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Abstract #1075

Identification of IDH and TERT Mutation Status in Glioma Patients using Dynamic Susceptibility Contrast MRI

Buse Buz Yalug1, Ayca Ersen Danyeli2,3, Cengiz Yakicier3,4, M. Necmettin Pamir3,5, Koray Ozduman3,5, Alp Dincer3,6, and Esin Ozturk-Isik1,3
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, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey, 5Department of Neurosurgery, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey, 6Department of Radiology, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

The main purpose of this study was to identify isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase (TERT) promoter mutations in glioma patients using classical machine learning and convolutional neural networks (CNN) on dynamic susceptibility contrast MRI (DSC-MRI). Relative cerebral blood volume (rCBV) maps of glioma patients with different genotypes including IDH-mutant, IDH-wildtype, TERT-mutant, and TERT-wildtype were compared in tumor areas. Classical machine learning classification results were over 85% for both IDH and TERT mutations. On the other hand, CNNs were able to classify IDH mutation status with 83% and TERT mutation status with 72% accuracies.

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Abstract