Abstract #1516
Differentiation of IDH and TERTp mutations in Glioma Using Dynamic Susceptibility Contrast MRI with Machine Learning at 3T
Buse Buz-Yalug1, Ayca Ersen Danyeli2,3, Cengiz Yakicier3,4, Necmettin Pamir3,5, Alp Dincer3,6, Koray Ozduman3,7, and Esin Ozturk-Isik1
1Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkey, 2Department of Medical Pathology, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey, 3Center for Neuroradiological Applications and Reseach, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey, 4Department of Molecular Biology and Genetics, Istanbul, Turkey, 5Department of Neurosurgery, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey, 6Department of Radiology, Acıbadem Mehmet Ali Aydinlar University, Istanbul, Turkey, 7Department of Neurosurgery, Acıbadem Mehmet Ali Aydinlar University, Istanbul, Turkey
Synopsis
Isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase promoter (TERTp) mutations highly affect the clinical outcome in gliomas. The aim of this study was to identify IDH and TERTp mutations in glioma patients using machine learning approaches on relative cerebral blood volume (rCBV) maps obtained from dynamic susceptibility contrast MRI (DSC-MRI). The highest classification accuracy was 87.2% (sensitivity = 85.7%, specificity = 88.9%) for the IDH subgroup, 81.8% accuracy (sensitivity = 77.5%, specificity = 86.4%) was obtained for classifying the TERTp subgroup. Additionally, a classification accuracy of 89.6% (sensitivity = 88.3%, specificity = 91.2%) was obtained for identifying the TERTp-only gliomas.
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