Literature DB >> 24949678

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

Sung Soo Ahn1, Na-Young Shin, Jong Hee Chang, Se Hoon Kim, Eui Hyun Kim, Dong Wook Kim, Seung-Koo Lee.   

Abstract

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.

Entities:  

Keywords:  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; O-6-methylguanine-DNA methyltransferase; ROI = region of interest; Ve = volume fraction of extravascular extracellular space; diffusion tensor imaging; glioblastoma; magnetic resonance imaging; oncology; permeability

Mesh:

Substances:

Year:  2014        PMID: 24949678     DOI: 10.3171/2014.5.JNS132279

Source DB:  PubMed          Journal:  J Neurosurg        ISSN: 0022-3085            Impact factor:   5.115


  28 in total

1.  Residual Deep Convolutional Neural Network Predicts MGMT Methylation Status.

Authors:  Panagiotis Korfiatis; Timothy L Kline; Daniel H Lachance; Ian F Parney; Jan C Buckner; Bradley J Erickson
Journal:  J Digit Imaging       Date:  2017-10       Impact factor: 4.056

Review 2.  Imaging signatures of glioblastoma molecular characteristics: A radiogenomics review.

Authors:  Anahita Fathi Kazerooni; Spyridon Bakas; Hamidreza Saligheh Rad; Christos Davatzikos
Journal:  J Magn Reson Imaging       Date:  2019-08-27       Impact factor: 4.813

Review 3.  Imaging genomics in cancer research: limitations and promises.

Authors:  Harrison X Bai; Ashley M Lee; Li Yang; Paul Zhang; Christos Davatzikos; John M Maris; Sharon J Diskin
Journal:  Br J Radiol       Date:  2016-02-11       Impact factor: 3.039

4.  Amide proton transfer imaging to discriminate between low- and high-grade gliomas: added value to apparent diffusion coefficient and relative cerebral blood volume.

Authors:  Yoon Seong Choi; Sung Soo Ahn; Seung-Koo Lee; Jong Hee Chang; Seok-Gu Kang; Se Hoon Kim; Jinyuan Zhou
Journal:  Eur Radiol       Date:  2017-01-23       Impact factor: 5.315

5.  The Initial Area Under the Curve Derived from Dynamic Contrast-Enhanced MRI Improves Prognosis Prediction in Glioblastoma with Unmethylated MGMT Promoter.

Authors:  Y S Choi; S S Ahn; H-J Lee; J H Chang; S-G Kang; E H Kim; S H Kim; S-K Lee
Journal:  AJNR Am J Neuroradiol       Date:  2017-06-22       Impact factor: 3.825

6.  New prognostic factor telomerase reverse transcriptase promotor mutation presents without MR imaging biomarkers in primary glioblastoma.

Authors:  Tunc F Ersoy; Vera C Keil; Dariusch R Hadizadeh; Gerrit H Gielen; Rolf Fimmers; Andreas Waha; Barbara Heidenreich; Rajiv Kumar; Hans H Schild; Matthias Simon
Journal:  Neuroradiology       Date:  2017-09-11       Impact factor: 2.804

7.  Diagnostic Accuracy of T1-Weighted Dynamic Contrast-Enhanced-MRI and DWI-ADC for Differentiation of Glioblastoma and Primary CNS Lymphoma.

Authors:  X Lin; M Lee; O Buck; K M Woo; Z Zhang; V Hatzoglou; A Omuro; J Arevalo-Perez; A A Thomas; J Huse; K Peck; A I Holodny; R J Young
Journal:  AJNR Am J Neuroradiol       Date:  2016-12-08       Impact factor: 3.825

Review 8.  Conventional and advanced magnetic resonance imaging in patients with high-grade glioma.

Authors:  Whitney B Pope; Garth Brandal
Journal:  Q J Nucl Med Mol Imaging       Date:  2018-04-26       Impact factor: 2.346

9.  MRI-Based Deep-Learning Method for Determining Glioma MGMT Promoter Methylation Status.

Authors:  C G B Yogananda; B R Shah; S S Nalawade; G K Murugesan; F F Yu; M C Pinho; B C Wagner; B Mickey; T R Patel; B Fei; A J Madhuranthakam; J A Maldjian
Journal:  AJNR Am J Neuroradiol       Date:  2021-03-04       Impact factor: 3.825

Review 10.  Dynamic contrast-enhanced (DCE) imaging: state of the art and applications in whole-body imaging.

Authors:  Domenico Albano; Federico Bruno; Andrea Agostini; Salvatore Alessio Angileri; Massimo Benenati; Giulia Bicchierai; Michaela Cellina; Vito Chianca; Diletta Cozzi; Ginevra Danti; Federica De Muzio; Letizia Di Meglio; Francesco Gentili; Giuliana Giacobbe; Giulia Grazzini; Irene Grazzini; Pasquale Guerriero; Carmelo Messina; Giuseppe Micci; Pierpaolo Palumbo; Maria Paola Rocco; Roberto Grassi; Vittorio Miele; Antonio Barile
Journal:  Jpn J Radiol       Date:  2021-12-24       Impact factor: 2.374

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