Textural features in pre-treatment [F18]-FDG-PET/CT are correlated with risk of local recurrence and disease-specific survival in early stage NSCLC patients receiving primary stereotactic radiation therapy

BACKGROUND: 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). METHODS: 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. RESULTS: 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) 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. CONCLUSIONS: 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

Survival prediction in patients undergoing radionuclide therapy based on intratumoral somatostatin-receptor heterogeneity

The NETTER-1 trial demonstrated significantly improved progression-free survival (PFS) for peptide receptor radionuclide therapy (PRRT) in neuroendocrine tumors (NET) emphasizing the high demand for response prediction in appropriate candidates. In this multicenter study, we aimed to elucidate the prognostic value of tumor heterogeneity as assessed by somatostatin receptor (SSTR)-PET/CT. 141 patients with SSTR-expressing tumors were analyzed obtaining SSTR-PET/CT before PRRT (1-6 cycles, (177)Lu somatostatin analog). Using the Interview Fusion Workstation (Mediso), a total of 872 metastases were manually segmented. Conventional PET parameters as well as textural features representing intratumoral heterogeneity were computed. The prognostic ability for PFS and overall survival (OS) were examined. After performing Cox regression, independent parameters were determined by ROC analysis to obtain cut-off values to be used for Kaplan-Meier analysis. Within follow-up (median, 43.1 months), 75 patients showed disease progression (median, 22.2 m) and 54 patients died (median, 27.6 m). Cox analysis identified 8 statistically independent heterogeneity parameters for time-to-progression and time-to-death. Among them, the textural feature Entropy predicted both PFS and OS. Conventional PET parameters failed in response prediction. Imaging-based heterogeneity assessment provides prognostic information in PRRT candidates and outperformed conventional PET parameters. Its implementation in clinical practice can pave the way for individualized patient management

Volumetric and Texture Analysis of Pretherapeutic 18^{18}F-FDG PET can Predict Overall Survival in Medullary Thyroid Cancer Patients Treated with Vandetanib

Purpose: The metabolically most active lesion in 2-deoxy-2-($^{18}$F)fluoro-D-glucose ($^{18}$F-FDG) PET/CT can predict progression-free survival (PFS) in patients with medullary thyroid carcinoma (MTC) starting treatment with the tyrosine kinase inhibitor (TKI) vandetanib. However, this metric failed in overall survival (OS) prediction. In the present proof of concept study, we aimed to explore the prognostic value of intratumoral textural features (TF) as well as volumetric parameters (total lesion glycolysis, TLG) derived by pre-therapeutic $^{18}$F-FDG PET. Methods: Eighteen patients with progressive MTC underwent baseline $^{18}$F-FDG PET/CT prior to and 3 months after vandetanib initiation. By manual segmentation of the tumor burden at baseline and follow-up PET, intratumoral TF and TLG were computed. The ability of TLG, imaging-based TF, and clinical parameters (including age, tumor marker doubling times, prior therapies and RET (rearranged during transfection) mutational status) for prediction of both PFS and OS were evaluated. Results: The TF Complexity and the volumetric parameter TLG obtained at baseline prior to TKI initiation successfully differentiated between low- and high-risk patients. Complexity allocated 10/18 patients to the high-risk group with an OS of 3.3y (vs. low-risk group, OS=5.3y, 8/18, AUC=0.78, P=0.03). Baseline TLG designated 11/18 patients to the high-risk group (OS=3.5y vs. low-risk group, OS=5y, 7/18, AUC=0.83, P=0.005). The Hazard Ratio for cancer-related death was 6.1 for Complexity (TLG, 9.5). Among investigated clinical parameters, the age at initiation of TKI treatment reached significance for PFS prediction (P=0.02, OS, n.s.). Conclusions: The TF Complexity and the volumetric parameter TLG are both independent parameters for OS prediction

Pre-therapy Somatostatin-Receptor-Based Heterogeneity Predicts Overall Survival in Pancreatic Neuroendocrine Tumor Patients Undergoing Peptide Receptor Radionuclide Therapy

Purpose: Early identification of aggressive disease could improve decision-support in pancreatic neuroendocrine tumor (pNET) patients prior to peptide receptor radionuclide therapy (PRRT). The prognostic value of intratumoral textural features (TF) determined by baseline somatostatin receptor (SSTR)-PET before PRRT was analyzed. Procedures: 31 patients with G1/G2 pNET were enrolled (G2, n=23/31). Prior to PRRT with [$^{177}$Lu]DOTATATE (mean, 3.6 cycles), baseline SSTR-PET/CT was performed. By segmentation of 162 (median per patient, 5) metastases, intratumoral TF were computed. The impact of conventional PET parameters (SUV$_{mean/max}$), imaging-based TF as well as clinical parameters (Ki67, CgA) for prediction of both progression-free (PFS) and overall survival (OS) after PRRT was evaluated. Results: Within a median follow-up of 3.7y, tumor progression was detected in 21 patients (median, 1.5y) and 13/31 deceased (median, 1.9y). In ROC analysis, the TF Entropy, reflecting derangement on a voxel-by-voxel level, demonstrated predictive capability for OS (cutoff=6.7, AUC=0.71, p=0.02). Of note, increasing Entropy could predict a longer survival (>6.7, OS=2.5y, 17/31), whereas less voxel-based derangement portended inferior outcome (6.9, OS=2.8y, 9/23 vs. <6.9, OS=1.9y, 14/23). Kaplan-Meier analysis revealed a significant distinction between high- and low-risk groups using Entropy (n=31, p<0.05). For those patients below the ROC-derived threshold, the relative risk of death after PRRT was 2.73 (n=31, p=0.04). Ki67 was negatively associated with PFS (p=0.002); however, SUVmean/max failed in prognostication (n.s.). Conclusions: In contrast to conventional PET parameters, assessment of intratumoral heterogeneity demonstrated superior prognostic performance in pNET patients undergoing PRRT. This novel PET-based strategy of outcome prediction prior to PRRT might be useful for patient risk stratification