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Abstract #2585

Quantifying confidence in the OE-MRI biomarker pOxy-R using bootstrap analysis

Ross A Little1, Geoff JM Parker2,3, and James PB O'Connor1
1Division of Cancer Sciences, University of Manchester, Manchester, United Kingdom, 2Centre for Medical Image Computing, University College London, London, United Kingdom, 3Bioxydyn Limited, Manchester, United Kingdom


OE-MRI is an emerging technique for identifying, mapping and quantifying tumour hypoxia. Current analysis is based on combining data with a perfusion map and categorising each voxel absolutely as hypoxic, normoxic or necrotic. In this study we use bootstrap analysis to map the uncertainty on the biomarker pOxy-R. We investigate how this performs in synthetic tumour data before applying the method to data from 9 patients with rectal cancer undergoing chemoradiotherapy. Bootstrapping enabled estimates of confidence intervals for change, thus identifying those patients who exhibited hypoxia modification on therapy.

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