title: Clinical respiratory motion correction software (reconstruct, register and averaged-RRA), for18F-FDG-PET-CT: phantom validation, practical implications and patient evaluation.
abstract: OBJECTIVE
  On fluorine-18 fludeoxyglucose (18F-FDG) positron emission tomography (PET) CT of pulmonary or hepatic lesions, standard uptake value (SUV) is often underestimated due to patient breathing. The aim of this study is to validate, on phantom and patient data, a motion correction algorithm [reconstruct, register and averaged (RRA)] implemented on a PET-CT system.
  
  
  METHODS
  Three phantoms containing five spheres filled with18F-FDG and suspended in a water or Styrofoam®18F-FDG-filled tank to create different contrasts and attenuation environment were acquired on a Discovery GE710. The spheres were animated with a 2-cm longitudinal respiratory-based movement. Respiratory-gated (RRA) and ungated PET images were compared with static reference images (without movement). The optimal acquisition time, number of phases and the best phase within the respiratory cycle were investigated. The impact of irregular motion was also investigated. Quantification impact was computed on each sphere. Quantification improvement on 28 lung lesions was also investigated.
  
  
  RESULTS
  Phantoms: 4 min was required to obtain a stable quantification with the RRA method. The reference phase and the number of phases used for RRA did not affect the quantification which was similar on static acquisitions but different on ungated images. The results showed that the maximum standard uptake value (SUVmax) restoration is majored for the smallest spheres (≤2.1 ml).
  
  
  METHODS
  SUVmaxon RRA and ungated acquisitions were statistically different to the SUVmaxon whole-body images (p = 0.05) but not different from each other (mean SUVmax: 7.0 ± 7.8 vs 6.9 ± 7.8, p = 0.23 on RRA and ungated images, respectively). We observed a statistically significant correlation between SUV restoration and lesion displacement, with a real SUV quantitation improvement for lesion with movement >1.2 mm.
  
  
  CONCLUSIONS
  According to the results obtained using phantoms, RRA method is promising, showing a real impact on the lesion quantification on phantom data. With regard to the patient study, our results showed a trend towards an increase in the SUVs and a decrease in the volume between the ungated and RRA data. We also noticed a statistically significant correlation between the quantitative restoration obtained with RRA compared with ungated data and lesion displacement, indicating that the RRA approach should be reserved to patients with small lesions or nodes moving with a displacement larger than 1.2 cm. Advances in knowledge: This article investigates the performances of motion correction software recently introduced in PET. The conclusion revealed that such respiratory motion correction approach shows a real impact on the lesion quantification but must be reserved to the patient for whom lesion displacement was confirmed and high enough to clearly impact lesion evaluation.
authors.affiliation: 1 Nuclear Department, Becquerel Center, Rouen University Hospital, France.
authors.forename: Anne-Charlotte
authors.initials: AC
authors.lastname: Bouyeure-Petit
authors.affiliation: 1 Nuclear Department, Becquerel Center, Rouen University Hospital, France.
authors.forename: Mathieu
authors.initials: M
authors.lastname: Chastan
authors.affiliation: 1 Nuclear Department, Becquerel Center, Rouen University Hospital, France.
authors.forename: Agathe
authors.initials: A
authors.lastname: Edet-Sanson
authors.affiliation: 1 Nuclear Department, Becquerel Center, Rouen University Hospital, France.|2 QuantIF-LITIS EA4108, Rouen University, France.
authors.forename: Stephanie
authors.initials: S
authors.lastname: Becker
authors.affiliation: 1 Nuclear Department, Becquerel Center, Rouen University Hospital, France.|2 QuantIF-LITIS EA4108, Rouen University, France.
authors.forename: Sebastien
authors.initials: S
authors.lastname: Thureau
authors.affiliation: 3 Biostatistics Department, Rouen University Hospital, France.
authors.forename: Estelle
authors.initials: E
authors.lastname: Houivet
authors.affiliation: 1 Nuclear Department, Becquerel Center, Rouen University Hospital, France.|2 QuantIF-LITIS EA4108, Rouen University, France.
authors.forename: Pierre
authors.initials: P
authors.lastname: Vera
authors.affiliation: 1 Nuclear Department, Becquerel Center, Rouen University Hospital, France.|2 QuantIF-LITIS EA4108, Rouen University, France.
authors.forename: Sebastien
authors.initials: S
authors.lastname: Hapdey
mesh_terms: D000465:Algorithms; D019788:Fluorodeoxyglucose F18; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008168:Lung / Q000000981:diagnostic imaging; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D009038:Motion; D019047:Phantoms, Imaging; D000072078:Positron Emission Tomography Computed Tomography / Q000379:methods*; D019275:Radiopharmaceuticals; D012119:Respiration
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18