MRI texture features as biomarkers to predict MGMT methylation status in glioblastomas.
OBJECTIVE
Imaging biomarker research focuses on discovering relationships between radiological features and histological findings. In glioblastoma patients, methylation of the O(6)-methylguanine methyltransferase (MGMT) gene promoter is positively correlated with an increased effectiveness of current standard of care. In this paper, the authors investigate texture features as potential imaging biomarkers for capturing the MGMT methylation status of glioblastoma multiforme (GBM) tumors when combined with supervised classification schemes.


METHODS
A retrospective study of 155 GBM patients with known MGMT methylation status was conducted. Co-occurrence and run length texture features were calculated, and both support vector machines (SVMs) and random forest classifiers were used to predict MGMT methylation status.


RESULTS
The best classification system (an SVM-based classifier) had a maximum area under the receiver-operating characteristic (ROC) curve of 0.85 (95% CI: 0.78-0.91) using four texture features (correlation, energy, entropy, and local intensity) originating from the T2-weighted images, yielding at the optimal threshold of the ROC curve, a sensitivity of 0.803 and a specificity of 0.813.


CONCLUSIONS
Results show that supervised machine learning of MRI texture features can predict MGMT methylation status in preoperative GBM tumors, thus providing a new noninvasive imaging biomarker.
Department of Radiology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905.
Panagiotis
P
Korfiatis
Department of Radiology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905.
Timothy L
TL
Kline
Department of Radiology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905; Department of Neurosurgery of First Faculty of Medicine, Charles University in Prague, Military University Hospital, Prague 128 21, Czech Republic; and International Clinical Research Center, St. Anne's University Hospital Brno, Brno 656 91, Czech Republic.
Lucie
L
Coufalova
Department of Neurology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905.
Daniel H
DH
Lachance
Department of Neurologic Surgery, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905.
Ian F
IF
Parney
Department of Health Sciences Research, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905.
Rickey E
RE
Carter
Department of Medical Oncology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905.
Jan C
JC
Buckner
Department of Radiology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905.
Bradley J
BJ
Erickson
D014408:Biomarkers, Tumor / Q000235:genetics; D001921:Brain / Q000000981:diagnostic imaging* / Q000601:surgery; D001932:Brain Neoplasms / Q000000981:diagnostic imaging* / Q000235:genetics / Q000601:surgery; D019175:DNA Methylation; D015254:DNA Modification Methylases / Q000235:genetics*; D045643:DNA Repair Enzymes / Q000235:genetics*; D005909:Glioblastoma / Q000000981:diagnostic imaging* / Q000235:genetics / Q000601:surgery; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D011401:Promoter Regions, Genetic; D012372:ROC Curve; D012189:Retrospective Studies; D060388:Support Vector Machine; D025521:Tumor Suppressor Proteins / Q000235:genetics*
D014408:Biomarkers, Tumor; D025521:Tumor Suppressor Proteins; D015254:DNA Modification Methylases; C515491:MGMT protein, human; D045643:DNA Repair Enzymes