title: Respiratory motion correction for quantitative PET/CT using all detected events with internal-external motion correlation.
abstract: OBJECTIVE
  We present a method to correct respiratory motion blurring in PET/CT imaging using internal-external (INTEX) motion correlation. The internal motion of a known tumor is derived from respiratory-gated PET images; this internal motion is then correlated with external respiratory signals to determine the complete information of tumor motion during the scan.
  
  
  METHODS
  For each PET/CT data, PET listmode data were phase-gated into five bins and reconstructed. The centroid of a targeted tumor in each bin was determined and correlated with the corresponding mean displacement of externally monitored respiratory motion signal. Based on this correlation, the external motion signal was converted into internal tumor motion information in the superior-inferior direction. Then, the PET listmode data were binned sequentially to multiple 1-s sinograms. According to the converted internal tumor motion signal, each 1-s sinogram was registered to a reference frame, which best matched the helical CT attenuation map based on consistency conditions. The registered sinograms were summed and reconstructed to form an image, corrected for the motion of the specific tumor. In this study, the proposed INTEX method was evaluated with phantom and patient studies in terms of tracer concentration and volume.
  
  
  RESULTS
  The INTEX method effectively recovered the tracer concentration to the level of the stationary scan data in the phantom experiment. In the patient study, the INTEX method yielded a (17 +/- 22)% tumor volume decrease and a (10 +/- 10)% tumor SUVmax increase compared to non-gated images.
  
  
  CONCLUSIONS
  The proposed INTEX method reduces respiratory motion degradation of PET tumor quantification and delineation in an effective manner. This can be used to improve the assessment of response to therapy for a known tumor by minimizing residual motion and matching the attenuation correction, without increasing image noise.
authors.affiliation: Department of Diagnostic Radiology, Yale University, New Haven, Connecticut 06520, USA. chi.liu@yale.edu
authors.forename: Chi
authors.initials: C
authors.lastname: Liu
authors.forename: Adam M
authors.initials: AM
authors.lastname: Alessio
authors.forename: Paul E
authors.initials: PE
authors.lastname: Kinahan
mesh_terms: D000465:Algorithms; D016477:Artifacts; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D009038:Motion; D009068:Movement; D009369:Neoplasms / Q000175:diagnosis*; D049268:Positron-Emission Tomography / Q000379:methods*; D015203:Reproducibility of Results; D015656:Respiratory Mechanics; D055425:Respiratory-Gated Imaging Techniques / Q000379:methods*; D012680:Sensitivity and Specificity; D013223:Statistics as Topic; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*