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Purpose: Metabolic activity and hypoxia are both important factors characterizing tumor aggressiveness. Here, we used F-18 fluoromisonidazole (FMISO) and F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) to define metabolically active hypoxic volume, and investigate its clinical significance in relation to progression free survival (PFS) and overall survival (OS) in glioblastoma patients. Experimental Design: Glioblastoma patients ( n = 32) underwent FMISO PET, FDG PET, and magnetic resonance imaging (MRI) before surgical intervention. FDG and FMISO PET images were coregistered with gadolinium-enhanced T1-weighted MR images. Volume of interest (VOI) of gross tumor volume (GTV) was manually created to enclose the entire gadolinium-positive areas. The FMISO tumor-to-normal region ratio (TNR) and FDG TNR were calculated in a voxel-by-voxel manner. For calculating TNR, standardized uptake value (SUV) was divided by averaged SUV of normal references. Contralateral frontal and parietal cortices were used as the reference region for FDG, whereas the cerebellar cortex was used as the reference region for FMISO. FDG-positive was defined as the FDG TNR ≥1.0, and FMISO-positive was defined as FMISO TNR ≥1.3. Hypoxia volume (HV) was defined as the volume of FMISO-positive and metabolic tumor volume in hypoxia (hMTV) was the volume of FMISO/FDG double-positive. The total lesion glycolysis in hypoxia (hTLG) was hMTV × FDG SUVmean. The extent of resection (EOR) involving cytoreduction surgery was volumetric change based on planimetry methods using MRI. These factors were tested for correlation with patient prognosis. Results: All tumor lesions were FMISO-positive and FDG-positive. Univariate analysis indicated that hMTV, hTLG, and EOR were significantly correlated with PFS ( p = 0.007, p = 0.04, and p = 0.01, respectively) and that hMTV, hTLG, and EOR were also significantly correlated with OS ( p = 0.0028, p = 0.037, and p = 0.014, respectively). In contrast, none of FDG TNR, FMISO TNR, GTV, HV, patients' age, or Karnofsky performance scale (KPS) was significantly correlated with PSF or OS. The hMTV and hTLG were found to be independent factors affecting PFS and OS on multivariate analysis. Conclusions: We introduced hMTV and hTLG using FDG and FMISO PET to define metabolically active hypoxic volume. Univariate and multivariate analyses demonstrated that both hMTV and hTLG are significant predictors for PFS and OS in glioblastoma patients. [ABSTRACT FROM AUTHOR]

Purpose: Glioblastoma multiforme (GBM) is the most aggressive primary brain tumor and its prognosis is significantly poorer than those of less malignant gliomas. Pathologically, necrosis is one of the most important characteristics that differentiate GBM from lower grade gliomas; therefore, we hypothesized that F fluoromisonidazole (FMISO), a radiotracer for hypoxia imaging, accumulates in GBM but not in lower grade gliomas. We aimed to evaluate the diagnostic value of FMISO positron emission tomography (PET) for the differential diagnosis of GBM from lower grade gliomas. Methods: This prospective study included 23 patients with pathologically confirmed gliomas. All of the patients underwent FMISO PET and F-fluorodeoxyglucose (FDG) PET within a week. FMISO images were acquired 4 h after intravenous administration of 400 MBq of FMISO. Tracer uptake in the tumor was visually assessed. Lesion to normal tissue ratios and FMISO uptake volume were calculated. Results: Of the 23 glioma patients, 14 were diagnosed as having GBM (grade IV glioma in the 2007 WHO classification), and the others were diagnosed as having non-GBM (5 grade III and 4 grade II). In visual assessment, all GBM patients showed FMISO uptake in the tumor greater than that in the surrounding brain tissues, whereas all the non-GBM patients showed FMISO uptake in the tumor equal to that in the surrounding brain tissues ( p ≤ 0.001). One GBM patient was excluded from FDG PET study because of hyperglycemia. All GBM patients and three of the nine (33%) non-GBM patients showed FDG uptake greater than or equal to that in the gray matter. The sensitivity and specificity for diagnosing GBM were 100 and 100% for FMISO, and 100 and 66% for FDG, respectively. The lesion to cerebellum ratio of FMISO uptake was higher in GBM patients (2.74 ± 0.60, range 1.71-3.81) than in non-GBM patients (1.22 ± 0.06, range 1.09-1.29, p ≤ 0.001) with no overlap between the groups. The lesion to gray matter ratio of FDG was also higher in GBM patients (1.46 ± 0.75, range 0.91-3.79) than in non-GBM patients (1.07 ± 0.62, range 0.66-2.95, p ≤ 0.05); however, overlap of the ranges did not allow clear differentiation between GBM and non-GBM. The uptake volume of FMISO was larger in GBM (27.18 ± 10.46%, range 14.02-46.67%) than in non-GBM (6.07 ± 2.50%, range 2.12-9.22%, p ≤ 0.001). Conclusion: These preliminary data suggest that FMISO PET may distinguish GBM from lower grade gliomas. [ABSTRACT FROM AUTHOR]