Textural features in FDG-PET have been shown to provide prognostic information in a variety of tumor entities. Here we evaluate their predictive value for recurrence and prognosis in NSCLC patients receiving primary stereotactic radiation therapy (SBRT). 45 patients with early stage NSCLC (T1 or T2 tumor, no lymph node or distant metastases) were included in this retrospective study and followed over a median of 21.4 months (range 3.1–71.1). All patients were considered non-operable due to concomitant disease and referred to SBRT as the primary treatment modality. Pre-treatment FDG-PET/CT scans were obtained from all patients. SUV and volume-based analysis as well as extraction of textural features based on neighborhood gray-tone difference matrices (NGTDM) and gray-level co-occurence matrices (GLCM) were performed using InterView Fusion™ (Mediso Inc., Budapest). The ability to predict local recurrence (LR), lymph node (LN) and distant metastases (DM) was measured using the receiver operating characteristic (ROC). Univariate and multivariate analysis of overall and disease-specific survival were executed. 7 out of 45 patients (16%) experienced LR, 11 (24%) LN and 11 (24%) DM. ROC revealed a significant correlation of several textural parameters with LR with an AUC value for entropy of 0.872. While there was also a significant correlation of LR with tumor size in the overall cohort, only texture was predictive when examining T1 (tumor diameter < = 3 cm) and T2 (>3 cm) subgroups. No correlation of the examined PET parameters with LN or DM was shown. In univariate survival analysis, both heterogeneity and tumor size were predictive for disease-specific survival, but only texture determined by entropy was determined as an independent factor in multivariate analysis (hazard ratio 7.48, p = .016). Overall survival was not significantly correlated to any examined parameter, most likely due to the high comorbidity in our cohort. Our study adds to the growing evidence that tumor heterogeneity as described by FDG-PET texture is associated with response to radiation therapy in NSCLC. The results may be helpful into identifying patients who might profit from an intensified treatment regime, but need to be verified in a prospective patient cohort before being incorporated into routine clinical practice.

In prostate cancer (PC) patients, the differentiation between lung metastases and lesions of different origin, for example, primary lung cancer, is a common clinical question. Herein, we investigated the use of Glu-NH-CO-NH-Lys(Ahx)-HBED-CC (⁶⁸Ga-PSMA-HBED-CC) for this purpose. Methods: PC patients (n = 1,889) undergoing ⁶⁸Ga-PSMA PET/CT or PET/MR scans were evaluated retrospectively for suggestive lung lesions. For up to 5 lesions per patient, location, CT diameter, CT morphology, and SUV_max were determined. The standard for classification was either histopathologic evaluation or, in the case of PC metastases, responsivity to antihormone therapy. A comparison of the different classes was executed by Student t test. Prostate-specific antigen and prostate-specific membrane antigen (PSMA) immunohistochemistry were performed if histologic samples were available; ⁶⁸Ga-PSMA autoradiography was performed on an exemplary case of PET-positive lung cancer. Results: Eighty-nine lesions in 45 patients were identified, of which 76 were classified as PC (39 proven, 37 highly probable), 7 as primary lung cancer, and 2 as activated tuberculosis; 4 lesions remained unclear. The mean SUV_max was 4.4 ± 3.9 for PC metastases and 5.6 ± 1.6 for primary lung cancer (P = 0.408). Additionally, substantial differences in SUV_max intraindividually were detected. The 2 tuberculous lesions showed an SUV_max of 7.8 and 2.5. Using immunohistochemistry, we could demonstrate PSMA expression in the neovasculature of several PSMA PET-positive lung cancers as well as in tuberculous lesions from our histologic database. Conclusion: Quantitative (SUV) analysis of ⁶⁸Ga-PSMA PET was not able to discriminate reliably between pulmonary metastases and primary lung cancer in PC patients. The reason for the unexpectedly high tracer uptake in non-PC lesions is not completely clear. PSMA expression in neovasculature provides a possible explanation for this finding; however, other contributing factors, such as tracer binding to proteins other than PSMA, cannot be excluded at present.

BACKGROUND AND PURPOSE: Inter- and intratumor heterogeneity and the variable course of disease in patients with glioma motivate the investigation of new prognostic factors to optimize individual treatment. Here we explore the usefulness of standard static and more sophisticated dynamic ¹⁸F-fluoroethyltyrosine-PET imaging for the assessment of patient prognosis. MATERIALS AND METHODS: Thirty-four consecutive patients with untreated, first-diagnosed, histologically proved glioma were included in this retrospective study. All patients underwent dynamic PET scans before surgery (± standard treatment) and were followed up clinically and by MR imaging. Static and dynamic tumor-to-background ratio, TTP, and slope-to-peak were obtained and correlated with progression-free survival. RESULTS: Twenty of 34 patients experienced progression, with a median progression-free survival of 28.0 ± 11.1 months. Dynamic TTP was highly prognostic for recurrent disease, showing a strong correlation with progression-free survival (hazard ratio, 6.050; 95% CI, 2.11–17.37; P < .001). Most interesting, this correlation also proved significant in the subgroup of low-grade glioma (hazard ratio, 5.347; 95% CI, 1.05–27.20; P = .044), but not when using established static imaging parameters, such as maximum tumor-to-background ratio and mean tumor-to-background ratio. In the high-grade glioma subgroup, both dynamic and static parameters correlated with progression-free survival. The best results were achieved by defining ROIs around “hot spots” in earlier timeframes, underlining the concept of intratumor heterogeneity. CONCLUSIONS: ¹⁸F-fluoroethyltyrosine-PET can predict recurrence in patients with glioma, with dynamic analysis showing advantages over static imaging, especially in the low-grade subgroup.