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Purpose: Tumor necrosis is one of the indicators of tumor aggressiveness. F-fluoromisonidazole (FMISO) is the most widely used positron emission tomography (PET) tracer to evaluate severe hypoxia in vivo. Because severe hypoxia causes necrosis, we hypothesized that intratumoral necrosis can be detected by FMISO PET in brain tumors regardless of their histopathology. We applied FMISO PET to various types of brain tumors before tumor resection and evaluated the correlation between histopathological necrosis and FMISO uptake. Methods: This study included 59 brain tumor patients who underwent FMISO PET/computed tomography before any treatments. According to the pathological diagnosis, the brain tumors were divided into three groups: astrocytomas (group 1), neuroepithelial tumors except for astrocytomas (group 2), and others (group 3). Two experienced neuropathologists evaluated the presence of necrosis in consensus. FMISO uptake in the tumor was evaluated visually and semi-quantitatively using the tumor-to-normal cerebellum ratio (TNR). Results: In visual analyses, 26/27 cases in the FMISO-positive group presented with necrosis, whereas 28/32 cases in the FMISO-negative group did not show necrosis. Mean TNRs with and without necrosis were 3.49 ± 0.97 and 1.43 ± 0.42 ( p < 0.00001) in group 1, 2.91 ± 0.83 and 1.44 ± 0.20 ( p < 0.005) in group 2, and 2.63 ± 1.16 and 1.35 ± 0.23 ( p < 0.05) in group 3, respectively. Using a cut-off value of TNR = 1.67, which was calculated by normal reference regions of interest, we could predict necrosis with sensitivity, specificity, and accuracy of 96.7, 93.1, and 94.9 %, respectively. Conclusions: FMISO uptake within the lesion indicated the presence of histological micro-necrosis. When we used a TNR of 1.67 as the cut-off value, intratumoral micro-necrosis was sufficiently predictable. Because the presence of necrosis implies a poor prognosis, our results suggest that FMISO PET could provide important information for treatment decisions or surgical strategies of any type of brain tumor. [ABSTRACT FROM AUTHOR]

Purpose: C-methionine (MET) PET is an established diagnostic tool for glioma. Studies have suggested that MET uptake intensity in the tumor is a useful index for predicting patient outcome. Because MET uptake is known to reflect tumor expansion more accurately than MRI, we aimed to elucidate the association between volume-based tumor measurements and patient prognosis. Methods: The study population comprised 52 patients with newly diagnosed glioma who underwent PET scanning 20 min after injection of 370 MBq MET. The tumor was contoured using a threshold of 1.3 times the activity of the contralateral normal cortex. Metabolic tumor volume (MTV) was defined as the total volume within the boundary. Total lesion methionine uptake (TLMU) was defined as MTV times the mean standardized uptake value (SUVmean) within the boundary. The tumor-to-normal ratio (TNR), calculated as the maximum standardized uptake value (SUVmax) divided by the contralateral reference value, was also recorded. All patients underwent surgery (biopsy or tumor resection) targeting the tissue with high MET uptake. The Kaplan-Meier method was used to estimate the predictive value of each measurement. Results: Grade II tumor was diagnosed in 12 patients (3 diffuse astrocytoma, 2 oligodendroglioma, and 7 oligoastrocytoma), grade III in 18 patients (8 anaplastic astrocytoma, 6 anaplastic oligodendroglioma, and 4 anaplastic oligoastrocytoma), and grade IV in 22 patients (all glioblastoma). TNR, MTV and TLMU were 3.1 ± 1.2, 51.6 ± 49.9 ml and 147.7 ± 153.3 ml, respectively. None of the three measurements was able to categorize the glioma patients in terms of survival when all patients were analyzed. However, when only patients with astrocytic tumor ( N = 33) were analyzed (i.e., when those with oligodendroglial components were excluded), MTV and TLMU successfully predicted patient outcome with higher values associated with a poorer prognosis ( P < 0.05 and P < 0.01, respectively), while the predictive ability of TNR did not reach statistical significance ( P = NS). Conclusion: MTV and TLMU may be useful for predicting outcome in patients with astrocytic tumor. [ABSTRACT FROM AUTHOR]