Evaluation of data-driven respiratory gating in continuous bed motion in lung lesions

Abstract

Objectives: Respiratory gating is used in positron emission tomography (PET) to prevent image quality degradation due to respiratory effects. In this study, we evaluated a data-driven respiratory gating for continuous bed motion OncoFreeze AI, which was implemented to improve image quality and accuracy of semiquantitative uptake values affected by respiratory motion. Methods: ¹⁸F-fluoro-deoxyglucose PET/ computed tomography was performed on 32 patients with lung lesions. Two types of respiratory gating images (OncoFreeze AI with data-driven respiratory gating, device-based amplitude-based OncoFreeze with elastic motion compensation) and ungated images (Static) were reconstructed. For each image, we calculated standardized uptake value (SUV) and metabolic tumor volume (MTV). The improvement rate (IR) from respiratory gating and the contrast-to-noise ratio (CNR), which indicates the improvement in image noise, were also calculated for these indices. IR was also calculated for the upper and lower lobes of the lung. As OncoFreeze AI assumes the presence of respiratory motion, we examined quantitativity in regions where respiratory motion was not present using a ⁶⁸Ge cylinder phantom with known quantitativity. Results: OncoFreeze and OncoFreeze AI showed similar values, with a significant increase in SUV and decrease in MTV compared to Static. OncoFreeze and OncoFreeze AI also showed similar values for IR and CNR. OncoFreeze AI increased SUV_max by an average of 18% and decreased MTV by an average of 25% compared to Static. From the IR results, both OncoFreeze and OncoFreeze AI showed a greater improvement rate from Static in the lower lobe than in the upper lobe. OncoFreeze and OncoFreeze AI increased CNR by 17.9% and 18.0%, respectively, compared to Static. The quantitativity of the ⁶⁸Ge phantom, assuming a region of no respiratory motion, was almost equal for the Static and OncoFreeze AI. Conclusion: OncoFreeze AI improved the influence of respiratory motion in the assessment of lung lesion accumulation to a comparable level to the previously launched OncoFreeze. OncoFreeze AI provides more accurate imaging with significantly larger SUV values and smaller MTV than Static.