Imaging of Small Lung Nodules on Modern SAFOV and LAFOV PET in Combination With Data-driven Motion Correction: Implications for Current Practice.

Abstract

Guidelines recommend [ 18 F]FDG PET/CT for lung nodules >8 mm only. For smaller lesions, PET/CT has not been recommended due to lower lesion conspicuity. However, this threshold was established using earlier generations of PET scanners. In this work, we sought to evaluate the combined effects of modern scanner technology, long-axial-field-of-view (LAFOV) PET and data-driven respiratory motion correction on lung nodule imaging. We identified 55 consecutive patients with lung nodules who underwent [ 18 F]FDG PET/CT for a known or suspected malignancy. We created image reconstructions with combinations of simulated short-axial-field-of-view (sSAFOV), LAFOV, and data-driven gating (DDG) and measured effects on image parameters. We then gathered follow-up data (over 13 mo) to establish nodule benignity or malignancy and evaluated effects on diagnostic accuracy with receiver-operating-characteristic (ROC) analysis. All methods showed good to excellent diagnostic accuracy, even for nodules <6 mm, with AUCs consistently above 0.85. LAFOV reduced noise compared with sSAFOV, and adding DDG increased the median SUV max by 32%. The combination of LAFOV and DDG showed the highest image quality improvement compared with sSAFOV, with a median improvement in contrast-to-noise ratio (CNR) of 29%. Data-driven motion correction and LAFOV-PET provide synergistic improvements in image quality. Furthermore, the high diagnostic accuracy of sSAFOV reconstructions for lung nodules ≤8 mm, and even <6 mm, indicates that assessment of lung nodules smaller than current guideline recommendations might be possible.