title: Evaluation of kV cone-beam ct performance for prostate IGRT: a comparison of automatic grey-value alignment to implanted fiducial-marker alignment.
abstract: OBJECTIVE
  Cone-beam computed tomography (CBCT) is a new image-guided radiation therapy (IGRT) technique for patient alignment in radiotherapy. The CBCT x-ray volume imaging system from Elekta allows for a variety of alignment methods. The aim of this study is to assess the accuracy of soft-tissue-based automatic alignment as compared with manual alignment using intraprostatic fiducials.
  
  
  METHODS
  All patients were treated on an Elekta Synergy S linear accelerator with kilovoltage CBCT. All alignments were performed using the x-ray volume imaging system and associated software. Automatic alignment with gray-value-based registration and manual alignment to fiducial markers were performed. Transitional corrections along each axis as well as 3-dimensional vectors were compared with evaluate the accuracy of gray-value-based registration compared with fiducials.
  
  
  RESULTS
  The distribution of the 3-dimensional vectors between gray-value and fiducial registrations demonstrated notable differences. The mean summed vector was 0.75 cm, with a standard deviation (SD) of 0.52 cm and range from 0.04 to 2.06 cm. There was minimal difference along the lateral direction, with a mean ± SD of -0.02 cm ± 0.13 cm. However, there were large discrepancies along the superior-inferior and anterior-posterior direction alignments, with mean ± SD values of -0.55 ± 0.48 cm and -0.31 ± 0.43 cm, respectively.
  
  
  CONCLUSIONS
  CBCT with soft-tissue-based automatic corrections is not an accurate alignment compared with manual alignment to fiducial markers for prostate IGRT. We have concluded that a daily manual alignment to fiducials is one of the most reliable methods to maintain accuracy in prostate IGRT.
authors.affiliation: Department of Radiation Oncology University of Florida College of Medicine, Gainesville, FL, USA.
authors.forename: Wenyin
authors.initials: W
authors.lastname: Shi
authors.forename: Jonathan G
authors.initials: JG
authors.lastname: Li
authors.forename: Robert A
authors.initials: RA
authors.lastname: Zlotecki
authors.forename: Anamaria
authors.initials: A
authors.lastname: Yeung
authors.forename: Heather
authors.initials: H
authors.lastname: Newlin
authors.forename: Jatinder
authors.initials: J
authors.lastname: Palta
authors.forename: Chihray
authors.initials: C
authors.lastname: Liu
authors.forename: Alexei V
authors.initials: AV
authors.lastname: Chvetsov
authors.forename: Kenneth
authors.initials: K
authors.lastname: Olivier
mesh_terms: D000230:Adenocarcinoma / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D054893:Cone-Beam Computed Tomography; D057918:Fiducial Markers; D006801:Humans; D008297:Male; D009367:Neoplasm Staging; D010363:Pattern Recognition, Automated; D011379:Prognosis; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D019736:Prostheses and Implants; D011856:Radiographic Image Enhancement; D011857:Radiographic Image Interpretation, Computer-Assisted; D050397:Radiotherapy, Intensity-Modulated; D012189:Retrospective Studies