Learning MRI-based classification models for MGMT methylation status prediction in glioblastoma
•A noninvasive and reliable surrogate method of determining MGMT status could serve to complement brain tumor biopsy or as an alternative in those patients who have a contraindication to undergo an invasive procedure.•The significance of magnetic resonance 3D volumetrics and qualitative imaging feat...
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| Published in: | Computer methods and programs in biomedicine Vol. 140; pp. 249 - 257 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
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01.03.2017
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| ISSN: | 0169-2607, 1872-7565, 1872-7565 |
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| Abstract | •A noninvasive and reliable surrogate method of determining MGMT status could serve to complement brain tumor biopsy or as an alternative in those patients who have a contraindication to undergo an invasive procedure.•The significance of magnetic resonance 3D volumetrics and qualitative imaging features for predicting MGMT methylation status in glioblastoma was evaluated (73.6% accuracy achieved).•Our analysis showed that the edema/necrosis volume ratio, tumor/necrosis volume ratio, edema volume, and tumor location and enhancement characteristics were associated with the status of MGMT promoter methylation in glioblastoma.•The results of our study provide further evidence of an association between standard preoperative MRI features and MGMT methylation status in glioblastoma.
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.
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.
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.
The obtained results provide further evidence of an association between standard preoperative MRI variables and MGMT methylation status in GBM. |
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| AbstractList | The O
-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.
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.
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.
The obtained results provide further evidence of an association between standard preoperative MRI variables and MGMT methylation status in GBM. •A noninvasive and reliable surrogate method of determining MGMT status could serve to complement brain tumor biopsy or as an alternative in those patients who have a contraindication to undergo an invasive procedure.•The significance of magnetic resonance 3D volumetrics and qualitative imaging features for predicting MGMT methylation status in glioblastoma was evaluated (73.6% accuracy achieved).•Our analysis showed that the edema/necrosis volume ratio, tumor/necrosis volume ratio, edema volume, and tumor location and enhancement characteristics were associated with the status of MGMT promoter methylation in glioblastoma.•The results of our study provide further evidence of an association between standard preoperative MRI features and MGMT methylation status in glioblastoma. 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. 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. 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. The obtained results provide further evidence of an association between standard preoperative MRI variables and MGMT methylation status in GBM. 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.BACKGROUND AND OBJECTIVEThe 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.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.METHODSA 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.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.RESULTSThe 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.The obtained results provide further evidence of an association between standard preoperative MRI variables and MGMT methylation status in GBM.CONCLUSIONSThe obtained results provide further evidence of an association between standard preoperative MRI variables and MGMT methylation status in GBM. Highlights • A noninvasive and reliable surrogate method of determining MGMT status could serve to complement brain tumor biopsy or as an alternative in those patients who have a contraindication to undergo an invasive procedure. • The significance of magnetic resonance 3D volumetrics and qualitative imaging features for predicting MGMT methylation status in glioblastoma was evaluated (73.6% accuracy achieved). • Our analysis showed that the edema/necrosis volume ratio, tumor/necrosis volume ratio, edema volume, and tumor location and enhancement characteristics were associated with the status of MGMT promoter methylation in glioblastoma. • The results of our study provide further evidence of an association between standard preoperative MRI features and MGMT methylation status in glioblastoma. 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. |
| Author | Kanas, Vasileios G. Thomas, Ginu A. Megalooikonomou, Vasileios Zinn, Pascal O. Zacharaki, Evangelia I. Colen, Rivka R. |
| Author_xml | – sequence: 1 givenname: Vasileios G. surname: Kanas fullname: Kanas, Vasileios G. organization: Department of Electrical and Computer Engineering, University of Patras, Patras, Greece – sequence: 2 givenname: Evangelia I. surname: Zacharaki fullname: Zacharaki, Evangelia I. email: evangelia.zacharaki@centralesupelec.fr organization: Department of Computer Engineering and Informatics, University of Patras, Patras, Greece – sequence: 3 givenname: Ginu A. surname: Thomas fullname: Thomas, Ginu A. organization: Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA – sequence: 4 givenname: Pascal O. surname: Zinn fullname: Zinn, Pascal O. organization: Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA – sequence: 5 givenname: Vasileios surname: Megalooikonomou fullname: Megalooikonomou, Vasileios organization: Department of Computer Engineering and Informatics, University of Patras, Patras, Greece – sequence: 6 givenname: Rivka R. surname: Colen fullname: Colen, Rivka R. organization: Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA |
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| Keywords | Feature extraction MGMT promoter methylation Multivariate analysis Glioblastoma Prediction model glioblastoma prediction model feature extraction multivariate analysis |
| Language | English |
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| Snippet | •A noninvasive and reliable surrogate method of determining MGMT status could serve to complement brain tumor biopsy or as an alternative in those patients who... Highlights • A noninvasive and reliable surrogate method of determining MGMT status could serve to complement brain tumor biopsy or as an alternative in those... The O -methylguanine-DNA-methyltransferase (MGMT) promoter methylation has been shown to be associated with improved outcomes in patients with glioblastoma... The O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation has been shown to be associated with improved outcomes in patients with glioblastoma... Background and Objective: The O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation has been shown to be associated with improved outcomes in... |
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| SubjectTerms | Adolescent Adult Aged Aged, 80 and over Brain Neoplasms - diagnostic imaging Brain Neoplasms - genetics Computer Science DNA Methylation DNA Modification Methylases - genetics DNA Modification Methylases - metabolism DNA Repair Enzymes - genetics DNA Repair Enzymes - metabolism Feature extraction Female Glioblastoma Glioblastoma - diagnostic imaging Glioblastoma - genetics Humans Internal Medicine Machine Learning Magnetic Resonance Imaging Male Medical Imaging MGMT promoter methylation Middle Aged Multivariate analysis Other Prediction model Promoter Regions, Genetic Tumor Suppressor Proteins - genetics Tumor Suppressor Proteins - metabolism Young Adult |
| Title | Learning MRI-based classification models for MGMT methylation status prediction in glioblastoma |
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