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Correcting PET Images of Hypoxia for Tissue Transport Properties

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E Taylor

E Taylor1*, J Gottwald2 , I Yeung3 , H Keller4 , M Milosevic5 , D Hedley6 , N Dhani7 , I Siddiqui8 , D Jaffray9 , (1) Princess Margaret Cancer Center, Toronto, Ontario, (2) University of Toronto, Toronto, Ontario, (3) The Princess Margaret Cancer Centre - UHN, Toronto, ON, (4) The Princess Margaret Cancer Centre - UHN, Toronto, ON, (5) Princess Margaret Hospital, Toronto, ON, (6) Princess Margaret Cancer Centre, Toronto, Ontario, (7) Princess Margaret Cancer Centre, Toronto, Ontario, (8) Hospital for Sick Children, Toronto, Ontario, (9) University Health Network, Toronto, ON


SU-E-708-1 (Sunday, July 30, 2017) 1:00 PM - 1:55 PM Room: 708

Purpose: Compared to FDG, the binding rate of hypoxia-sensitive tracers such as fluoro-azomycinarabinoside (FAZA) is small, meaning that tracer uptake is sensitive to the presence of hypoxia as well as the transport properties (perfusion, diffusive transit time) of the imaged tissue. In order to accurately quantify hypoxia in solid tumours, PET images should be corrected for these.

Methods: Dynamic PET time-activity curves were analyzed using a novel compartmental model in twenty patients with pancreatic ductal adenocarcinoma. A key transport quantity—the nonequilibrium partition coefficient—describing the voxel-scale ratio of unbound tracer concentrations in tissue and blood at short times after injection was identified in this model and used to interpret dynamic and static PET uptake metrics. Hypoxia was quantified by the fraction of voxels in which the FAZA binding rate exceeded a threshold value.

Results: Partitioning diminished the ability of static PET imaging to accurately quantify hypoxia: the tumour-to-blood uptake ratio (T/B) of FAZA after two hours was poorly correlated with the tracer trapping rate. Applying a theory-based partition correction, strong correlations were found. Hypoxic fractions calculated from the tracer binding rate agreed with those calculated from static imaging (T/B > 1.2) when partitioning was small; otherwise, differences were significant. Partitioning was well-correlated with hypo-dense features on non-contrast CT images, suggesting a physiological origin.

Conclusion: Partitioning confounds simple attempts to quantify hypoxia in pancreatic tumours. We have proposed a novel way to correct for partitioning using dynamic PET imaging. The correlation between partitioning and static CT suggests that a combined static PET/CT biomarker may suffice to accomplish this in future.

Funding Support, Disclosures, and Conflict of Interest: Terry Fox Research Institute

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