Comparison of the effectiveness of MRI perfusion and fluorine-18 FDG PET-CT for differentiating radiation injury from viable brain tumor: a preliminary retrospective analysis with pathologic correlation in all patients

Objectives: Differentiating radiation injury from viable tumor is important for optimizing patient care. Our aim was to directly compare the effectiveness of fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography computed tomography (PET-CT) and dynamic susceptibility-weighted contrast-enhanced (DSC) magnetic resonance (MR) perfusion in differentiating radiation effects from tumor growth in patients with increased enhancement following radiotherapy for primary or secondary brain tumors. Materials and methods: We retrospectively identified 12 consecutive patients with primary and secondary brain tumors over a 1-year period that demonstrated indeterminate enhancing lesions after radiotherapy and that had undergone DSC MR perfusion, FDG PET-CT, and subsequent histopathologic diagnosis. The maximum standardized uptake value (SUV) of the lesion (SUVlesion (max)), SUVratio (SUVlesion (max)/SUVnormal (brain)), maximum relative cerebral blood volume, percentage of signal intensity recovery, and relative peak height were calculated from the positron emission tomography and MR perfusion studies. A prediction of tumor or radiation injury was made based on these variables while being blinded to the results of the surgical pathology. Results: SUVratio had the highest predictive value (area under the curve=0.943) for tumor progression, although this was not statistically better than any MR perfusion metric (area under the curve=0.757-0.829). Conclusions: This preliminary study suggests that FDG PET-CT and DSC MR perfusion may demonstrate similar effectiveness for distinguishing tumor growth from radiation injury. Assessment of the SUVratio may increase the sensitivity and specificity of FDG PET-CT for differentiating tumor and radiation injury. Further analysis is needed to help define which modality has greater predictive capabilities. (C) 2013 Elsevier Inc. All rights reserved.