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024 7 _ |a 10.1016/j.ejmp.2020.01.012
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024 7 _ |a pmid:32006939
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024 7 _ |a 1120-1797
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024 7 _ |a 1724-191X
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037 _ _ |a DKFZ-2020-00307
041 _ _ |a eng
082 _ _ |a 610
100 1 _ |a Paredes-Cisneros, Isabela
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245 _ _ |a Simulation of hypoxia PET-tracer uptake in tumours: Dependence of clinical uptake-values on transport parameters and arterial input function.
260 _ _ |a Amsterdam
|c 2020
|b Elsevier
336 7 _ |a article
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520 _ _ |a Poor radiotherapy outcome is in many cases related to hypoxia, due to the increased radioresistance of hypoxic tumour cells. Positron emission tomography may be used to non-invasively assess the oxygenation status of the tumour using hypoxia-specific radiotracers. Quantification and interpretation of these images remains challenging, since radiotracer binding and oxygen tension are not uniquely related. Computer simulation is a useful tool to improve the understanding of tracer dynamics and its relation to clinical uptake parameters currently used to quantify hypoxia. In this study, a model for simulating oxygen and radiotracer distribution in tumours was implemented to analyse the impact of physiological transport parameters and of the arterial input function (AIF) on: oxygenation histograms, time-activity curves, tracer binding and clinical uptake-values (tissue-to-blood ratio, TBR, and a composed hypoxia-perfusion metric, FHP). Results were obtained for parallel and orthogonal vessel architectures and for vascular fractions (VFs) of 1% and 3%. The most sensitive parameters were the AIF and the maximum binding rate (Kmax). TBR allowed discriminating VF for different AIF, and FHP for different Kmax, but neither TBR nor FHP were unbiased in all cases. Biases may especially occur in the comparison of TBR- or FHP-values between different tumours, where the relation between measured and actual AIF may vary. Thus, these parameters represent only surrogates rather than absolute measurements of hypoxia in tumours.
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700 1 _ |a Karger, Christian P
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700 1 _ |a Caprile, Paola
|b 2
700 1 _ |a Nolte, David
|b 3
700 1 _ |a Espinoza, Ignacio
|b 4
700 1 _ |a Gago-Arias, Araceli
|b 5
773 _ _ |a 10.1016/j.ejmp.2020.01.012
|g Vol. 70, p. 109 - 117
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|t Physica medica
|v 70
|y 2020
|x 1120-1797
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910 1 _ |a Deutsches Krebsforschungszentrum
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