title: The impact of respiratory motion on tumor quantification and delineation in static PET/CT imaging.
abstract: Our aim is to investigate the impact of respiratory motion on tumor quantification and delineation in static PET/CT imaging using a population of patient respiratory traces. A total of 1295 respiratory traces acquired during whole body PET/CT imaging were classified into three types according to the qualitative shape of their signal histograms. Each trace was scaled to three diaphragm motion amplitudes (6 mm, 11 mm and 16 mm) to drive a whole body PET/CT computer simulation that was validated with a physical phantom experiment. Three lung lesions and one liver lesion were simulated with diameters of 1 cm and 2 cm. PET data were reconstructed using the OS-EM algorithm with attenuation correction using CT images at the end-expiration phase and respiratory-averaged CT. The errors of the lesion maximum standardized uptake values (SUV(max)) and lesion volumes between motion-free and motion-blurred PET/CT images were measured and analyzed. For respiration with 11 mm diaphragm motion and larger quiescent period fraction, respiratory motion can cause a mean lesion SUV(max) underestimation of 28% and a mean lesion volume overestimation of 130% in PET/CT images with 1 cm lesions. The errors of lesion SUV(max) and volume are larger for patient traces with larger motion amplitudes. Smaller lesions are more sensitive to respiratory motion than larger lesions for the same motion amplitude. Patient respiratory traces with relatively larger quiescent period fraction yield results less subject to respiratory motion than traces with long-term amplitude variability. Mismatched attenuation correction due to respiratory motion can cause SUV(max) overestimation for lesions in the lower lung region close to the liver dome. Using respiratory-averaged CT for attenuation correction yields smaller mismatch errors than those using end-expiration CT. Respiratory motion can have a significant impact on static oncological PET/CT imaging where SUV and/or volume measurements are important. The impact is highly dependent upon motion amplitude, lesion location and size, attenuation map and respiratory pattern. To overcome the motion effect, motion compensation techniques may be necessary in clinical practice to improve the tumor quantification for determining the response to therapy or for radiation treatment planning.
authors.affiliation: Department of Radiology, University of Washington, Seattle, WA, USA. cliu2@u.washington.edu
authors.forename: Chi
authors.initials: C
authors.lastname: Liu
authors.forename: Larry A
authors.initials: LA
authors.lastname: Pierce
authors.forename: Adam M
authors.initials: AM
authors.lastname: Alessio
authors.forename: Paul E
authors.initials: PE
authors.lastname: Kinahan
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003964:Diaphragm / Q000503:physiopathology; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008297:Male; D008954:Models, Biological; D009068:Movement; D009369:Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000503:physiopathology*; D019047:Phantoms, Imaging; D049268:Positron-Emission Tomography; D015203:Reproducibility of Results; D012119:Respiration; D014057:Tomography, X-Ray Computed; D047368:Tumor Burden