Prediction of methylguanine methyltransferase promoter methylation in glioblastoma using dynamic contrast-enhanced magnetic resonance and diffusion tensor imaging

Clinical article

Sung Soo Ahn M.D., Ph.D.1, Na-Young Shin M.D.1, Jong Hee Chang M.D., Ph.D.2, Se Hoon Kim M.D., Ph.D.3, Eui Hyun Kim M.D.2, Dong Wook Kim Ph.D.4, and Seung-Koo Lee M.D., Ph.D.1
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  • 1 Department of Radiology, Research Institute of Radiological Science, Yonsei University College of Medicine;
  • | 2 Departments of Neurosurgery and
  • | 3 Pathology, Brain Research Institute, Yonsei University College of Medicine; and
  • | 4 Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Korea
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Object

The methylation status of the methylguanine methyltransferase (MGMT) promoter has been associated with treatment response in glioblastoma. The authors aimed to assess whether MGMT methylation status can be predicted by dynamic contrast-enhanced (DCE) MRI and diffusion tensor imaging (DTI).

Methods

This retrospective study included 43 patients with pathologically diagnosed glioblastoma who had undergone preoperative DCE-MRI and DTI and whose MGMT methylation status was available. The imaging features were qualitatively assessed using conventional MR images. Regions of interest analyses for DCE-MRI permeability parameters (transfer constant [Ktrans], rate transfer coefficient [Kep], and volume fraction of extravascular extracellular space [Ve]) and DTI parameters (apparent diffusion coefficient [ADC] and fractional anisotropy [FA]) were performed on the enhancing solid portion of the glioblastoma. Chi-square or Mann-Whitney tests were used to evaluate relationships between MGMT methylation and imaging parameters. The authors performed receiver operating characteristic curve analysis to find the optimal cutoff value for the presence of MGMT methylation.

Results

MGMT methylation was not significantly associated with any imaging features on conventional MR images. Ktrans values were significantly higher in the MGMT methylated group (median 0.091 vs 0.053 min−1, p = 0.018). However, Kep, Ve, ADC, and FA were not significantly different between the 2 groups. The optimal cutoff value for the presence of MGMT methylation was Ktrans > 0.086 min−1 with an area under the curve of 0.756, a sensitivity of 56.3%, and a specificity of 85.2%.

Conclusions

Ktrans may serve as a potential imaging biomarker to predict MGMT methylation status preoperatively in glioblastoma; however, further investigation with a larger cohort is necessary.

Abbreviations used in this paper:

ADC = apparent diffusion coefficient; BBB = blood-brain barrier; DCE = dynamic contrast-enhanced; DTI = diffusion tensor imaging; FA = fractional anisotropy; Kep = rate transfer coefficient; Ktrans = transfer constant; MGMT = methylguanine methyltransferase; ROI = region of interest; Ve = volume fraction of extravascular extracellular space.

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