title: Effect of tomographic operator inaccuracies and respiratory motion on PET/CT lung nodule images smearing.
abstract: BACKGROUND
  In thoracic PET/computed tomography (CT) imaging, uptake foci usually appear smeared because of postreconstruction smoothing and respiratory motion.
  
  
  OBJECTIVE
  The aim of the present study was to assess the respective contributions of the reconstruction process and respiratory motion on PET/CT images.
  
  
  METHODS
  Thirty-one pulmonary lesions were studied. Free-breathing PET/CT acquisitions were followed by a 10-min respiratory-gated PET/CT acquisition. Four different reconstructions were performed by combining two different tomographic operators (TOs) (i.e. the geometric clinical system matrix or a system matrix including the detector response) and taking account (or not) of respiratory motion using a previously developed 'CT-based' technique. For each reconstruction method, lesion segmentation was performed with an adaptive threshold. Next, we computed the volume differences between each reconstruction. Finally, we applied a multiple linear model to compute the relative contributions of TO-based and CT-based respiratory compensation to lesion volume.
  
  
  RESULTS
  The three groups, combining the reconstruction methods and the respiratory compensation (or not), differed significantly in terms of the volume differences. For all lesions, the full linear model yielded a regression coefficient R of 76.10%. The partial R values were 65.58 and 10.52% for the detector response operator and the CT-based method, respectively. For lesions in the upper/middle lobes, blurring was mainly because of TO (partial R=78.53%), whereas, for lower lobe lesions, smearing was mainly because of respiratory motion (partial R=56.76%).
  
  
  CONCLUSIONS
  Our results showed that image reconstruction, by TO accuracy, was the main explanatory factor for lesion smearing when considering the chest as a whole. Respiration had a major impact on the lower lobes.
authors.affiliation: aBioflow Image Unit, Jules Verne University of Picardie bDepartment of Nuclear Medicine and Image Processing, Amiens University Medical Center, Amiens, France.
authors.forename: Joël
authors.initials: J
authors.lastname: Daouk
authors.forename: Pascal
authors.initials: P
authors.lastname: Bailly
authors.forename: Roger
authors.initials: R
authors.lastname: Bouzerar
authors.forename: Marc-Étienne
authors.initials: MÉ
authors.lastname: Meyer
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D019788:Fluorodeoxyglucose F18; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D009068:Movement; D055613:Multiple Pulmonary Nodules / Q000000981:diagnostic imaging* / Q000503:physiopathology; D000072078:Positron Emission Tomography Computed Tomography / Q000379:methods* / Q000706:statistics & numerical data; D019275:Radiopharmaceuticals; D012119:Respiration; D059629:Signal-To-Noise Ratio; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging* / Q000503:physiopathology
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18