title: Evaluation of a template-based algorithm for markerless lung tumour localization on single- and dual-energy kilovoltage images.
abstract: OBJECTIVE
  To evaluate a template-based matching algorithm on single-energy (SE) and dual-energy (DE) radiographs for markerless localization of lung tumours.
  
  
  METHODS
  A total of 74 images from 17 patients with Stages IA-IV lung cancer were considered. At the time of radiotherapy treatment, gated end-expiration SE radiographs were obtained at 60 and 120 kVp at different gantry angles (33° anterior and 41° oblique), from which soft-tissue-enhanced DE images were created. A template-based matching algorithm was used to localize individual tumours on both SE and DE radiographs. Tumour centroid co-ordinates obtained from the template-matching software on both SE and DE images were compared with co-ordinates defined by physicians.
  
  
  RESULTS
  The template-based matching algorithm was able to successfully localize the gross tumor volume within 5 mm on 70% (52/74) of the SE images vs 91% (66/74) of the DE images (p < 0.01). The mean vector differences between the co-ordinates of the template matched by the algorithm and the co-ordinates of the physician-defined ground truth were 3.2 ± 2.8 mm for SE images vs 2.3 ± 1.7 mm for DE images (p = 0.03).
  
  
  CONCLUSIONS
  Template-based matching on DE images was more accurate and precise than using SE images. Advances in knowledge: This represents, to the authors' knowledge, the largest study evaluating template matching on clinical SE and DE images, considering not only anterior gantry angles but also oblique angles, suggesting a novel lung tumour matching technique using DE subtraction that is reliable, accurate and precise.
authors.affiliation: Department of Radiation Oncology, Loyola University Medical Center, Maywood, IL, USA.
authors.forename: Alec M
authors.initials: AM
authors.lastname: Block
authors.affiliation: Department of Radiation Oncology, Loyola University Medical Center, Maywood, IL, USA.
authors.forename: Rakesh
authors.initials: R
authors.lastname: Patel
authors.affiliation: Department of Radiation Oncology, Loyola University Medical Center, Maywood, IL, USA.
authors.forename: Murat
authors.initials: M
authors.lastname: Surucu
authors.affiliation: Department of Radiation Oncology, Loyola University Medical Center, Maywood, IL, USA.
authors.forename: Matthew M
authors.initials: MM
authors.lastname: Harkenrider
authors.affiliation: Department of Radiation Oncology, Loyola University Medical Center, Maywood, IL, USA.
authors.forename: John C
authors.initials: JC
authors.lastname: Roeske
mesh_terms: D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008168:Lung / Q000000981:diagnostic imaging; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results