A Dose Distribution Approach Using Monte Carlo Simulation in Dosimetric Accuracy Calculation for Treating the Lung Tumor
This paper presents a Monte Carlo (MC) method-based dose distributions on lung tumor for 6 MV photon beam to improve the dosimetric accuracy for cancer treatment. The polystyrene which is tissue equivalent material to the lung tumor density is used in this research. In the empirical calculations, TRS-398 formalism of IAEA has been used, and the setup was made according to the ICRU recommendations. The research outcomes were compared with the state-of-the-art experimental results. From the experimental results, it is observed that the proposed based approach provides more accurate results and improves the accuracy than the existing approaches. The average %variation between measured and TPS simulated values was obtained 1.337±0.531, which shows a substantial improvement comparing with the state-of-the-art technology.
[1] Ganesh N, Wilbert C, Niko P, Sotirios S. Comparison between measured tissue phantom ratio values and calculated from percent depth dose with and without peak scatter correction factor in a 6 MV beam. Int J Cancer Ther Oncol 2015:3(2):03024.
[2] Gibbons et al.: Monitoring unit calculations for photon and electron beams. Med. Phys. 41(3), March 2014: 031501-1.
[3] Brahme A, Lax I, Andreo P. Electron beam dose planning using discrete Gaussian beams. Mathematical background. Acta Oncol. 1981;20(2):147–158.
[4] Hogstrom KR, Mills MD, Almond PR. Electron beam dose calculations. Phys Med Biol. 1981;26(3):445–459.
[5] Mohan R, Chui C, Lidofsky L. Differential pencil beam dose computation model for photons. Med Phys.1986;13(1):64–73.
[6] Ulmer W, Pyyry J, Kaissl W. A 3D photon superposition/convolution algorithm and its foundation on results of Monte Carlo calculations. Phys Med Biol. 2005;50(8):1767–1790.
[7] Boyer A, Mok E. A photon dose distribution model employing convolution calculations. Med Phys. 1985;12(2):169–177.
[8] Ahnesjö A. Collapsed cone convolution of radiant energy for photon dose calculation in heterogeneous media. Med Phys. 1989;16(4):577–592.
[9] Antonella Fogliata et. al,. Dosimetric validation of the anisotropic analytical algorithm for photon dose calculation: fundamental characterization in water. Phys. Med. Bio. 2006; 51:1421-1438.
[10] Fippel M, Kawrakow I, Friedrich K. Electron beam dose calculations with the VMC algorithm and the verification data of the NCI working group. Phys Med Biol. 1997;42(3):501–520.
[11] Kawrakow I, Fippel M. Investigation of variance reduction techniques for Monte Carlo photon dose calculation using XVMC. Phys Med Biol. 2000;45(8):2163–2183.
[12] Hartmann Siantar CL, Walling RS, Daly TP, et al. Description and dosimetric verification of the PEREGRINE Monte Carlo dose calculation system for photon beams incident on a water phantom. Med Phys. 2001;28(7):1322–1337.
[13] Neuenschwander H, Mackie TR, Reckwerdt PJ. MMC—a high-performance Monte Carlo code for electron beam treatment planning. Phys Med Biol. 1995;40(4):543–574.
[14] Fippel M. Fast Monte Carlo dose calculation for photon beams based on the VMC electronalgorithm. Med Phys.1999;26(8):1466–1475.
[15] Kawrakow I. Proceeding of the Monte Carlo 2000 Meeting Lisbon. In: Kling A, Barao FJC, Nakaqawa M, et al., editors. Advanced Monte Carlo for radiation physics, particle transport simulation and applications. Berlin (Germany): Springer; 2001: 229–236
[16] Paelinck L, Reynaert N, Thierens H, De NW, De WC. Experimental verification of lung dose with radiochromic film: comparison with Monte Carlo simulations and commercially available treatment planning systems. Phys Med Biol. 2005;50(9):2055–2069.
[17] Werner BL, Das IJ, Salk WN. Dose perturbations at interfaces in photon beams: secondary electron transport. Med Phys. 1990;17(2):212–226.
[18] Van DJ, Barnett RB, Cygler JE, Shragge PC. Commissioning and quality assurance of treatment planning computers. Int J Radiat Oncol Biol Phys. 1993;26(2):261–273.
[19] Brahme A, Chavaudra J, Landberg T, et al. Accuracy requirements and quality assurance of external beam therapy with photons and electrons. Acta Oncol. 1988;27(1 Suppl):1–76.
