Abstract #0502

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

Or Perlman¹, Hirotaka Ito², Kai Herz^3,4, Hiroshi Nakashima², Moritz Zaiss^3,5, E. Antonio Chiocca², Christopher Nguyen¹, Ouri Cohen⁶, Matthew S. Rosen^1,7, 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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