gradient echo (SPGR)-methods, balanced steady-state free precession (bSSFP) provides quantitative magnetization transfer (qMT) images with increased resolution and high signal-to-noise ratio (SNR) in clinically feasible acquisition times. The aim of this study was to acquire 3D high-resolution qMT-data to create standardized qMT-values of many single brain structures that might serve as a baseline for the future characterization of pathologies of the brain. QMT parameters, such as the fractional pool size (F), exchange rate (kf) and relaxation times of the free pool (T1, T2) were assessed in a total of 12 white matter (WM) and 11 grey matter (GM) structures in 12 healthy volunteers with MT-sensitized bSSFP. Our results were compared with qMT-data from previous studies obtained with SPGR-methods using MT-sensitizing preparation pulses with significantly lower resolution. In general, qMT-values were in good accordance with prior studies. As expected, higher F and kf and lower relaxation times were observed in WM as compared to GM structures. However, many significant differences were observed within WM and GM regions and also between different regions of the same structure like in the internal capsule where the posterior limb showed significant higher kf than the anterior limb. Significant differences for all parameters were observed between subjects. In contrast to previous studies, bSSFP allowed assessment of even small brain structures due to its high resolution. The observed differences from previous studies can partly be explained by the reduced partial volume effects. MT-sensitized bSSFP is an ideal candidate for qMT-analysis in the clinical routine as it provides high-resolution 3D qMT-data of even small brain structures in clinically feasible acquisition times. The present qMT-data can serve as a reference for the characterization of cerebral diseases. (C) 2010 Elsevier Inc. All rights reserved.