@article {Rapp229, author = {Marion Rapp and Alexander Heinzel and Norbert Galldiks and Gabriele Stoffels and J{\"o}rg Felsberg and Christian Ewelt and Michael Sabel and Hans J. Steiger and Guido Reifenberger and Thomas Beez and Heinz H. Coenen and Frank W. Floeth and Karl-Josef Langen}, title = {Diagnostic Performance of 18F-FET PET in Newly Diagnosed Cerebral Lesions Suggestive of Glioma}, volume = {54}, number = {2}, pages = {229--235}, year = {2013}, doi = {10.2967/jnumed.112.109603}, publisher = {Society of Nuclear Medicine}, abstract = {The aim of this study was to assess the clinical value of O-(2-18F-fluoroethyl)-l-tyrosine (18F-FET) PET in the initial diagnosis of cerebral lesions suggestive of glioma. Methods: In a retrospective study, we analyzed the clinical, radiologic, and neuropathologic data of 174 patients (77 women and 97 men; mean age, 45 {\textpm} 15 y) who had been referred for neurosurgical assessment of unclear brain lesions and had undergone 18F-FET PET. Initial histology (n = 168, confirmed after surgery or biopsy) and the clinical course and follow-up MR imaging in 2 patients revealed 66 high-grade gliomas (HGG), 77 low-grade gliomas (LGG), 2 lymphomas, and 25 nonneoplastic lesions (NNL). In a further 4 patients, initial histology was unspecific, but during the course of the disease all patients developed an HGG. The diagnostic value of maximum and mean tumor-to-brain ratios (TBRmax/TBRmean) of 18F-FET uptake was assessed using receiver-operating-characteristic (ROC) curve analyses to differentiate between neoplastic lesions and NNL, between HGG and LGG, and between high-grade tumor (HGG or lymphoma) and LGG or NNL. Results: Neoplastic lesions showed significantly higher 18F-FET uptake than NNL (TBRmax, 3.0 {\textpm} 1.3 vs. 1.8 {\textpm} 0.5; P \< 0.001). ROC analysis yielded an optimal cutoff of 2.5 for TBRmax to differentiate between neoplastic lesions and NNLs (sensitivity, 57\%; specificity, 92\%; accuracy, 62\%; area under the curve [AUC], 0.76; 95\% confidence interval [CI], 0.68{\textendash}0.84). The positive predictive value (PPV) was 98\%, and the negative predictive value (NPV) was 27\%. ROC analysis for differentiation between HGG and LGG (TBRmax, 3.6 {\textpm} 1.4 vs. 2.4 {\textpm} 1.0; P \< 0.001) yielded an optimal cutoff of 2.5 for TBRmax (sensitivity, 80\%; specificity, 65\%; accuracy, 72\%; AUC, 0.77; PPV, 66\%; NPV, 79\%; 95\% CI, 0.68{\textendash}0.84). Best differentiation between high-grade tumors (HGG or lymphoma) and both NNL and LGG was achieved with a TBRmax cutoff of 2.5 (sensitivity, 79\%; specificity, 72\%; accuracy, 75\%; AUC, 0.79; PPV, 65\%; NPV, 84\%; 95\% CI, 0.71{\textendash}0.86). The results for TBRmean were similar with a cutoff of 1.9. Conclusion: 18F-FET uptake ratios provide valuable additional information for the differentiation of cerebral lesions and the grading of gliomas. TBRmax of 18F-FET uptake beyond the threshold of 2.5 has a high PPV for detection of a neoplastic lesion and supports the necessity of an invasive procedure, for example, biopsy or surgical resection. Low 18F-FET uptake (TBRmax \< 2.5) excludes a high-grade tumor with high probability.}, issn = {0161-5505}, URL = {https://jnm.snmjournals.org/content/54/2/229}, eprint = {https://jnm.snmjournals.org/content/54/2/229.full.pdf}, journal = {Journal of Nuclear Medicine} }