Abstract #1520

A Deep Neural Network for Detection of Glioblastomas in Spectroscopic MRI

Erin Beate Bjørkeli^1,2, Jonn Terje Geitung^1,2, and Morteza Esmaeili^1,3

¹Department of Diagnostic Imaging, Akershus University Hospital, Oslo, Norway, ²Institue of Clinical Medicine, University of Oslo, Oslo, Norway, ³Department of Electrical Engineering and Computer Science, University of Stavanger, Stavanger, Norway

Synopsis

We have developed a MRSI spectra classifying convolutional neural network (CNN), building on the AUTOMAP model for image and spectra reconstruction. The model was trained to discern between non-water-suppressed spectra from healthy subjects and glioblastoma (GBM) patients. The trained CNN was able to classify the spectra correctly and seemed to recognize the healthy spectra based on the NAA-peak and the GBM based on the choline levels and possibly 2HG, indicating an IDH mutation.

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