title: A method to estimate mean position, motion magnitude, motion correlation, and trajectory of a tumor from cone-beam CT projections for image-guided radiotherapy.
abstract: OBJECTIVE
  To develop a probability-based method for estimating the mean position, motion magnitude, and trajectory of a tumor using cone-beam CT (CBCT) projections.
  
  
  METHODS
  CBCT acquisition was simulated for more than 80 hours of patient-measured trajectories for thoracic/abdominal tumors and prostate. The trajectories were divided into 60-second segments for which CBCT was simulated by projecting the tumor position onto a rotating imager. Tumor (surrogate) visibility on all projections was assumed. The mean and standard deviation of the tumor position and motion correlation along the three axes were determined with maximum likelihood estimation based on the projection data, assuming a Gaussian spatial distribution. The unknown position component along the imager axis was approximated by its expectation value, determined by the Gaussian distribution. Transformation of the resulting three-dimensional position to patient coordinates provided the estimated trajectory. Two trajectories were experimentally investigated by CBCT acquisition of a phantom.
  
  
  RESULTS
  The root-mean-square error of the estimated mean position was 0.05 mm. The root-mean-square error of the trajectories was <1 mm in 99.1% of the thorax/abdomen cases and in 99.7% of the prostate cases. The experimental trajectory estimation agreed with the actual phantom trajectory within 0.44 mm in any direction. Clinical applicability was demonstrated by estimating the tumor trajectory for a pancreas cancer case.
  
  
  CONCLUSIONS
  A method for estimation of mean position, motion magnitude, and trajectory of a tumor from CBCT projections has been developed. The accuracy was typically much better than 1 mm. The method is applicable to motion-inclusive, respiratory-gated, and tumor-tracking radiotherapy.
authors.affiliation: Department of Radiation Oncology, Stanford University, Stanford, CA, USA.
authors.forename: Per Rugaard
authors.initials: PR
authors.lastname: Poulsen
authors.forename: Byungchul
authors.initials: B
authors.lastname: Cho
authors.forename: Paul J
authors.initials: PJ
authors.lastname: Keall
mesh_terms: D000008:Abdominal Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D003198:Computer Simulation; D054893:Cone-Beam Computed Tomography / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D016013:Likelihood Functions; D008297:Male; D016011:Normal Distribution; D010190:Pancreatic Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology* / Q000532:radiotherapy; D011336:Probability; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D011877:Radionuclide Imaging; D011878:Radiotherapy / Q000379:methods*; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D012680:Sensitivity and Specificity; D013899:Thoracic Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology