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Abstract #4801

Segmentation of Intra-Tumour Distinct Metabolic Regions Using Chemical Exchange Saturation Transfer Imaging

Elham Karami1,2,3, Wilfred Lam2, Wendy Oakden2, Margaret Koletar2, Leedan Murray2, Stanley Liu1,4,5,6, Ali Sadeghi Naini1,2,3,6, and Greg Stanisz1,2,7

1Medical Biophysics, University of Toronto, Toronto, ON, Canada, 2Physical Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada, 3Electrical and Computer Engineering, Lassonde School of Engineering, York University, Toronto, ON, Canada, 4Radiation Oncology, University of Toronto, Toronto, ON, Canada, 5Biological Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada, 6Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada, 7Neurosurgery and Paediatric Neurosurgery, Medical University of Lublin, Lublin, Poland

Chemical exchange saturation transfer (CEST) is a promising MR contrast mechanism that has been shown to correlate with cancer metabolism and reveal regions of active tumour metabolism. However, the acquisition of CEST-weighted images is time consuming. In this study, computational methods including unsupervised learning were adapted to find the minimum number of CEST images required to segment the intra-tumour distinct metabolic regions accurately, and to find the number of different cell groups existing within a tumour. The results indicate that four intra-tumour regions can be segmented accurately using only CEST images acquired at 3.5 ppm and 2.0 ppm.

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