There is a need to develop tumour hypoxia biomarkers for patient stratification and for tracking tumour response to therapy. We apply our preclinically-optimised, data-driven segmentation of combined OE-MRI/DCE-MRI data to a cohort of non small-cell lung cancer (NSCLC) patients, aiming to map tumour hypoxia non-invasively. Tissue classes with different oxygenation and perfusion characteristics are located, and we discuss challenges specific to use in the clinical setting. Further optimisation of the technique is needed to improve its repeatability and its ability to enable the identification of definitively hypoxic regions in these types of data.
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