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Abstract #3863

MRSI-based characterization of GBM using a novel map: Expected Distance to Tumor (EDT)

Nuno Pedrosa de Barros1, Raphael Meier2, Samuel Stettler1, Urspeter Knecht1, Evelyn Herrmann3, Philippe Schucht4, Mauricio Reyes2, Jan Gralla1, Roland Wiest1, and Johannes Slotboom1

1Institute for Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland, 2Institute for Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland, 3Institute of Radiooncology, University of Bern, Bern, Switzerland, 4Neurosurgery, University of Bern, Bern, Switzerland

MRSI can detect regions of brain tumor infiltration beyond the tumor borders visible in structural-MRI (sMRI). However, this is often achieved using only a small fraction of the information provided by MRSI, namely Cho/NAA maps only. Here, we present a new machine-learning-based approach that translates the multidimensional information provided by each spectrum into a single measure: the Expected Distance to solid Tumor volume visible in sMRI. The results show that peritumoral spectra carry information on the distance to solid tumor and that EDT maps may improve the characterization of peritumoral tissue changes invisible with structural MRI.

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