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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