Amplitude-based Optimal Respiratory Gating in Positron Emission Tomography in Patients with Primary Lung Cancer
Overview
Authors
Affiliations
Objectives: Respiratory motion during PET imaging introduces quantitative and diagnostic inaccuracies, which may result in non-optimal patient management. This study investigated the effects of respiratory gating on image quantification using an amplitude-based optimal respiratory gating (ORG) algorithm.
Methods: Whole body FDG-PET/CT was performed in 66 lung cancer patients. The respiratory signal was obtained using a pressure sensor integrated in an elastic belt placed around the patient's thorax. ORG images were reconstructed with 50%, 35%, and 20% of acquired PET data (duty cycle). Lesions were grouped into anatomical locations. Differences in lesion volume between ORG and non-gated images, and mean FDG-uptake (SUVmean) were calculated.
Results: Lesions in the middle and lower lobes demonstrated a significant SUVmean increase for all duty cycles and volume decrease for duty cycles of 35% and 20%. Significant increase in SUVmean and decrease in volume for lesions in the upper lobes were observed for a 20% duty cycle. The SUVmean increase for central lesions was significant for all duty cycles, whereas a significant volume decrease was observed for a duty cycle of 20%.
Conclusions: This study implies that ORG could influence clinical PET imaging with respect to response monitoring and radiotherapy planning.
Key Points: Quantifying lesion volume and uptake in PET is important for patient management. Respiratory motion artefacts introduce inaccuracies in quantification of PET images. Amplitude-based optimal respiratory gating maintains image quality through selection of duty cycle. The effect of respiratory gating on lesion quantification depends on anatomical location.
Data-driven gating (DDG)-based motion match for improved CTAC registration.
Cook E, Su K, Higgins G, Johnsen R, Bouhnik J, McGowan D EJNMMI Phys. 2024; 11(1):42.
PMID: 38691232 PMC: 11554991. DOI: 10.1186/s40658-024-00644-0.
Faist D, Jreige M, Oreiller V, Nicod Lalonde M, Schaefer N, Depeursinge A Eur J Hybrid Imaging. 2022; 6(1):33.
PMID: 36309636 PMC: 9617997. DOI: 10.1186/s41824-022-00153-2.
Cheung A, Wu V, Cheung A, Cai J Front Oncol. 2022; 12:789506.
PMID: 35223472 PMC: 8864173. DOI: 10.3389/fonc.2022.789506.
Influences on PET Quantification and Interpretation.
Rogasch J, Hofheinz F, van Heek L, Voltin C, Boellaard R, Kobe C Diagnostics (Basel). 2022; 12(2).
PMID: 35204542 PMC: 8871060. DOI: 10.3390/diagnostics12020451.
Evaluating two respiratory correction methods for abdominal PET/MRI imaging.
Ruan W, Liu F, Sun X, Hu F, Wu T, Zhang Y EJNMMI Phys. 2022; 9(1):5.
PMID: 35099646 PMC: 8804027. DOI: 10.1186/s40658-022-00430-w.