Extension of the NCAT phantom for the investigation of intra-fraction respiratory motion in IMRT using 4D Monte Carlo

The purpose of this work was to create a computational platform for studying motion in intensity modulated radiotherapy (IMRT). Specifically, the non-uniform rational B-spline (NURB) cardiac and torso (NCAT) phantom was modified for use in a four-dimensional Monte Carlo (4D-MC) simulation system to investigate the effect of respiratory-induced intra-fraction organ motion on IMRT dose distributions as a function of diaphragm motion, lesion size and lung density. Treatment plans for four clinical scenarios were designed: diaphragm peak-to-peak amplitude of 1 cm and 3 cm, and two lesion sizes--2 cm and 4 cm diameter placed in the lower lobe of the right lung. Lung density was changed for each phase using a conservation of mass calculation. Further, a new heterogeneous lung model was implemented and tested. Each lesion had an internal target volume (ITV) subsequently expanded by 15 mm isotropically to give the planning target volume (PTV). The PTV was prescribed to receive 72 Gy in 40 fractions. The MLC leaf sequence defined by the planning system for each patient was exported and used as input into the MC system. MC simulations using the dose planning method (DPM) code together with deformable image registration based on the NCAT deformation field were used to find a composite dose distribution for each phantom. These composite distributions were subsequently analyzed using information from the dose volume histograms (DVH). Lesion motion amplitude has the largest effect on the dose distribution. Tumor size was found to have a smaller effect and can be mitigated by ensuring the planning constraints are optimized for the tumor size. The use of a dynamic or heterogeneous lung density model over a respiratory cycle does not appear to be an important factor with a <or=0.6% change in the mean dose received by the ITV, PTV and right lung. The heterogeneous model increases the realism of the NCAT phantom and may provide more accurate simulations in radiation therapy investigations that use the phantom. This work further evaluates the NCAT phantom for use as a tool in radiation therapy research in addition to its extensive use in diagnostic imaging and nuclear medicine research. Our results indicate that the NCAT phantom, combined with 4D-MC simulations, is a useful tool in radiation therapy investigations and may allow the study of relative effects in many clinically relevant situations.

[1]  Steve B. Jiang,et al.  Estimation of the delivered patient dose in lung IMRT treatment based on deformable registration of 4D-CT data and Monte Carlo simulations , 2006, Physics in medicine and biology.

[2]  K. Langen,et al.  Organ motion and its management. , 2001, International journal of radiation oncology, biology, physics.

[3]  D. G. Lewis,et al.  A DICOM-RT-based toolbox for the evaluation and verification of radiotherapy plans. , 2002, Physics in medicine and biology.

[4]  V. Spitzer,et al.  The visible human dataset: The anatomical platform for human simulation , 1998, The Anatomical record.

[5]  N Petoussi-Henss,et al.  ADULT FEMALE VOXEL MODELS OF DIFFERENT STATURE AND PHOTON CONVERSION COEFFICIENTS FOR RADIATION PROTECTION , 2004, Health physics.

[6]  Joao Seco,et al.  Dosimetric impact of motion in free-breathing and gated lung radiotherapy: a 4D Monte Carlo study of intrafraction and interfraction effects. , 2007, Medical physics.

[7]  Indrin J Chetty,et al.  How extensive of a 4D dataset is needed to estimate cumulative dose distribution plan evaluation metrics in conformal lung therapy? , 2006, Medical physics.

[8]  C. Ling,et al.  Respiration-correlated spiral CT: a method of measuring respiratory-induced anatomic motion for radiation treatment planning. , 2002, Medical physics.

[9]  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.

[10]  G. Christensen,et al.  A method for the reconstruction of four-dimensional synchronized CT scans acquired during free breathing. , 2003, Medical physics.

[11]  Ehsan Samei,et al.  Patient-specific dose estimation for pediatric chest CT. , 2008, Medical physics.

[12]  A. Bozkurt,et al.  VIP-MAN: AN IMAGE-BASED WHOLE-BODY ADULT MALE MODEL CONSTRUCTED FROM COLOR PHOTOGRAPHS OF THE VISIBLE HUMAN PROJECT FOR MULTI-PARTICLE MONTE CARLO CALCULATIONS , 2000, Health physics.

[13]  Indrin J Chetty,et al.  The impact of breathing motion versus heterogeneity effects in lung cancer treatment planning. , 2007, Medical physics.

[14]  Linda Hong,et al.  The effects of intra-fraction organ motion on the delivery of intensity-modulated field with a multileaf collimator. , 2003, Medical physics.

[15]  J Debus,et al.  Influence of intra-fractional breathing movement in step-and-shoot IMRT. , 2004, Physics in medicine and biology.

[16]  T. Pan,et al.  4D-CT imaging of a volume influenced by respiratory motion on multi-slice CT. , 2004, Medical physics.

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

[18]  Hongliang Yu,et al.  Automatic Rigid and Deformable Medical Image Registration , 2005 .

