Dosimetric evaluation of intrafractional tumor motion by means of a robot driven phantom.

PURPOSE The aim of the work was to investigate the influence of intrafractional tumor motion to the accumulated (absorbed) dose. The accumulated dose was determined by means of calculations and measurements with a robot driven motion phantom. METHODS Different motion scenarios and compensation techniques were realized in a phantom study to investigate the influence of motion on image acquisition, dose calculation, and dose measurement. The influence of motion on the accumulated dose was calculated by employing two methods (a model based and a voxel based method). RESULTS Tumor motion resulted in a blurring of steep dose gradients and a reduction of dose at the periphery of the target. A systematic variation of motion parameters allowed the determination of the main influence parameters on the accumulated dose. The key parameters with the greatest influence on dose were the mean amplitude and the pattern of motion. Investigations on necessary safety margins to compensate for dose reduction have shown that smaller safety margins are sufficient, if the developed concept with optimized margins (OPT concept) was used instead of the standard internal target volume (ITV) concept. Both calculation methods were a reasonable approximation of the measured dose with the voxel based method being in better agreement with the measurements. CONCLUSIONS Further evaluation of available systems and algorithms for dose accumulation are needed to create guidelines for the verification of the accumulated dose.

[1]  Y D Mutaf,et al.  A simulation study of irregular respiratory motion and its dosimetric impact on lung tumors , 2011, Physics in medicine and biology.

[2]  Matthias Guckenberger,et al.  Tracking moving objects with megavoltage portal imaging: a feasibility study. , 2006, Medical physics.

[3]  Jan Seuntjens,et al.  A deformable phantom for 4D radiotherapy verification: design and image registration evaluation. , 2008, Medical physics.

[4]  Vladimir Pekar,et al.  Assessment of a model-based deformable image registration approach for radiation therapy planning. , 2007, International journal of radiation oncology, biology, physics.

[5]  Jan-Jakob Sonke,et al.  Mid-ventilation CT scan construction from four-dimensional respiration-correlated CT scans for radiotherapy planning of lung cancer patients. , 2006, International journal of radiation oncology, biology, physics.

[6]  John N Tsitsiklis,et al.  Optimal margin and edge-enhanced intensity maps in the presence of motion and uncertainty , 2010, Physics in medicine and biology.

[7]  R. Mohan,et al.  Motion adaptive x-ray therapy: a feasibility study , 2001, Physics in medicine and biology.

[8]  George T. Y. Chen,et al.  Four-dimensional image-based treatment planning: Target volume segmentation and dose calculation in the presence of respiratory motion. , 2005, International journal of radiation oncology, biology, physics.

[9]  Patrick A Kupelian,et al.  Modeling simulation and visualization of conformal 3D lung tumor dosimetry , 2009, Physics in medicine and biology.

[10]  Steve B. Jiang,et al.  Quality assurance challenges for motion-adaptive radiation therapy: gating, breath holding, and four-dimensional computed tomography. , 2008, International journal of radiation oncology, biology, physics.

[11]  Y. Mutaf,et al.  Optimization of internal margin to account for dosimetric effects of respiratory motion. , 2008, International journal of radiation oncology, biology, physics.

[12]  D. Yan,et al.  A model to accumulate fractionated dose in a deforming organ. , 1999, International journal of radiation oncology, biology, physics.

[13]  J. Leong,et al.  Implementation of random positioning error in computerised radiation treatment planning systems as a result of fractionation. , 1987, Physics in medicine and biology.

[14]  Steve B. Jiang,et al.  An experimental investigation on intra-fractional organ motion effects in lung IMRT treatments. , 2003, Physics in medicine and biology.

[15]  T. Gevaert,et al.  Gating and tracking, 4D in thoracic tumours. , 2010, Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique.

[16]  B. Rhein,et al.  The influence of breathing motion on intensity modulated radiotherapy in the step-and-shoot technique: phantom measurements for irradiation of superficial target volumes , 2006, Physics in medicine and biology.

[17]  Paul Segars,et al.  Extension of the NCAT phantom for the investigation of intra-fraction respiratory motion in IMRT using 4D Monte Carlo , 2010, Physics in medicine and biology.

[18]  J. V. Dyk,et al.  Lung density as measured by computerized tomography: implications for radiotherapy. , 1982 .

[19]  Radhe Mohan,et al.  Audio-visual biofeedback for respiratory-gated radiotherapy: impact of audio instruction and audio-visual biofeedback on respiratory-gated radiotherapy. , 2006, International journal of radiation oncology, biology, physics.

[20]  Matthias Guckenberger,et al.  Influence of increased target dose inhomogeneity on margins for breathing motion compensation in conformal stereotactic body radiotherapy , 2008, BMC medical physics.

[21]  J. Biederer,et al.  Four-dimensional magnetic resonance imaging for the determination of tumour movement and its evaluation using a dynamic porcine lung phantom , 2007, Physics in medicine and biology.

[22]  Rojano Kashani,et al.  Technical note: a deformable phantom for dynamic modeling in radiation therapy. , 2007, Medical physics.

[23]  T. Mackie,et al.  Fast free-form deformable registration via calculus of variations , 2004, Physics in medicine and biology.

[24]  Matthias Guckenberger,et al.  Potential of image-guidance, gating and real-time tracking to improve accuracy in pulmonary stereotactic body radiotherapy. , 2009, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[25]  James C L Chow,et al.  The use of spatial dose gradients and probability density function to evaluate the effect of internal organ motion for prostate IMRT treatment planning , 2007, Physics in medicine and biology.

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

[27]  Matthias Guckenberger,et al.  Feasibility study for markerless tracking of lung tumors in stereotactic body radiotherapy. , 2010, International journal of radiation oncology, biology, physics.

[28]  Matthias Guckenberger,et al.  Influence of retrospective sorting on image quality in respiratory correlated computed tomography. , 2007, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[29]  Jan-Jakob Sonke,et al.  Variability of four-dimensional computed tomography patient models. , 2008, International journal of radiation oncology, biology, physics.

[30]  K. Brock,et al.  Accurate accumulation of dose for improved understanding of radiation effects in normal tissue. , 2010, International journal of radiation oncology, biology, physics.

[31]  S Minohara,et al.  Respiratory gated irradiation system for heavy-ion radiotherapy. , 2000, International journal of radiation oncology, biology, physics.

[32]  T. Bortfeld,et al.  How much margin reduction is possible through gating or breath hold? , 2005, Physics in medicine and biology.