title: Motion tracking in the liver: validation of a method based on 4D ultrasound using a nonrigid registration technique.
abstract: OBJECTIVE
  Treatments like radiotherapy and focused ultrasound in the abdomen require accurate motion tracking, in order to optimize dosage delivery to the target and minimize damage to critical structures and healthy tissues around the target. 4D ultrasound is a promising modality for motion tracking during such treatments. In this study, the authors evaluate the accuracy of motion tracking in the liver based on deformable registration of 4D ultrasound images.
  
  
  METHODS
  The offline analysis was performed using a nonrigid registration algorithm that was specifically designed for motion estimation from dynamic imaging data. The method registers the entire 4D image data sequence in a groupwise optimization fashion, thus avoiding a bias toward a specifically chosen reference time point. Three healthy volunteers were scanned over several breathing cycles (12 s) from three different positions and angles on the abdomen; a total of nine 4D scans for the three volunteers. Well-defined anatomic landmarks were manually annotated in all 96 time frames for assessment of the automatic algorithm. The error of the automatic motion estimation method was compared with interobserver variability. The authors also performed experiments to investigate the influence of parameters defining the deformation field flexibility and evaluated how well the method performed with a lower temporal resolution in order to establish the minimum frame rate required for accurate motion estimation.
  
  
  RESULTS
  The registration method estimated liver motion with an error of 1 mm (75% percentile over all datasets), which was lower than the interobserver variability of 1.4 mm. The results were only slightly dependent on the degrees of freedom of the deformation model. The registration error increased to 2.8 mm with an eight times lower temporal resolution.
  
  
  CONCLUSIONS
  The authors conclude that the methodology was able to accurately track the motion of the liver in the 4D ultrasound data. The authors believe that the method has potential in interventions on moving abdominal organs such as MR or ultrasound guided focused ultrasound therapy and radiotherapy, pending the method is enabled to run in real-time. The data and the annotations used for this study are made publicly available for those who would like to test other methods on 4D liver ultrasound data.
authors.affiliation: Norwegian University of Science and Technology, 7491 Trondheim, Norway.
authors.forename: Sinara
authors.initials: S
authors.lastname: Vijayan
authors.affiliation: Norwegian University of Science and Technology, 7491 Trondheim, Norway and Biomedical Imaging Group Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC, 3000 CA Rotterdam, The Netherlands.
authors.forename: Stefan
authors.initials: S
authors.lastname: Klein
authors.affiliation: SINTEF, Department Medical Technology, 7465 Trondheim, Norway.
authors.forename: Erlend Fagertun
authors.initials: EF
authors.lastname: Hofstad
authors.affiliation: Norwegian University of Science and Technology, 7491 Trondheim, Norway and SINTEF, Department Medical Technology, 7465 Trondheim, Norway.
authors.forename: Frank
authors.initials: F
authors.lastname: Lindseth
authors.affiliation: Department of Surgery, St. Olavs Hospital, 7030 Trondheim, Norway.
authors.forename: Brynjulf
authors.initials: B
authors.lastname: Ystgaard
authors.affiliation: SINTEF, Department Medical Technology, 7465 Trondheim, Norway.
authors.forename: Thomas
authors.initials: T
authors.lastname: Langø
mesh_terms: D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008099:Liver / Q000000981:diagnostic imaging*; D009038:Motion; D010363:Pattern Recognition, Automated / Q000379:methods; D012119:Respiration; D013995:Time; D014463:Ultrasonography / Q000379:methods*