Gaussian Filtering Effects on Brain Tissue-masked Susceptibility Weighted Images to Optimize Voxel-based Analysis

ABSTRACT

PURPOSE: The objective of this study was to investigate effects of different smoothing kernel sizes on brain tissue-masked susceptibility-weighted images (SWI) obtained from normal elderly subjects using voxel-based analyses. MATERIALS AND METHODS: Twenty healthy human volunteers (mean age+/-SD = 67.8 +/- 6.09 years, 14 females and 6 males) were studied after informed consent. A fully first-order flow-compensated three-dimensional (3D) gradient-echo sequence ran to obtain axial magnitude and phase images to generate SWI data. In addition, sagittal 3D T1-weighted images were acquired with the magnetization-prepared rapid acquisition of gradient-echo sequence for brain tissue segmentation and imaging registration. Both paramagnetically (PSWI) and diamagnetically (NSWI) phase-masked SWI data were obtained with masking out non-brain tissues. Finally, both tissue-masked PSWI and NSWI data were smoothed using different smoothing kernel sizes that were isotropic 0, 2, 4, and 8 mm Gaussian kernels. The voxel-based comparisons were performed using a paired t-test between PSWI and NSWI for each smoothing kernel size. RESULTS: The significance of comparisons increased with increasing smoothing kernel sizes. Signals from NSWI were greater than those from PSWI. The smoothing kernel size of four was optimal to use voxel-based comparisons. The bilaterally different areas were found on multiple brain regions. CONCLUSION: The paramagnetic (positive) phase mask led to reduce signals from high susceptibility areas. To minimize partial volume effects and contributions of large vessels, the voxel-based analysis on SWI with masked non-brain components should be utilized.