Structural and advanced imaging in predicting MGMT promoter methylation of primary glioblastoma: a region of interest based analysis

• Main Authors: Yu Han, Lin-Feng Yan, Xi-Bin Wang, Ying-Zhi Sun, Xin Zhang, Zhi-Cheng Liu, Hai-Yan Nan, Yu-Chuan Hu, Yang Yang, Jin Zhang, Ying Yu, Qian Sun, Qiang Tian, Bo Hu, Gang Xiao, Wen Wang, Guang-Bin Cui
• Format: Article
• Language: English
• Published: BMC 2018-02-01
• Series: BMC Cancer
• Subjects: Glioblastoma; Image feature; Oxygen 6-methylguanine-DNA methyltransferase (MGMT) promoter; Apparent diffusion coefficient (ADC); 3-diminsional pseudo-continuous arterial spin labeling (3D pCASL) imaging
• Online Access: http://link.springer.com/article/10.1186/s12885-018-4114-2

Abstract Background The methylation status of oxygen 6-methylguanine-DNA methyltransferase (MGMT) promoter has been associated with treatment response in glioblastoma(GBM). Using pre-operative MRI techniques to predict MGMT promoter methylation status remains inconclusive. In this study, we investigated the value of features from structural and advanced imagings in predicting the methylation of MGMT promoter in primary glioblastoma patients. Methods Ninety-two pathologically confirmed primary glioblastoma patients underwent preoperative structural MR imagings and the efficacy of structural image features were qualitatively analyzed using Fisher’s exact test. In addition, 77 of the 92 patients underwent additional advanced MRI scans including diffusion-weighted (DWI) and 3-diminsional pseudo-continuous arterial spin labeling (3D pCASL) imaging. Apparent diffusion coefficient (ADC) and relative cerebral blood flow (rCBF) values within the manually drawn region-of-interest (ROI) were calculated and compared using independent sample t test for their efficacies in predicting MGMT promoter methylation. Receiver operating characteristic curve (ROC) analysis was used to investigate the predicting efficacy with the area under the curve (AUC) and cross validations. Multiple-variable logistic regression model was employed to evaluate the predicting performance of multiple variables. Results MGMT promoter methylation was associated with tumor location and necrosis (P <  0.05). Significantly increased ADC value (P <  0.001) and decreased rCBF (P <  0.001) were associated with MGMT promoter methylation in primary glioblastoma. The ADC achieved the better predicting efficacy than rCBF (ADC: AUC, 0.860; sensitivity, 81.1%; specificity, 82.5%; vs rCBF: AUC, 0.835; sensitivity, 75.0%; specificity, 78.4%; P = 0.032). The combination of tumor location, necrosis, ADC and rCBF resulted in the highest AUC of 0.914. Conclusion ADC and rCBF are promising imaging biomarkers in clinical routine to predict the MGMT promoter methylation in primary glioblastoma patients.