Objective: Voxel-Based Morphometry (VBM) and Source-Based Morphometry (SBM) are widely used techniques for analyzing structural Magnetic Resonance Imaging (MRI) data. VBM compares differences in gray and white matter volume, density, or concentration voxel-wise, while SBM identifies patterns of structural variation using independent component analysis. This study aims to compare the performance of VBM and SBM in detecting differences in brain structure across Parkinson's patients and healthy controls, grouped based on their chronotype.
Methods: Thirty-three subjects were divided into three groups: a Parkinson's Group (PG), an Early Chronotype Group (EG), and a Late Chronotype Group (LG). Circadian preference, daytime sleepiness, and sleep quality were assessed, and MRI data were acquired using a 3 T scanner. SBM and VBM were used to test differences and similarities in MRI scans and chronotypes.
Results: Results from SBM revealed significant clusters surviving the analysis, with the 1st component for the PG-EG and the 4th component for the PG-LG analysis showing the lowest p-value (< 0.05). Denser gray matter volume (GMV) or white matter volume (WMV) was observed in the Middle Frontal Gyrus and the Lentiform Nucleus through Talairach Coordinates analysis.
Conclusions: This study emphasizes the importance of selecting appropriate methods for analyzing structural MRI data. VBM is effective in identifying local differences in brain structure, while SBM provides a more comprehensive view of structural variation, detecting patterns not captured by VBM. Future studies should consider utilizing both VBM and SBM to fully characterize brain structural differences in diverse clinical and cognitive populations. Further studies, with larger sample sizes and more balanced genders, genomic analysis, disease severity and duration, as well as medications' effect, are warranted.
Keywords: Parkinson; VBM; chronotype; neuroimaging; sBM.