Diagnostic Performance of 18F-FET PET in Newly Diagnosed Cerebral Lesions Suggestive of Glioma
| Autor: | Michael Sabel, Hans Jakob Steiger, Frank W. Floeth, Alexander Heinzel, Heinz H. Coenen, Jörg Felsberg, Thomas Beez, Marion Rapp, Christian Ewelt, Norbert Galldiks, Guido Reifenberger, Gabriele Stoffels, Karl-Josef Langen |
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| Rok vydání: | 2012 |
| Předmět: | |
| Zdroj: | Journal of Nuclear Medicine. 54:229-235 |
| ISSN: | 2159-662X 0161-5505 |
| DOI: | 10.2967/jnumed.112.109603 |
| Popis: | UNLABELLED The aim of this study was to assess the clinical value of O-(2-(18)F-fluoroethyl)-l-tyrosine ((18)F-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 ± 15 y) who had been referred for neurosurgical assessment of unclear brain lesions and had undergone (18)F-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 (TBR(max/)TBR(mean)) of (18)F-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 (18)F-FET uptake than NNL (TBR(max), 3.0 ± 1.3 vs. 1.8 ± 0.5; P < 0.001). ROC analysis yielded an optimal cutoff of 2.5 for TBR(max) to differentiate between neoplastic lesions and NNLs (sensitivity, 57%; specificity, 92%; accuracy, 62%; area under the curve [AUC], 0.76; 95% confidence interval [CI], 0.68-0.84). The positive predictive value (PPV) was 98%, and the negative predictive value (NPV) was 27%. ROC analysis for differentiation between HGG and LGG (TBR(max), 3.6 ± 1.4 vs. 2.4 ± 1.0; P < 0.001) yielded an optimal cutoff of 2.5 for TBR(max) (sensitivity, 80%; specificity, 65%; accuracy, 72%; AUC, 0.77; PPV, 66%; NPV, 79%; 95% CI, 0.68-0.84). Best differentiation between high-grade tumors (HGG or lymphoma) and both NNL and LGG was achieved with a TBR(max) cutoff of 2.5 (sensitivity, 79%; specificity, 72%; accuracy, 75%; AUC, 0.79; PPV, 65%; NPV, 84%; 95% CI, 0.71-0.86). The results for TBR(mean) were similar with a cutoff of 1.9. CONCLUSION (18)F-FET uptake ratios provide valuable additional information for the differentiation of cerebral lesions and the grading of gliomas. TBR(max) of (18)F-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 (18)F-FET uptake (TBR(max) < 2.5) excludes a high-grade tumor with high probability. |
| Databáze: | OpenAIRE |
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