Objectives: The objective of our study was to investigate whether a phosphatase and tensin homolog deleted on chromosome 10 (PTEN) expression was associated with dynamic contrast-enhanced MRI (DCE-MRI) parameters and prognosis in nasopharyngeal carcinoma (NPC). Methods: Two hundred and forty-ve (245) patients with NPC who underwent pretreatment biopsy, PTEN immunohistochemistry of biopsy, and radical intensity-modulated radiation therapy (IMRT) with or without chemotherapy were included. Tumor segmentations were delineated on pretreatment MRI manually. The pharmacokinetic parameters (Ktrans, Kep, Ve, and Vp) derived from dynamic contrastenhanced MRI (DCE-MRI) using the extended Toft's model within the tumor segmentations were estimated. The following demographics and clinical features were assessed and correlated against each other: gender, age, TNM stage, clinical-stage, Epstein-Barr virus (EBV), pathological type, progression-free survival (PFS), and prognosis status. DCE parameter evaluation and clinical feature comparison between the PTEN positive and negative groups was performed and correlation between PTEN expression with the PFS and prognosis status using Cox regression for survival analysis was assessed. Results: A signi cantly lower K trans and K ep were found in NPC tumors in PTEN negative patients than in PTEN positive patients. K trans performed better than K ep in detecting PTEN expression with the ROC AUC of 0.752. PTEN negative was associated with later TNM stage, later clinical-stage, shorter PFS, and worse prognosis. Moreover, N stage, pathological type, K ep , and prognostic status can be considered as independent variables in discrimination of PTEN negative expression in NPCs. Conclusions: PTEN negative indicated a shorter PFS and worse prognosis than PTEN positive in NPC patients. K trans and K ep derived from DCE-MRI, which yielded reliable capability, should be considered as novel image markers that are correlated with PTEN expression and may be used to predict PTEN expression noninvasively. Combined radiological and clinical features can improve the performance of the classi cation of PTEN expression.