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International Journal of Radiation Oncology Biology Physics 2008-Jun

Electron paramagnetic resonance oxygen image hypoxic fraction plus radiation dose strongly correlates with tumor cure in FSa fibrosarcomas.

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Martyna Elas
Rebecca Bell
Danielle Hleihel
Eugene D Barth
Colin McFaul
Chad R Haney
Joanna Bielanska
Katarzyna Pustelny
Kang-Hyun Ahn
Charles A Pelizzari

Mots clés

Abstrait

OBJECTIVE

Tumor hypoxia has long been known to produce resistance to radiation. In this study, electron paramagnetic resonance (EPR) oxygen imaging was investigated for its power to predict the success of tumor control according to tumor oxygenation level and radiation dose.

METHODS

A total of 34 EPR oxygen images were obtained from the legs of C3H mice bearing 0.5-cm(3) FSa fibrosarcomas under both normal (air breathing) and clamped tumor conditions. Under the same conditions as those during which the images were obtained, the tumors were irradiated to a variety of doses near the FSa dose at which 50% of tumors were cured. Tumor tissue was distinguished from normal tissue using co-registration of the EPR oxygen images with spin-echo magnetic resonance imaging of the tumor and/or stereotactic localization. The tumor voxel statistics in the EPR oxygen image included the mean and median partial pressure of oxygen and the fraction of tumor voxels below the specified partial pressure of oxygen values of 3, 6, and 10 mm Hg. Bivariate logistic regression analysis using the radiation dose and each of the EPR oxygen image statistics to determine which best separated treatment failure from success.

RESULTS

The measurements of the dose at which 50% of tumors were cured were similar to those found in published data for this syngeneic tumor. Bivariate analysis of 34 tumors demonstrated that tumor cure correlated with dose (p = 0.004) and with a <10 mm Hg hypoxic fraction (p = 0.023).

CONCLUSIONS

Our results have shown that, together, radiation dose and EPR image hypoxic fraction separate the population of FSa fibrosarcomas that are cured from those that fail, thus predicting curability.

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