title: Correlation between external and internal respiratory motion: a validation study.
abstract: OBJECTIVE
  In motion-compensated image-guided radiotherapy, accurate tracking of the target region is required. This tracking process includes building a correlation model between external surrogate motion and the motion of the target region. A novel correlation method is presented and compared with the commonly used polynomial model.
  
  
  METHODS
  The CyberKnife system (Accuray, Inc., Sunnyvale/CA) uses a polynomial correlation model to relate externally measured surrogate data (optical fibres on the patient's chest emitting red light) to infrequently acquired internal measurements (X-ray data). A new correlation algorithm based on ɛ -Support Vector Regression (SVR) was developed. Validation and comparison testing were done with human volunteers using live 3D ultrasound and externally measured infrared light-emitting diodes (IR LEDs). Seven data sets (5:03-6:27 min long) were recorded from six volunteers.
  
  
  RESULTS
  Polynomial correlation algorithms were compared to the SVR-based algorithm demonstrating an average increase in root mean square (RMS) accuracy of 21.3% (0.4 mm). For three signals, the increase was more than 29% and for one signal as much as 45.6% (corresponding to more than 1.5 mm RMS). Further analysis showed the improvement to be statistically significant.
  
  
  CONCLUSIONS
  The new SVR-based correlation method outperforms traditional polynomial correlation methods for motion tracking. This method is suitable for clinical implementation and may improve the overall accuracy of targeted radiotherapy.
authors.affiliation: Institute for Robotics and Cognitive Systems, University of Lübeck, Ratzeburger Allee 160, 23538, Lübeck, Germany. ernst@rob.uni-luebeck.de
authors.forename: Floris
authors.initials: F
authors.lastname: Ernst
authors.forename: Ralf
authors.initials: R
authors.lastname: Bruder
authors.forename: Alexander
authors.initials: A
authors.lastname: Schlaefer
authors.forename: Achim
authors.initials: A
authors.lastname: Schweikard
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008171:Lung Diseases / Q000175:diagnosis* / Q000601:surgery; D008954:Models, Biological; D009038:Motion; D016634:Radiosurgery / Q000379:methods; D015203:Reproducibility of Results; D013909:Thorax / Q000502:physiology*