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Discriminating MGMT promoter methylation status in patients with glioblastoma employing amide proton transfer-weighted MRI metrics.

Authors :
Jiang S
Rui Q
Wang Y
Heo HY
Zou T
Yu H
Zhang Y
Wang X
Du Y
Wen X
Chen F
Wang J
Eberhart CG
Zhou J
Wen Z
Source :
European radiology [Eur Radiol] 2018 May; Vol. 28 (5), pp. 2115-2123. Date of Electronic Publication: 2017 Dec 12.
Publication Year :
2018

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).<br />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.<br />Results: Ten GBMs were found to harbour a methylated MGMT promoter, and eight GBMs were unmethylated. The mean, variance, 50th percentile, 90th percentile and Width <subscript>10-90</subscript> 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.<br />Conclusions: APTw signal metrics have the potential to serve as valuable imaging biomarkers for identifying MGMT methylation status in the GBM population.<br />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).

Details

Language :
English
ISSN :
1432-1084
Volume :
28
Issue :
5
Database :
MEDLINE
Journal :
European radiology
Publication Type :
Academic Journal
Accession number :
29234914
Full Text :
https://doi.org/10.1007/s00330-017-5182-4