Vasileios G Kanas1, Evangelia I Zacharaki2, Ginu A Thomas3, Pascal O Zinn4, Vasileios Megalooikonomou5, Rivka R Colen3. 1. Department of Electrical and Computer Engineering, University of Patras, Patras, Greece; Department of Computer Engineering and Informatics, University of Patras, Patras, Greece. 2. Department of Computer Engineering and Informatics, University of Patras, Patras, Greece; Center for Visual Computing (CVC), CentraleSupélec, INRIA, Université Paris-Saclay, France. Electronic address: evangelia.zacharaki@centralesupelec.fr. 3. Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA. 4. Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA. 5. Department of Computer Engineering and Informatics, University of Patras, Patras, Greece.
Abstract
BACKGROUND AND OBJECTIVE: The O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation has been shown to be associated with improved outcomes in patients with glioblastoma (GBM) and may be a predictive marker of sensitivity to chemotherapy. However, determination of the MGMT promoter methylation status requires tissue obtained via surgical resection or biopsy. The aim of this study was to assess the ability of quantitative and qualitative imaging variables in predicting MGMT methylation status noninvasively. METHODS: A retrospective analysis of MR images from GBM patients was conducted. Multivariate prediction models were obtained by machine-learning methods and tested on data from The Cancer Genome Atlas (TCGA) database. RESULTS: The status of MGMT promoter methylation was predicted with an accuracy of up to 73.6%. Experimental analysis showed that the edema/necrosis volume ratio, tumor/necrosis volume ratio, edema volume, and tumor location and enhancement characteristics were the most significant variables in respect to the status of MGMT promoter methylation in GBM. CONCLUSIONS: The obtained results provide further evidence of an association between standard preoperative MRI variables and MGMT methylation status in GBM.
BACKGROUND AND OBJECTIVE: The O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation has been shown to be associated with improved outcomes in patients with glioblastoma (GBM) and may be a predictive marker of sensitivity to chemotherapy. However, determination of the MGMT promoter methylation status requires tissue obtained via surgical resection or biopsy. The aim of this study was to assess the ability of quantitative and qualitative imaging variables in predicting MGMT methylation status noninvasively. METHODS: A retrospective analysis of MR images from GBM patients was conducted. Multivariate prediction models were obtained by machine-learning methods and tested on data from The Cancer Genome Atlas (TCGA) database. RESULTS: The status of MGMT promoter methylation was predicted with an accuracy of up to 73.6%. Experimental analysis showed that the edema/necrosis volume ratio, tumor/necrosis volume ratio, edema volume, and tumor location and enhancement characteristics were the most significant variables in respect to the status of MGMT promoter methylation in GBM. CONCLUSIONS: The obtained results provide further evidence of an association between standard preoperative MRI variables and MGMT methylation status in GBM.
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
Authors: Roberto Altieri; Francesco Zenga; Alessandro Ducati; Antonio Melcarne; Fabio Cofano; Marco Mammi; Giuseppe Di Perna; Riccardo Savastano; Diego Garbossa Journal: Neurosurg Rev Date: 2017-08-31 Impact factor: 3.042
Authors: Jeffrey D Rudie; Andreas M Rauschecker; R Nick Bryan; Christos Davatzikos; Suyash Mohan Journal: Radiology Date: 2019-01-22 Impact factor: 11.105
Authors: P Chang; J Grinband; B D Weinberg; M Bardis; M Khy; G Cadena; M-Y Su; S Cha; C G Filippi; D Bota; P Baldi; L M Poisson; R Jain; D Chow Journal: AJNR Am J Neuroradiol Date: 2018-05-10 Impact factor: 3.825
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