Comparison of 13N-NH 3, 11C-MET and 18F-FDG PET/CT imaging in the diagnosis and evaluation of cerebral glioma
10.3760/cma.j.cn321828-20190724-00141
- VernacularTitle:13N－NH 3、 11C－MET及 18F－FDG PET/CT显像在脑胶质瘤诊断与评估中的对比研究
- Author:
Yali LONG
1
;
Qiao HE
;
Bing ZHANG
;
Xinchong SHI
;
Chang YI
;
Xiangsong ZHANG
Author Information
1. 中山大学附属第一医院核医学科，广州 510080
- From:
Chinese Journal of Nuclear Medicine and Molecular Imaging
2020;40(3):159-165
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To compare the application of 13N-NH 3, 11C-methionine (MET) and 18F-fluorodeoxyglucose (FDG) PET/CT imaging in the diagnosis and evaluation of suspected cerebral glioma. Methods:From September 2010 to December 2017, ninety patients (54 males, 36 females; age: (40.0±14.0) years) in the First Affiliated Hospital of Sun Yat-sen University with suspected glioma based on clinical diagnosis, who underwent 13N-NH 3, 11C-MET and 18F-FDG PET/CT imaging, were prospectively enrolled in the study. All patients were confirmed by histology or clinical and radiological follow-up. Images were interpreted by visual evaluation (higher radioactive uptake in lesions than that in the contralateral normal brain parenchyma was considered as positive (+ ), equal/lower were considered as negative (-)) and semi-quantitative analysis (the maximum standardized uptake value (SUV) of lesion (L) to the mean SUV of normal white matter (WM) (L/WM ratio)). Receiver operating characteristic (ROC) curve analysis was used and the area under curves (AUCs) were calculated and compared. The diagnostic efficacies of 3 imaging methods and the combination for diagnosing gliomas and the abilities to differentiating high-grade gliomas (HGG) and low-grade gliomas (LGG) were compared. Results:In 90 patients, 30 HGG, 27 LGG, 10 non-glioma brain tumors and 23 non-neoplastic lesions (NNL) were diagnosed. On visual evaluation, the sensitivities for differentiating tumors from NNL were 62.7%(42/67), 94.0%(63/67) and 35.8% (24/67) for 13N-NH 3, 11C-MET and 18F-FDG PET/CT respectively, while the specificities were 95.7%(22/23), 56.5% (13/23) and 65.2% (15/23), and the accuracies were 71.1%(64/90), 84.4%(76/90) and 43.3% (39/90). Taking the metabolic patterns of + /+ /+ , + /+ /- and + /-/- ( 11C-MET/ 13N-NH 3/ 18F-FDG) as the diagnosis standard of tumor lesions, the specificity and accuracy of the combined method increased to 73.9%(17/23) and 88.9%(80/90) with the sensitivity remaining the same (94.0%, 63/67). ROC curve analysis (L/WM) showed that the sensitivity, specificity and AUC were 64.2%(43/67), 100%(23/23) and 0.819 for 13N-NH 3 PET/CT, and 89.6%(60/67), 69.6%(16/23) and 0.840 for 11C-MET PET/CT ( z=-0.316, P>0.05). The accuracy for differentiating high and low grade glioma were 86.0% (49/57), 87.7%(50/57) and 93.0%(53/57) for 13N-NH 3, 11C-MET and 18F-FDG PET/CT, with the AUC of 0.896, 0.928 and 0.964, respectively ( z values: -0.554 to 1.334, all P>0.05). Conclusions:13N-NH 3 PET/CT imaging has remarkably high specificity but low sensitivity for the differentiation of brain tumors from NNL. 11C-MET PET/CT imaging was found to be highly useful for detection of brain tumors. However, like 18F-FDG, high MET uptake is frequently observed in some NNL. 13N-NH 3, 11C-MET and 18F-FDG PET/CT imaging all appear to be valuable for evaluating the histological grade of gliomas, and the combination of them is more useful for the accurate diagnosis of glioma.
