The assessment of treatment response in glioblastoma is difficult with MRI because reactive blood–brain barrier alterations with contrast enhancement can mimic tumor progression. In this study, we investigated the predictive value of PET using O-(2-¹⁸F-fluoroethyl)-l-tyrosine (¹⁸F-FET PET) during treatment. Methods: In a prospective study, 25 patients with glioblastoma were investigated by MRI and ¹⁸F-FET PET after surgery (MRI-/FET-1), early (7–10 d) after completion of radiochemotherapy with temozolomide (RCX) (MRI-/FET-2), and 6–8 wk later (MRI-/FET-3). Maximum and mean tumor-to-brain ratios (TBR_max and TBR_mean, respectively) were determined by region-of-interest analyses. Furthermore, gadolinium contrast-enhancement volumes on MRI (Gd-volume) and tumor volumes in ¹⁸F-FET PET images with a tumor-to-brain ratio greater than 1.6 (T_{vol 1.6}) were calculated using threshold-based volume-of-interest analyses. The patients were grouped into responders and nonresponders according to the changes of these parameters at different cutoffs, and the influence on progression-free survival and overall survival was tested using univariate and multivariate survival analyses and by receiver-operating-characteristic analyses. Results: Early after completion of RCX, a decrease of both TBR_max and TBR_mean was a highly significant and independent statistical predictor for progression-free survival and overall survival. Receiver-operating-characteristic analysis showed that a decrease of the TBR_max between FET-1 and FET-2 of more than 20% predicted poor survival, with a sensitivity of 83% and a specificity of 67% (area under the curve, 0.75). Six to eight weeks later, the predictive value of TBR_max and TBR_mean was less significant, but an association between a decrease of T_{vol 1.6} and PFS was noted. In contrast, Gd-volume changes had no significant predictive value for survival. Conclusion: In contrast to Gd-volumes on MRI, changes in ¹⁸F-FET PET may be a valuable parameter to assess treatment response in glioblastoma and to predict survival time.

The aim of this study was to investigate the potential of O-(2-¹⁸F-fluoroethyl)-l-tyrosine (¹⁸F-FET) PET for differentiating local recurrent brain metastasis from radiation necrosis after radiation therapy because the use of contrast-enhanced MRI for this issue is often difficult. Methods: Thirty-one patients (mean age ± SD, 53 ± 11 y) with single or multiple contrast-enhancing brain lesions (n = 40) on MRI after radiation therapy of brain metastases were investigated with dynamic ¹⁸F-FET PET. Maximum and mean tumor-to-brain ratios (TBR_max and TBR_mean, respectively; 20–40 min after injection) of ¹⁸F-FET uptake were determined. Time–activity curves were generated, and the time to peak (TTP) was calculated. Furthermore, time–activity curves of each lesion were assigned to one of the following curve patterns: (I) constantly increasing ¹⁸F-FET uptake, (II) ¹⁸F-FET uptake peaking early (TTP ≤ 20 min) followed by a plateau, and (III) ¹⁸F-FET uptake peaking early (TTP ≤ 20 min) followed by a constant descent. The diagnostic accuracy of the TBR_max and TBR_mean of ¹⁸F-FET uptake and the curve patterns for the correct identification of recurrent brain metastasis were evaluated by receiver-operating-characteristic analyses or Fisher exact test for 2 × 2 contingency tables using subsequent histologic analysis (11 lesions in 11 patients) or clinical course and MRI findings (29 lesions in 20 patients) as reference. Results: Both TBR_max and TBR_mean were significantly higher in patients with recurrent metastasis (n = 19) than in patients with radiation necrosis (n = 21) (TBR_max, 3.2 ± 0.9 vs. 2.3 ± 0.5, P < 0.001; TBR_mean, 2.1 ± 0.4 vs. 1.8 ± 0.2, P < 0.001). The diagnostic accuracy of ¹⁸F-FET PET for the correct identification of recurrent brain metastases reached 78% using TBR_max (area under the ROC curve [AUC], 0.822 ± 0.07; sensitivity, 79%; specificity, 76%; cutoff, 2.55; P = 0.001), 83% using TBR_mean (AUC, 0.851 ± 0.07; sensitivity, 74%; specificity, 90%; cutoff, 1.95; P < 0.001), and 92% for curve patterns II and III versus curve pattern I (sensitivity, 84%; specificity, 100%; P < 0.0001). The highest accuracy (93%) to diagnose local recurrent metastasis was obtained when both a TBR_mean greater than 1.9 and curve pattern II or III were present (AUC, 0.959 ± 0.03; sensitivity, 95%; specificity, 91%; P < 0.001). Conclusion: Our findings suggest that the combined evaluation of the TBR_mean of ¹⁸F-FET uptake and the pattern of the time–activity curve can differentiate local brain metastasis recurrence from radionecrosis with high accuracy. ¹⁸F-FET PET may thus contribute significantly to the management of patients with brain metastases.

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 ± 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 (TBR_max/TBR_mean) 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 (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: ¹⁸F-FET uptake ratios provide valuable additional information for the differentiation of cerebral lesions and the grading of gliomas. TBR_max 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 (TBR_max < 2.5) excludes a high-grade tumor with high probability.