Comprehensive MRI quantification of the substantia nigra pars compacta in Parkinson's disease. Issue 109 (December 2018) - Takahashi, H.; Watanabe, Y.; Tanaka, H.; Mihara, M.; Mochizuki, H.; Takahashi, K.; Yamamoto, K.; Liu, T.; Wang, Y.; Tomiyama, N.
Highlights: PD is characterized by dopaminergic neurodegeneration and iron overload in the SNpc. QSM can quantify iron deposition. Neuromelanin imaging can quantify loss of dopaminergic neurons. A novel automatic volumetric SNpc region of interest selection method was developed. QSM and neuromelanin imaging are useful for quantifying the SNpc alterations in PD. Abstract: Purpose: To quantify dopaminergic neurodegeneration and iron overload in the substantia nigra pars compacta (SNpc) to evaluate Parkinson's disease (PD) using both quantitative susceptibility mapping (QSM) and neuromelanin imaging. Materials and methods: We studied 39 PD patients (PD group) and 25 healthy controls (HC group) who underwent brain MRI with QSM and neuromelanin imaging. QSM and neuromelanin values of the SNpc were obtained using a voxel-based automated region segmentation system. The signal-to-noise ratio (SNR) of the SNpc in the neuromelanin images was calculated based on the mean value for the background region. The neuromelanin value was defined as the neuromelanin volume with an SNR higher than that of the background. The significance of the intergroup differences, and according to the severity stages in the PD group was tested for each QSM and neuromelanin value. Receiver-operating characteristic (ROC) analysis for diagnosing PD was performed for QSM and neuromelanin values. Results: The QSM value was significantly higher in the PD group than in the HC group (P < 0.05). The neuromelanin value was significantly smaller in the PD group than in the HC group (P < 0.05). The areas under the ROC curve were 0.68 and 0.86 for QSM and neuromelanin values, respectively. Using QSM and neuromelanin imaging to classify the PD stage was difficult. Conclusions: Quantifying the SNpc alterations with our region-based approach is useful for the diagnosis of PD.