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Purpose: The characteristics of surface-based morphological patterns to primary trigeminal neuralgia (PTN) are still not well understood. This study aims to screen the useful cortical indices for the prediction of PTN and the quantification of pain severity. Methods: Fifty PTN patients and 48 matched healthy subjects enrolled in the study from March 2016 to August 2021. High-resolution T1 data were performed at 3.0 Tesla scanner and were analyzed with FreeSurfer software to detect the abnormalities of cortical mean curve (CMC), cortical thickness (CT), surface area (SA), and cortical volume (CV) in PTN patients compared to healthy controls. Logistic regression analysis was conducted to determine whether certain morphological patterns could predict PTN disorder. Then, the relationships of cortical indices to the pain characteristics in patient group were examined using linear regression model. Results: Distinctive cortical alterations were discovered through surface-based analysis, including increased temporal CMC, decreased insular CT and fusiform SA, along with decreased CV in several temporal and occipital areas. Moreover, the difference of temporal CMC was greater than other cortical parameters between the two groups, and the combination of certain morphological indices was of good value in the diagnosis for PTN. Besides, CT of left insula was negatively associated with the pain intensity in PTN patients. Conclusion: The patients with PTN demonstrate distinctive morphological patterns in several cortical regions, which may contribute to the imaging diagnosis of this refractory disorder and be useful for the quantification of the orofacial pain. Clinical trials: The registry name of this study in https://clinicaltrials.gov/: Magnetic Resonance Imaging Study on Patients with Trigeminal Neuralgia (MRI-TN) https://clinicaltrials.gov/ ID: NCT02713646 A link to the full application: https://clinicaltrials.gov/ct2/results?cond=&term=NCT02713646&cntry=&state=&city=&dist= The first patient with primary trigeminal neuralgia was recruited on November 28, 2016. [ABSTRACT FROM AUTHOR]