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Abstract #1114

Mean-Shift Clustering for Assessing Response Heterogeneity in Bone Metastases

Sarah Ann Mason 1 , Nina Tunariu 1 , Dow-Mu Koh 1 , David J Collins 1 , Martin O Leach 1 , and Matthew D Blackledge 1

1 Institute of Cancer Research and Royal Marsden Hospital, Sutton, Surrey, United Kingdom

No single MR sequence can fully represent the underlying biology in bone metastases, which necessitates that clinicians employ complementary image data for disease diagnoses, response assessments, and treatment decisions. The sheer volume of data can make image interpretation complex and overwhelming. We introduce a method for consolidating information by identifying like regions in the bone (e.g. active disease) based on a mean-shift analysis of fat fraction (FF), apparent diffusion coefficient (ADC), and spatial location. This non-parametric method provides superb data visualization, makes no assumptions about the underlying data distributions, and can track changes in the region of interest over time.

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