Four-dimensional dosimetry validation and study in lung radiotherapy using deformable image registration and Monte Carlo techniques

Thoracic cancer treatment presents dosimetric difficulties due to respiratory motion and lung inhomogeneity. Monte Carlo and deformable image registration techniques have been proposed to be used in four-dimensional (4D) dose calculations to overcome the difficulties. This study validates the 4D Monte Carlo dosimetry with measurement, compares 4D dosimetry of different tumor sizes and tumor motion ranges, and demonstrates differences of dose-volume histograms (DVH) with the number of respiratory phases that are included in 4D dosimetry. BEAMnrc was used in dose calculations while an optical flow algorithm was used in deformable image registration and dose mapping. Calculated and measured doses of a moving phantom agreed within 3% at the center of the moving gross tumor volumes (GTV). 4D CT image sets of lung cancer cases were used in the analysis of 4D dosimetry. For a small tumor (12.5 cm3) with motion range of 1.5 cm, reduced tumor volume coverage was observed in the 4D dose with a beam margin of 1 cm. For large tumors and tumors with small motion range (around 1 cm), the 4D dosimetry did not differ appreciably from the static plans. The dose-volume histogram (DVH) analysis shows that the inclusion of only extreme respiratory phases in 4D dosimetry is a reasonable approximation of all-phase inclusion for lung cancer cases similar to the ones studied, which reduces the calculation in 4D dosimetry.

[1]  Carri K Glide-Hurst,et al.  A simplified method of four-dimensional dose accumulation using the mean patient density representation. , 2008, Medical physics.

[2]  Geoffrey G. Zhang,et al.  Dose mapping: Validation in 4D dosimetry with measurements and application in radiotherapy follow-up evaluation , 2008, Comput. Methods Programs Biomed..

[3]  Experimental verification of a commercial Monte Carlo-based dose calculation module for high-energy photon beams. , 2009, Physics in medicine and biology.

[4]  Daniel Normolle,et al.  Characterization of pancreatic tumor motion using cine MRI: surrogates for tumor position should be used with caution. , 2007, International journal of radiation oncology, biology, physics.

[5]  M. Fippel.  Efficient particle transport simulation through beam modulating devices for Monte Carlo treatment planning. , 2004, Medical physics.

[6]  Martin Weinmann,et al.  Intensity-modulated radiotherapy optimization in a quasi-periodically deforming patient model. , 2009, International journal of radiation oncology, biology, physics.

[7]  C. Ma,et al.  BEAM: a Monte Carlo code to simulate radiotherapy treatment units. , 1995, Medical physics.

[8]  Victor G. L. Alves,et al.  Percentage depth dose evaluation in heterogeneous media using thermoluminescent dosimetry , 2010, Journal of applied clinical medical physics.

[9]  Samy Bengio,et al.  Variance Reduction Techniques in . . . , 2003 .

[10]  F. Nüsslin,et al.  A virtual photon energy fluence model for Monte Carlo dose calculation. , 2003, Medical physics.

[11]  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.

[12]  Indrin J Chetty,et al.  Analysis of deformable image registration accuracy using computational modeling. , 2010, Medical physics.

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

[14]  I Kawrakow,et al.  Efficient photon beam dose calculations using DOSXYZnrc with BEAMnrc. , 2006, Medical physics.

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

[16]  M. Fippel.  Fast Monte Carlo dose calculation for photon beams based on the VMC electron algorithm. , 1999, Medical physics.

[17]  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.

[18]  J J DeMarco,et al.  A CT-based Monte Carlo simulation tool for dosimetry planning and analysis. , 1998, Medical physics.

[19]  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.

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

[21]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[22]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[23]  Steven S. Beauchemin,et al.  The computation of optical flow , 1995, CSUR.

[24]  Geoffrey G. Zhang,et al.  Intrathoracic tumour motion estimation from CT imaging using the 3D optical flow method. , 2004, Physics in medicine and biology.

[25]  George Starkschall,et al.  Comparing the accuracy of four-dimensional photon dose calculations with three-dimensional calculations using moving and deforming phantoms. , 2009, Medical physics.

[26]  Frank Verhaegen,et al.  Monte Carlo modelling of external radiotherapy photon beams. , 2003, Physics in medicine and biology.

[27]  C. Ma,et al.  A Monte Carlo dose calculation tool for radiotherapy treatment planning. , 2002, Physics in medicine and biology.

[28]  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.

[29]  C. Chui,et al.  A patient-specific Monte Carlo dose-calculation method for photon beams. , 1998, Medical physics.

[30]  Geoffrey G. Zhang,et al.  Elastic image mapping for 4-D dose estimation in thoracic radiotherapy. , 2005, Radiation protection dosimetry.

[31]  C. Ma,et al.  Clinical implementation of a Monte Carlo treatment planning system. , 1999, Medical physics.