Optimal respiratory-gated [18F]FDG PET/CT significantly impacts the quantification of metabolic parameters and their correlation with overall survival in patients with pancreatic ductal adenocarcinoma

Abstract

Purpose: Metabolic parameters are increasingly being used to characterize tumors. Motion artifacts due to patient respiration introduce uncertainties in quantification of metabolic parameters during positron emission tomography (PET) image acquisition. The present study investigates the impact of amplitude-based optimal respiratory gating (ORG) on quantification of PET-derived image features in patients with pancreatic ductal adenocarcinoma (PDAC), in correlation with overall survival (OS). Methods: Sixty-nine patients with histologically proven primary PDAC underwent 2′-deoxy-2′-[18F]fluoroglucose ([18F]FDG) PET/CT imaging during diagnostic work-up. Standard image acquisition and reconstruction was performed in accordance with the EANM guidelines and ORG images were reconstructed with a duty cycle of 35%. PET-derived image features, including standard parameters, first- and second-order texture features, were calculated from the standard and corresponding ORG images, and correlation with OS was assessed. Results: ORG significantly impacts the quantification of nearly all features; values of single-voxel parameters (e.g., SUVmax) showed a wider range, volume-based parameters (e.g., SUVmean) were reduced, and texture features were significantly changed. After correction for motion artifacts using ORG, some features that describe intra-tumoral heterogeneity were more strongly correlated to OS. Conclusions: Correction for respiratory motion artifacts using ORG impacts the quantification of metabolic parameters in PDAC lesions. The correlation of metabolic parameters with OS was significantly affected, in particular parameters that describe intra-tumor heterogeneity. Therefore, interpretation of single-voxel or average metabolic parameters in relation to clinical outcome should be done cautiously. Furthermore, ORG is a valuable tool to improve quantification of intra-tumoral heterogeneity in PDAC.