Correlation of apparent diffusion coefficient values measured by diffusion MRI and MGMT promoter methylation semiquantitatively analyzed with MS‐MLPA in patients with glioblastoma multiforme

Abstract

To retrospectively determine whether the apparent diffusion coefficient (ADC) values correlate with O(6)-methylguanine DNA methyltransferase (MGMT) promoter methylation semiquantitatively analyzed by methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) in patients with glioblastoma. The study was approved by the Institutional Review Board and was Health Insurance Portability and Accountability Act (HIPAA) compliant. Newly diagnosed patients with glioblastoma (n = 26) were analyzed with an ADC histogram approach based on enhancing solid portion. The methylation status of MGMT promoter was assessed by methylation-specific polymerase chain reaction (MSP) and by MS-MLPA. MS-MLPA is a semiquantitative method that determines the methylation ratio. The Ki-67 labeling index was also analyzed. The mean and 5th percentile ADC values were correlated with MGMT promoter methylation status and Ki-67 labeling index using a linear regression model. Progression-free survival (PFS) was also correlated with the ADC values using Kaplan-Meier survival analysis. The mean methylation ratio was 0.21 ± 0.20. By MSP, there were 5 methylated and 21 unmethylated tumors. The mean ADC revealed a positive relationship with MGMT promoter methylation ratio (P = 0.015) and was also significantly different according to MSP-determined methylation status (P = 0.011). Median PFS was significantly related with methylation ratio (P = 0.017) and MSP-derived methylation status (P = 0.025). A positive relationship was demonstrated between PFS and the mean ADC value (P = 0.001). The 5th percentile ADC values showed a significant negative relationship with Ki-67 labeling index (P = 0.036). We found that ADC values were significantly correlated with PFS as well as with MGMT promoter methylation status. We believe that ADC values may merit further investigation as a noninvasive biomarker for predicting treatment response.