Erschienen in:
12.12.2017 | Molecular Imaging
Discriminating MGMT promoter methylation status in patients with glioblastoma employing amide proton transfer-weighted MRI metrics
verfasst von:
Shanshan Jiang, Qihong Rui, Yu Wang, Hye-Young Heo, Tianyu Zou, Hao Yu, Yi Zhang, Xianlong Wang, Yongxing Du, Xinrui Wen, Fangyao Chen, Jihong Wang, Charles G. Eberhart, Jinyuan Zhou, Zhibo Wen
Erschienen in:
European Radiology
|
Ausgabe 5/2018
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Abstract
Objectives
To explore the feasibility of using amide proton transfer-weighted (APTw) MRI metrics as surrogate biomarkers to identify the O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status in glioblastoma (GBM).
Methods
Eighteen newly diagnosed GBM patients, who were previously scanned at 3T and had a confirmed MGMT methylation status, were retrospectively analysed. For each case, a histogram analysis in the tumour mass was performed to evaluate several quantitative APTw MRI metrics. The Mann-Whitney test was used to evaluate the difference in APTw parameters between MGMT methylated and unmethylated GBMs, and the receiver-operator-characteristic analysis was further used to assess diagnostic performance.
Results
Ten GBMs were found to harbour a methylated MGMT promoter, and eight GBMs were unmethylated. The mean, variance, 50th percentile, 90th percentile and Width10-90 APTw values were significantly higher in the MGMT unmethylated GBMs than in the MGMT methylated GBMs, with areas under the receiver-operator-characteristic curves of 0.825, 0.837, 0.850, 0856 and 0.763, respectively, for the discrimination of MGMT promoter methylation status.
Conclusions
APTw signal metrics have the potential to serve as valuable imaging biomarkers for identifying MGMT methylation status in the GBM population.
Key Points
• APTw-MRI is applied to predict MGMT promoter methylation status in GBMs.
• GBMs with unmethylated MGMT promoter present higher APTw-MRI than methylated GBMs.
• Multiple APTw histogram metrics can identify MGMT methylation status.
• Mean APTw values showed the highest diagnostic accuracy (AUC = 0.825).