• Daliang Liu, Guang Cheng, Xiaowei Ma, Shuailiang Wang, Xiaohu Zhao, Wei Zhang, Weidong Yang, and Jing Wang.
• Department of Nuclear Medicine, The first affiliated Hospital of Fourth Military Medical University, Xi'an, Shannxi Province, China.
• J Neuroimaging. 2021 Jul 1; 31 (4): 733-742.

Background And PurposeTo compare and characterize metabolic features of high- and low-grade glioma tumors using 68 Ga-PSMA-617 and 18 F-FDG positron emission tomography/computed tomography (PET/CT).MethodsThirty patients who underwent both 68 Ga-PSMA-617 and 18 F-FDG PET/CT over 2 consecutive days and then underwent surgical treatment were retrospectively identified. All tumors were diagnosed histologically. This report includes 16 high-grade glioma (HGG) and 14 low-grade glioma (LGG) tumors. Standard uptake value (SUV) and target to nontarget (T/NT) were quantitatively investigated through the entire tumor region. Statistical analyses were performed using area under the curve (AUC) and comparison of two means.ResultsSUVmax and SUVmean were the most effective (AUC, 0.96 and 0.94 for PSMA PET; AUC, 0.79 and 0.74 for FDG PET, respectively) for differentiating HGGs from LGGs. These methods distinguished between HGG and LGG effectively (PSMA PET: SUVmax , 5.766 ± 3.945 vs. 0.7364 ± 0.5295, p < 0.0001; SUVmean , 1.666 ± 1.680 and 0.1514 ± 0.1534, p < 0.0001, respectively) (FDG PET: SUVmax , 11.67 ± 3.639 and 9.118 ± 6.612; SUVmean , 5.648 ± 2.114 and 4.435 ± 2.872; p = 0.0083, 0.0262, respectively). The Youden index for SUVmax and SUVmean of 68 Ga-PSMA-617 and 18 F-FDG were 0.82 and 0.79 and 0.54 and 0.61, separately. T/NTmax was helpful for visual inspection of 68 Ga-PSMA-617-PET images (T/NTmax : 1.291 ± 0.9553 in grade II, 5.25 ± 2.435 in grade III, and 13.61 ± 13.84 in grade IV). T/NTmax differed significantly between LGG and HGG and between subtypes of LGG.ConclusionPET/CT with 68 Ga-PSMA-617 and 18 F-FDG may help distinguish between HGG and LGG, and 68 Ga-PSMA-617 PET/CT is superior to18 F-FDG in differentiating HGG and LGG.© 2021 American Society of Neuroimaging.

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