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- 2018 (1) (entfernen)
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- Preprint (Vorabdruck) (1) (entfernen)
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- Englisch (1)
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- [177Lu]-DOTATATE/-DOTATOC (1) (entfernen)
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- 701983 (1)
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 (<6.7, OS=1.9y, 14/31). These findings were supported in a G2 subanalysis (>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.