Introduction
Quantitative susceptibility mapping (QSM) is a new contrast mechanism in magnetic resonance imaging (MRI). The images produced by the QSM enable researchers and clinicians to easily localize specific structures of the brain, such as deep brain nuclei. These nuclei are targets in many clinical applications and therefore their easy localization is a must. In this study, we aimed to implement two QSM estimation algorithms, threshold-based k-space division (TKD) and morphology enabled dipole inversion (MEDI) in presurgical planning.
Materials and Methods
In this study, susceptibility weighted imaging (SWI) was performed on six patients referred to our center for presurgical planning purposes. The susceptibility values, as well as the contrast-to-noise ratio of few brain regions were estimated. To identify the algorithm, which was best applicable to clinics, a comparison of the two methods was performed.
Results
QSM images were produced; however, the results did not show any significant differences between the susceptibility values of the two methods. The contrast-to-noise ratio for the susceptibility values of the subthalamic nucleus and substantia nigra brain regions were significantly superior using the MEDI approach over TKD, suggesting improved localization of brain regions using the former method.
Conclusion
This study suggests that to identify specific brain regions, such as deep brain nuclei, a QSM contrast would be more beneficial than the conventional MRI contrasts. This study compared MEDI and TKD methods for quantification of brain susceptibility maps, and results showed that the MEDI method resulted in higher-quality images.