Reference respiratory waveforms by minimum jerk model analysis.

PURPOSE CyberKnife(®) robotic surgery system has the ability to deliver radiation to a tumor subject to respiratory movements using Synchrony(®) mode with less than 2 mm tracking accuracy. However, rapid and rough motion tracking causes mechanical tracking errors and puts mechanical stress on the robotic joint, leading to unexpected radiation delivery errors. During clinical treatment, patient respiratory motions are much more complicated, suggesting the need for patient-specific modeling of respiratory motion. The purpose of this study was to propose a novel method that provides a reference respiratory wave to enable smooth tracking for each patient. METHODS The minimum jerk model, which mathematically derives smoothness by means of jerk, or the third derivative of position and the derivative of acceleration with respect to time that is proportional to the time rate of force changed was introduced to model a patient-specific respiratory motion wave to provide smooth motion tracking using CyberKnife(®). To verify that patient-specific minimum jerk respiratory waves were being tracked smoothly by Synchrony(®) mode, a tracking laser projection from CyberKnife(®) was optically analyzed every 0.1 s using a webcam and a calibrated grid on a motion phantom whose motion was in accordance with three pattern waves (cosine, typical free-breathing, and minimum jerk theoretical wave models) for the clinically relevant superior-inferior directions from six volunteers assessed on the same node of the same isocentric plan. RESULTS Tracking discrepancy from the center of the grid to the beam projection was evaluated. The minimum jerk theoretical wave reduced the maximum-peak amplitude of radial tracking discrepancy compared with that of the waveforms modeled by cosine and typical free-breathing model by 22% and 35%, respectively, and provided smooth tracking for radial direction. Motion tracking constancy as indicated by radial tracking discrepancy affected by respiratory phase was improved in the minimum jerk theoretical model by 7.0% and 13% compared with that of the waveforms modeled by cosine and free-breathing model, respectively. CONCLUSIONS The minimum jerk theoretical respiratory wave can achieve smooth tracking by CyberKnife(®) and may provide patient-specific respiratory modeling, which may be useful for respiratory training and coaching, as well as quality assurance of the mechanical CyberKnife(®) robotic trajectory.

[1]  Frank Weichert,et al.  Analysis of the Accuracy and Robustness of the Leap Motion Controller , 2013, Sensors.

[2]  Xiaodong Wu,et al.  Report of AAPM TG 135: quality assurance for robotic radiosurgery. , 2011, Medical physics.

[3]  H. Shiomi,et al.  SU‐E‐T‐584: The Accuracy of the Respiratory Motion Tracking with Robotic Radiosurgery System , 2011 .

[4]  Mitsuhiro Nakamura,et al.  Positional reproducibility of pancreatic tumors under end-exhalation breath-hold conditions using a visual feedback technique. , 2011, International journal of radiation oncology, biology, physics.

[5]  Thierry Gevaert,et al.  Geometric accuracy of a novel gimbals based radiation therapy tumor tracking system. , 2011, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[6]  Hong Liu,et al.  Model predictive control for adaptive cruise control with multi-objectives: comfort, fuel-economy, safety and car-following , 2010 .

[7]  E. Pantelis,et al.  Image guidance quality assurance of a G4 CyberKnife robotic stereotactic radiosurgery system , 2009 .

[8]  M. Hoogeman,et al.  Clinical accuracy of the respiratory tumor tracking system of the cyberknife: assessment by analysis of log files. , 2009, International journal of radiation oncology, biology, physics.

[9]  Sergio Silvestri,et al.  Design and evaluation of a methodology to perform personalized visual biofeedback for reducing respiratory amplitude in radiation treatment. , 2009, Medical physics.

[10]  S. Senan,et al.  Impact of audio-coaching on the position of lung tumors. , 2008, International journal of radiation oncology, biology, physics.

[11]  Paul J Keall,et al.  Development and preliminary evaluation of a prototype audiovisual biofeedback device incorporating a patient-specific guiding waveform , 2008, Physics in medicine and biology.

[12]  Dwight E Heron,et al.  Synchrony--cyberknife respiratory compensation technology. , 2008, Medical dosimetry : official journal of the American Association of Medical Dosimetrists.

[13]  Hiroki Shirato,et al.  Accuracy of tumor motion compensation algorithm from a robotic respiratory tracking system: a simulation study. , 2007, Medical physics.

[14]  John A. Mills,et al.  Respiratory motion prediction for adaptive radiotherapy , 2006 .

[15]  Steve B. Jiang,et al.  The management of respiratory motion in radiation oncology report of AAPM Task Group 76. , 2006, Medical physics.

[16]  Steve B. Jiang,et al.  Synchronized moving aperture radiation therapy (SMART): improvement of breathing pattern reproducibility using respiratory coaching , 2006, Physics in medicine and biology.

[17]  Steve B. Jiang,et al.  Residual motion of lung tumours in gated radiotherapy with external respiratory surrogates , 2005, Physics in medicine and biology.

[18]  Jean-Philippe Pignol,et al.  Correlation of lung tumor motion with external surrogate indicators of respiration. , 2004, International journal of radiation oncology, biology, physics.

[19]  Radhe Mohan,et al.  Patient training in respiratory-gated radiotherapy. , 2003, Medical dosimetry : official journal of the American Association of Medical Dosimetrists.

[20]  Martin J Murphy,et al.  Issues in respiratory motion compensation during external-beam radiotherapy. , 2002, International journal of radiation oncology, biology, physics.

[21]  M. V. van Herk,et al.  Physical aspects of a real-time tumor-tracking system for gated radiotherapy. , 2000, International journal of radiation oncology, biology, physics.

[22]  T. Flash,et al.  The coordination of arm movements: an experimentally confirmed mathematical model , 1985, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[23]  Torsten Kröger,et al.  Robot motion control during abrupt switchings between manipulation primitives , 2011, ICRA 2011.

[24]  Steve B. Jiang,et al.  The management of respiratory motion in radiation oncology report of AAPM Task Group 76. , 2006, Medical physics.

[25]  Taketoshi Kunimatsu,et al.  Modeling of driver following behavior based on minimum-jerk theory , 2005 .