Magnetic Resonance Image Texture Analysis of the Periaqueductal Gray Matter in Episodic Migraine Patients without T2-Visible Lesions

OBJECTIVE: The periaqueductal gray matter (PAG), a small midbrain structure, presents dysfunction in migraine. However, the precise neurological mechanism is still not well understood. Herein, the aim of this study was to investigate the texture characteristics of altered PAG in episodic migraine (EM) patients based on high resolution brain structural magnetic resonance (MR) images. MATERIALS AND METHODS: The brain structural MR images were obtained from 18 normal controls (NC), 18 EM patients and 16 chronic migraine (CM) patients using a 3T MR system. A PAG template was created using the International Consortium Brain Mapping 152 gray matter model, and the individual PAG segment was developed by applying the deformation field from the structural image segment to the PAG template. A grey level co-occurrence matrix was used to calculate the texture parameters including the angular second moment (ASM), contrast, correlation, inverse difference moment (IDM) and entropy. RESULTS: There was a significant difference for ASM, IDM and entropy in the EM group (998.629 ± 0.162 × 10(−3), 999.311 ± 0.073 × 10(−3), 916.354 ± 0.947 × 10(−5)) compared to that found in the NC group (998.760 ± 0.110 × 10(−3), 999.358 ± 0.037 × 10(−3) and 841.198 ± 0.575 × 10(−5)) (p < 0.05). The entropy was significantly lower among the patients with CM (864.116 ± 0.571 × 10(−5)) than that found among patients with EM (p < 0.05). The area under the receiver operating characteristic curve was 0.776 and 0.750 for ASM and entropy in the distinction of the EM from NC groups, respectively. ASM was negatively related to disease duration (DD) and the Migraine Disability Assessment Scale (MIDAS) scores in the EM group, and entropy was positively related to DD and MIDAS in the EM group (p < 0.05). CONCLUSION: The present study identified altered MR image texture characteristics of the PAG in EM. The identified texture characteristics could be considered as imaging biomarkers for EM.