Shanshan Jiang1,2,3, Qihong Rui4, Yu Wang5, Hye-Young Heo6, Tianyu Zou4, Hao Yu4, Yi Zhang6, Xianlong Wang4, Yongxing Du4, Xinrui Wen7, Fangyao Chen8, Jihong Wang9, Charles G Eberhart10, Jinyuan Zhou6, Zhibo Wen11. 1. Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, 510282, China. sjiang21@jhmi.edu. 2. Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, MD, 21287, USA. sjiang21@jhmi.edu. 3. Department of Radiology, Futian Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China. sjiang21@jhmi.edu. 4. Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, 510282, China. 5. Department of Pathology, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China. 6. Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, MD, 21287, USA. 7. Department of Neurology, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China. 8. Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China. 9. Department of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. 10. Department of Pathology, Johns Hopkins University, Baltimore, MD, USA. 11. Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, 510282, China. zhibowen@163.com.
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).
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).
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