Correlation between external and internal respiratory motion: a validation study

Type of publication:  Artikel
Zeitschrift: International Journal of Computer Assisted Radiology and Surgery
Band: 7
Nummer: 3
Jahr: 2012
Seiten: 483-492
Verlag: Springer
Notiz: Motion Compensation in Radiosurgery
DOI: 10.1007/s11548-011-0653-6
Abriss: Purpose 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 and Materials 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 $${\varepsilon}$$ -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. Conclusion 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.
Nutzerfelder: file={ebss_12b.pdf:ebss_12b.pdf:PDF}
Autoren: Ernst, Floris
Bruder, Ralf
Schlaefer, Alexander
Schweikard, Achim
  • ernst2011.pdf