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Radiomics signature: A potential biomarker for the prediction of MGMT promoter methylation in glioblastoma.

Authors :
Xi YB
Guo F
Xu ZL
Li C
Wei W
Tian P
Liu TT
Liu L
Chen G
Ye J
Cheng G
Cui LB
Zhang HJ
Qin W
Yin H
Source :
Journal of magnetic resonance imaging : JMRI [J Magn Reson Imaging] 2018 May; Vol. 47 (5), pp. 1380-1387. Date of Electronic Publication: 2017 Sep 19.
Publication Year :
2018

Abstract

Background: In glioblastoma (GBM), promoter methylation of the DNA repair gene O-methylguanine-DNA methyltransferase (MGMT) is associated with beneficial chemotherapy.<br />Purpose/hypothesis: To analyze radiomics features for utilizing the full potential of medical imaging as biomarkers of MGMT promoter methylation.<br />Study Type: Retrospective.<br />Population/subjects: In all, 98 GBM patients with known MGMT (48 methylated and 50 unmethylated tumors).<br />Field Strength/sequence: 3.0T magnetic resonance (MR) images, containing T <subscript>1</subscript> -weighted image (T <subscript>1</subscript> WI), T <subscript>2</subscript> -weighted image (T <subscript>2</subscript> WI), and enhanced T <subscript>1</subscript> WI.<br />Assessment: A region of interest (ROI) of the tumor was delineated. A total of 1665 radiomics features were extracted and quantized, and were reduced using least absolute shrinkage and selection operator (LASSO) regularization.<br />Statistical Testing: After the support vector machine construction, accuracy, sensitivity, and specificity were computed for different sequences. An independent validation cohort containing 20 GBM patients was utilized to further evaluate the radiomics model performance.<br />Results: Radiomics features of T <subscript>1</subscript> WI reached an accuracy of 67.54%. Enhanced T <subscript>1</subscript> WI features reached an accuracy of 82.01%, while T <subscript>2</subscript> WI reached an accuracy of 69.25%. The best classification system for predicting MGMT promoter methylation status originated from the combination of 36 T <subscript>1</subscript> WI, T <subscript>2</subscript> WI, and enhanced T <subscript>1</subscript> WI images features, with an accuracy of 86.59%. Further validation on the independent cohort of 20 patients produced similar results, with an accuracy of 80%.<br />Data Conclusion: Our results provide further evidence that radiomics MR features could predict MGMT methylation status in preoperative GBM. Multiple imaging modalities together can yield putative noninvasive biomarkers for the identification of MGMT.<br />Level of Evidence: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1380-1387.<br /> (© 2017 International Society for Magnetic Resonance in Medicine.)

Details

Language :
English
ISSN :
1522-2586
Volume :
47
Issue :
5
Database :
MEDLINE
Journal :
Journal of magnetic resonance imaging : JMRI
Publication Type :
Academic Journal
Accession number :
28926163
Full Text :
https://doi.org/10.1002/jmri.25860