Abstract #4801

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

Elham Karami^1,2,3, Wilfred Lam², Wendy Oakden², Margaret Koletar², Leedan Murray², Stanley Liu^1,4,5,6, Ali Sadeghi Naini^1,2,3,6, and Greg Stanisz^1,2,7

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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