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Abstract #0502

Early Detection of Tumor Apoptotic Response to Oncolytic Virotherapy using Deep CEST MR Fingerprinting

Or Perlman1, Hirotaka Ito2, Kai Herz3,4, Hiroshi Nakashima2, Moritz Zaiss3,5, E. Antonio Chiocca2, Christopher Nguyen1, Ouri Cohen6, Matthew S. Rosen1,7, and Christian T. Farrar1
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States, 2Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, United States, 3Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 4IMPRS for Cognitive and Systems Neuroscience, University of Tübingen, Tübingen, Germany, 5Department of Neuroradiology, University Clinic Erlangen, Erlangen, Germany, 6Memorial Sloan Kettering Cancer Center, New York, NY, United States, 7Department of Physics, Harvard University, Cambridge, MA, United States

Oncolytic virotherapy (OV) is a promising treatment for high mortality cancers. To optimize the clinical outcome, non-invasive monitoring is essential. The goal of this work was to develop a deep-learning-based technique for quantitative and rapid molecular imaging of OV treatment response. Two CEST MR-fingerprinting protocols were sequentially implemented (105s each) and incorporated within a deep-reconstruction-network, trained to output the quantitative semi-solid and amide pool exchange parameters. The resulting molecular maps allowed early apoptosis detection in brain tumor OV mouse models. Clinical translation of CEST-MRF is demonstrated in a normal human subject and yielded parameters in good agreement with literature values.

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