[19]  Martin Caon,et al.  Voxel-based computational models of real human anatomy: a review , 2004, Radiation and Environmental Biophysics.

[20]  P. Keall 4-dimensional computed tomography imaging and treatment planning. , 2004, Seminars in radiation oncology.

[21]  D A Jaffray,et al.  The effects of intra-fraction organ motion on the delivery of dynamic intensity modulation. , 1998, Physics in medicine and biology.

[22]  J. Seco,et al.  Head-and-neck IMRT treatments assessed with a Monte Carlo dose calculation engine , 2005, Physics in medicine and biology.

[23]  Tinsu Pan,et al.  Four-dimensional computed tomography: image formation and clinical protocol. , 2005, Medical physics.

[24]  B.M.W. Tsui,et al.  Development of a dynamic model for the lung lobes and airway tree in the NCAT phantom , 2002 .

[25]  Habib Zaidi,et al.  Computational anthropomorphic models of the human anatomy: the path to realistic Monte Carlo modeling in radiological sciences. , 2007, Annual review of biomedical engineering.

[26]  G Baroni,et al.  Design and Testing of a Simulation Framework for Dosimetric Motion Studies Integrating an Anthropomorphic Computational Phantom into Four-dimensional Monte Carlo , 2008, Technology in cancer research & treatment.

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

[28]  George Starkschall,et al.  Assessing respiration-induced tumor motion and internal target volume using four-dimensional computed tomography for radiotherapy of lung cancer. , 2007, International journal of radiation oncology, biology, physics.

[29]  H Shirato,et al.  Detection of lung tumor movement in real-time tumor-tracking radiotherapy. , 2001, International journal of radiation oncology, biology, physics.

[30]  Barbara Vanderstraeten,et al.  Accuracy of patient dose calculation for lung IMRT: A comparison of Monte Carlo, convolution/superposition, and pencil beam computations. , 2006, Medical physics.

[31]  Ross Berbeco,et al.  Management of the interplay effect when using dynamic MLC sequences to treat moving targets. , 2008, Medical physics.

[32]  D. Manocha,et al.  Development and application of the new dynamic Nurbs-based Cardiac-Torso (NCAT) phantom. , 2001 .

[33]  Harald Paganetti,et al.  Monte Carlo simulations with time-dependent geometries to investigate effects of organ motion with high temporal resolution. , 2004, International journal of radiation oncology, biology, physics.

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

[35]  R. Mohan,et al.  Acquiring a four-dimensional computed tomography dataset using an external respiratory signal. , 2003, Physics in medicine and biology.

[36]  Randall K Ten Haken,et al.  A method for incorporating organ motion due to breathing into 3D dose calculations in the liver: sensitivity to variations in motion. , 2003, Medical physics.

[37]  2207 Lung tumor motion with respiration does not correlate with location, pulmonary function, or chest wall motion , 1999 .

[38]  G Starkschall,et al.  Respiratory-driven lung tumor motion is independent of tumor size, tumor location, and pulmonary function. , 2001, International journal of radiation oncology, biology, physics.

[39]  P. Dimbylow Development of the female voxel phantom, NAOMI, and its application to calculations of induced current densities and electric fields from applied low frequency magnetic and electric fields , 2005, Physics in medicine and biology.

[40]  M. V. van Herk,et al.  Precise and real-time measurement of 3D tumor motion in lung due to breathing and heartbeat, measured during radiotherapy. , 2002, International journal of radiation oncology, biology, physics.

[41]  H Paganetti,et al.  Effects of organ motion on IMRT treatments with segments of few monitor units. , 2007, Medical physics.

[42]  Jan Seuntjens,et al.  A direct voxel tracking method for four-dimensional Monte Carlo dose calculations in deforming anatomy. , 2006, Medical physics.

[43]  Icru Prescribing, recording, and reporting photon beam therapy , 1993 .

[44]  R Mohan,et al.  Monte Carlo as a four-dimensional radiotherapy treatment-planning tool to account for respiratory motion. , 2004, Physics in medicine and biology.

[45]  J. Sempau,et al.  DPM, a fast, accurate Monte Carlo code optimized for photon and electron radiotherapy treatment planning dose calculations , 2000 .

[46]  I. Kawrakow Accurate condensed history Monte Carlo simulation of electron transport. I. EGSnrc, the new EGS4 version. , 2000, Medical physics.

[47]  R. Mohan,et al.  A method for photon beam Monte Carlo multileaf collimator particle transport. , 2002, Physics in medicine and biology.

[48]  Quynh-Thu Le,et al.  Quantification of motion of different thoracic locations using four-dimensional computed tomography: implications for radiotherapy planning. , 2007, International journal of radiation oncology, biology, physics.

[49]  William P. Segars,et al.  A realistic spline-based dynamic heart phantom , 1998 .

[50]  Steve B. Jiang,et al.  Effects of intra-fraction motion on IMRT dose delivery: statistical analysis and simulation. , 2002, Physics in medicine and biology.