title: Patient-specific scatter correction in clinical cone beam computed tomography imaging made possible by the combination of Monte Carlo simulations and a ray tracing algorithm.
abstract: OBJECTIVE
  Cone beam computed tomography (CBCT) image quality is limited by scattered photons. Monte Carlo (MC) simulations provide the ability of predicting the patient-specific scatter contamination in clinical CBCT imaging. Lengthy simulations prevent MC-based scatter correction from being fully implemented in a clinical setting. This study investigates the combination of using fast MC simulations to predict scatter distributions with a ray tracing algorithm to allow calibration between simulated and clinical CBCT images.
  
  
  METHODS
  An EGSnrc-based user code (egs_cbct), was used to perform MC simulations of an Elekta XVI CBCT imaging system. A 60 keV x-ray source was used, and air kerma scored at the detector plane. Several variance reduction techniques (VRTs) were used to increase the scatter calculation efficiency. Three patient phantoms based on CT scans were simulated, namely a brain, a thorax and a pelvis scan. A ray tracing algorithm was used to calculate the detector signal due to primary photons. A total of 288 projections were simulated, one for each thread on the computer cluster used for the investigation.
  
  
  RESULTS
  Scatter distributions for the brain, thorax and pelvis scan were simulated within 2% statistical uncertainty in two hours per scan. Within the same time, the ray tracing algorithm provided the primary signal for each of the projections. Thus, all the data needed for MC-based scatter correction in clinical CBCT imaging was obtained within two hours per patient, using a full simulation of the clinical CBCT geometry.
  
  
  CONCLUSIONS
  This study shows that use of MC-based scatter corrections in CBCT imaging has a great potential to improve CBCT image quality. By use of powerful VRTs to predict scatter distributions and a ray tracing algorithm to calculate the primary signal, it is possible to obtain the necessary data for patient specific MC scatter correction within two hours per patient.
authors.affiliation: Institute of Clinical Research, University of Southern Denmark , Odense , Denmark.
authors.forename: Rune S
authors.initials: RS
authors.lastname: Thing
authors.forename: Uffe
authors.initials: U
authors.lastname: Bernchou
authors.forename: Ernesto
authors.initials: E
authors.lastname: Mainegra-Hing
authors.forename: Carsten
authors.initials: C
authors.lastname: Brink
mesh_terms: D000465:Algorithms; D001932:Brain Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy; D003198:Computer Simulation; D054893:Cone-Beam Computed Tomography; D006801:Humans; D007091:Image Processing, Computer-Assisted; D009010:Monte Carlo Method; D010386:Pelvic Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy; D019047:Phantoms, Imaging; D011856:Radiographic Image Enhancement; D061089:Radiotherapy, Image-Guided; D012542:Scattering, Radiation; D013899:Thoracic Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy