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Abstract #1391

Characterising and correcting for MR signal drift in dynamic SPGR oxygen-enhanced MRI acquisitions

Adam K Featherstone1,2, James P B O'Connor2,3,4, Geoff J M Parker1,2,5, and Julian C Matthews1,2

1Division of Informatics, Imaging and Data Sciences, The University of Manchester, Manchester, United Kingdom, 2CRUK & EPSRC Cancer Imaging Centre in Cambridge and Manchester, Cambridge and Manchester, United Kingdom, 3Division of Molecular and Clinical Cancer Studies, The University of Manchester, Manchester, United Kingdom, 4Department of Radiology, The Christie NHS Foundation Trust, Manchester, United Kingdom, 5Bioxydyn Ltd., Manchester, United Kingdom

Dynamic oxygen-enhanced (OE)-MRI, in combination with dynamic contrast-enhanced (DCE)-MRI, shows use in identifying hypoxic regions in tumours, but relies on an accurate knowledge of baseline (pre contrast-agent administration) tissue characteristics. We present a method of characterising baseline signal drift in an oxygen-enhanced MRI study of preclinical tumour xenografts, where the drift would otherwise impede quantitative analyses. We then demonstrate the utility and necessity of our methods through a comparison of calculated ∆R1 values (reflecting tissue oxygen delivery) with and without our baseline drift correction.

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