Literature DB >> 30002055

Clinically Relevant Imaging Features for MGMT Promoter Methylation in Multiple Glioblastoma Studies: A Systematic Review and Meta-Analysis.

C H Suh1, H S Kim2, S C Jung1, C G Choi1, S J Kim1.   

Abstract

BACKGROUND: O6-methylguanine methyltransferase (MGMT) promoter methylation status has been reported as a prognostic biomarker in clinical trials.
PURPOSE: Our aim was to systematically evaluate imaging features of MGMT promoter methylated glioblastoma and to determine the diagnostic performance of MR imaging for prediction of MGMT promoter methylation in patients with newly diagnosed glioblastoma. DATA SOURCES: A computerized search of Ovid MEDLINE and EMBASE up to February 27, 2018, was conducted. STUDY SELECTION: We selected studies evaluating imaging features of MGMT promoter methylated glioblastoma and the diagnostic performance of MR imaging for prediction of MGMT promoter methylation. DATA ANALYSIS: Pooled estimates of sensitivity and specificity were calculated using a hierarchic logistic regression model. Meta-regression and sensitivity analysis were performed. DATA SYNTHESIS: Twenty-two articles including 2199 patients were included. MGMT promoter methylated glioblastoma is likely to show less edema, high ADC, and low perfusion. Ten articles including 753 patients were included in the meta-analysis. The summary sensitivity was 79% (95% CI, 72%-85%), and the summary specificity was 78% (95% CI, 71%-84%). In the meta-regression, MGMT promoter methylation and mean age were associated with heterogeneity. Sensitivity analysis excluding 1 study resolved the heterogeneity. LIMITATIONS: Included studies used a variety of different MR imaging techniques to predict MGMT promoter methylation.
CONCLUSIONS: MGMT promotor methylated glioblastoma is likely to show less aggressive imaging features than MGMT promotor unmethylated glioblastoma. Despite the variety of different MR imaging techniques used, MR imaging in patients with newly diagnosed glioblastoma was shown to have the potential to predict MGMT promoter methylation noninvasively.
© 2018 by American Journal of Neuroradiology.

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Year:  2018        PMID: 30002055     DOI: 10.3174/ajnr.A5711

Source DB:  PubMed          Journal:  AJNR Am J Neuroradiol        ISSN: 0195-6108            Impact factor:   3.825


  9 in total

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Authors:  Natalia Saltybaeva; Stephanie Tanadini-Lang; Diem Vuong; Simon Burgermeister; Michael Mayinger; Andrea Bink; Nicolaus Andratschke; Matthias Guckenberger; Marta Bogowicz
Journal:  Phys Imaging Radiat Oncol       Date:  2022-05-14

2.  MGMT Promoter Methylation Status in Initial and Recurrent Glioblastoma: Correlation Study with DWI and DSC PWI Features.

Authors:  H J Choi; S H Choi; S-H You; R-E Yoo; K M Kang; T J Yun; J-H Kim; C-H Sohn; C-K Park; S-H Park
Journal:  AJNR Am J Neuroradiol       Date:  2021-02-25       Impact factor: 3.825

3.  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

4.  Fluid attenuation in non-contrast-enhancing tumor (nCET): an MRI Marker for Isocitrate Dehydrogenase (IDH) mutation in Glioblastoma.

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Journal:  J Neurooncol       Date:  2021-03-04       Impact factor: 4.130

5.  Apatinib Plus Temozolomide for Recurrent Glioblastoma: An Uncontrolled, Open-Label Study.

Authors:  Yong Wang; Xiangji Meng; Shizhen Zhou; Yufang Zhu; Jun Xu; Rongjie Tao
Journal:  Onco Targets Ther       Date:  2019-12-03       Impact factor: 4.147

6.  MR Fingerprinting-A Radiogenomic Marker for Diffuse Gliomas.

Authors:  Elisabeth Springer; Pedro Lima Cardoso; Bernhard Strasser; Wolfgang Bogner; Matthias Preusser; Georg Widhalm; Mathias Nittka; Gregor Koerzdoerfer; Pavol Szomolanyi; Gilbert Hangel; Johannes A Hainfellner; Wolfgang Marik; Siegfried Trattnig
Journal:  Cancers (Basel)       Date:  2022-01-30       Impact factor: 6.575

7.  Multiparametric MR radiomics in brain glioma: models comparation to predict biomarker status.

Authors:  Jinlong He; Jialiang Ren; Guangming Niu; Aishi Liu; Qiong Wu; Shenghui Xie; Xueying Ma; Bo Li; Peng Wang; Jing Shen; Jianlin Wu; Yang Gao
Journal:  BMC Med Imaging       Date:  2022-08-05       Impact factor: 2.795

8.  Validation of MRI-Based Models to Predict MGMT Promoter Methylation in Gliomas: BraTS 2021 Radiogenomics Challenge.

Authors:  Byung-Hoon Kim; Hyeonhoon Lee; Kyu Sung Choi; Ju Gang Nam; Chul-Kee Park; Sung-Hye Park; Jin Wook Chung; Seung Hong Choi
Journal:  Cancers (Basel)       Date:  2022-10-03       Impact factor: 6.575

9.  Association between MGMT status and response to alkylating agents in patients with neuroendocrine neoplasms: a systematic review and meta-analysis.

Authors:  Zhirong Qi; Huangying Tan
Journal:  Biosci Rep       Date:  2020-03-27       Impact factor: 3.840

  9 in total

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