Exploratory SWI-based texture analysis of the substantia nigra on MRI in parkinson's disease

This study aimed to compare the substantia nigra of patients with Parkinson's disease (PD) and healthy controls using magnetic resonance imaging texture analysis findings. Texture analysis was performed on the pixels within each region of interest in the substantia nigra for all participants. The entire imaging analysis workflow was implemented using an in-house algorithm developed using Matrix Laboratory. This study included 76 participants (37 patients and 39 controls). There were no significant differences between the groups in terms of age or sex (P > .05). In the unadjusted analysis, kurtosis, skewness, and uniformity differed significantly between patients and controls (P < .05); however, after correction for multiple comparisons, only kurtosis remained statistically significant. Receiver operating characteristic curve analysis demonstrated moderate discriminative performance, with kurtosis showing the most robust results. These findings suggest a potential supportive role of susceptibility-weighted imaging-based texture analysis in PD; however, given the exploratory design and the absence of external validation, the results should be interpreted with caution. The findings of this study suggest that texture analysis applied to imaging data of patients with PD may have a potential supportive role in the diagnostic evaluation of the disease.