MR-based hypoxia measures in human glioma
Abstract
Hypoxia plays a central role in tumor stem cell genesis and is related to a more malignant tumor phenotype, therapy resistance (e.g. in anti-angiogenic therapies) and radio-insensitivity. Reliable hypoxia imaging would provide crucial metabolic information in the diagnostic work-up of brain tumors. In this study, we applied a novel BOLD-based MRI method for the measurement of relative oxygen extraction fraction (rOEF) in glioma patients and investigated potential benefits and drawbacks. Forty-five glioma patients were examined preoperatively in a pilot study on a 3T MR scanner. rOEF was calculated from quantitative transverse relaxation rates (T2, T2*) and cerebral blood volume (CBV) using a quantitative BOLD approach. rOEF maps were assessed visually and by means of a volume of interest (VOI) analysis. In six cases, MRI-targeted biopsy samples were analyzed using HIF-1α-immunohistochemistry. rOEF maps could be obtained with a diagnostic quality. Focal spots with high rOEF values were observed in the majority of high-grade tumors but in none of the low-grade tumors. VOI analysis revealed potentially hypoxic tumor regions with high rOEF in contrast-enhancing tumor regions as well as in the non-enhancing infiltration zone. Systematic bias was found as a result of non-BOLD susceptibility effects (T2*) and contrast agent leakage affecting CBV. Histological samples demonstrated reasonable correspondence between MRI characteristics and HIF-1α-staining. The presented method of rOEF imaging is a promising tool for the metabolic characterization of human glioma. For the interpretation of rOEF maps, confounding factors must be considered, with a special focus on CBV measurements in the presence of contrast agent leakage. Further validation involving a bigger cohort and extended immuno-histochemical correlation is required.
Keywords
Hypoxia Glioma MRI Multimodal imaging T2′ rOEF HIF-1αNotes
Acknowledgments
We thank Ralf Deichmann for providing the template of source code for the correction of background gradients and motion in T2* mapping. This work was supported by the Deutsche Forschungsgemeinschaft (SFB 824: “Imaging for the selection, monitoring and individualization of cancer therapies,” Project B6). The data have been presented in parts at the annual meetings of the DGNR, Köln, Germany, October 2011 and at the annual meeting of the ASNR, New York, USA, April 2012.
Conflict of interest
The authors report no conflict of interest concerning the materials or methods used in this study or the findings described in this paper. No benefits in any form have been or will be received from any commercial party related directly or indirectly to the subject of this manuscript.
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