[20] Jeff Craig, Mike Oliver, Adam Gladwish, Matt Mulligan, Jeff Chen and Eugene Wong. Commissioning a fast Monte Carlo dose calculation algorithm for lung cancer treatment Planning. Journal of Applied Clinical Medical Physics. 2008; 9(2): 83-93.
[21] Fox R. A. & Webb S. A comparison of inhomogeneity correction methods with Monte Carlo data. Australasian Physical Sciences in Medicine, 2 – 8, no.85, 452-462. Nov/Dec. 1979.
[22] Chow JC, Wong E, Chen JZ, Van Dyk J., Comparison of dose calculation algorithms with Monte Carlo methods for photon arcs, Med. Phys. 30(10), Am. Assoc. Phys. Med, 2003, 30(10), 2686-2694.
[23] George X Ding, Dennis M Duggan, Charles W Coffey, Parvaneh Shokrani and Joanna E Cygler. First macro Monte Carlo based commercial Dose calculation module for electron beam Treatment Planning, new issues for clinical consideration. Phys. Med. Biol. 51, 2781-2799, 2006.
[24] Hideharu Miura et al.: Evaluation and Commissioning of Commercial Monte Carlo Dose Algorithm for Air Cavity. Int J Medical Physics, Clinical Engineering and Radiation Oncology, 2014: 3: 9-13.
[25] Alam M.J. et.al. Calculation Accuracy and Quality Assurance of Computer Aided Radiation Therapy Planning. Ph.D., Thesis, University of Dhaka, 2012.
[26] E. G. A. Aird et.al, Central Axis Depth Dose data for Use in Radiotherapy. British Journal of Radiology Supplement-25.
[27] M. J. Alam, K. S. Rabbani, S. M. A. Husain, A. Kabir and T. Bagi. A modified formula for defining tissue phantom ratio of photon beams. Bangladesh Med Res Counc Bull 2007; 33: 92-921996.
[28] M. Jahangir Alam, M. Ashrafur Rahman, Khandoker Siddique-E. Rabbani. Dosimetric Accuracy Using the New Mathematical Tools for Inhomogeneous Denser Medium. International Journal of Clinical and Experimental Medical Sciences. Vol. 3, No. 2, 2017, pp. 23-29. doi: 10.11648/j.ijcems.20170302.12.
[29] J R Greening. Fundamentals of Radiation Dosimetry, Second Edition: Institute of Physics Pub., in collaboration with the Hospital Physicists' Association. 1992; p-176.
[30] Webb S. & Fox R. A,. Verification by Monte Carlo methods of power law tissue-air ratio algorithm for inhomogeneity corrections in photon beam Dose calculations. Phys. Med. Biol. 1980, 25(2); 225-240.
[31] Pedro Andreo et.al,. Absorbed Dose Determination in External Beam Radiotherapy. An International Code of Practice for Dosimetry Based on Standards of Absorbed Dose to Water. Technical Report Series no. IAEA TRS-398, 2004.
[32] S. A. Memon, N. A. Laghari, F. H. Mangi, F. Ahmad, M. M. Hussain, S. Palijo, N. Jhatyal and A. Adeel. “Analysis and verification of percent depth dose and tissue maximum ratio for Co-60 gamma ray beam.” Worl App Sci J 2015;33(1):109-13. http://dx.doi.org/10.5829/idosi.wasj.2015.33.01.9261.
[33] Samuelsson A. and Johansson K.A., Dose Accuracy Check of the 3-D Electron Beam Algorithm in Cad Plan. Sahlgrenska University Hospital, September 1995.
[34] William L. Saylor, M. S., D. A. B. R. and Thomas E., Dosage Calculations in Radiation Therapy, Ames, B. S., R. T. Urban & Schwarzenberg, 1979.
[35] Webb S., The Physics of Three-Dimensional Radiation Therapy: Conformal Radiotherapy, Radiosurgery, and Treatment Planning, (Ph. D.) p- 373 Jan 1, 1993.
[36] M. R. Sontag and J. R. Cunningham. The equivalent tissue–air ratio method for making absorbed dose calculations in a heterogeneous medium. Radiology 129, 787–794(1978).
[1] Ganesh N, Wilbert C, Niko P, Sotirios S. Comparison between measured tissue phantom ratio values and calculated from percent depth dose with and without peak scatter correction factor in a 6 MV beam. Int J Cancer Ther Oncol 2015:3(2):03024.
[2] Gibbons et al.: Monitoring unit calculations for photon and electron beams. Med. Phys. 41(3), March 2014: 031501-1.
[3] Brahme A, Lax I, Andreo P. Electron beam dose planning using discrete Gaussian beams. Mathematical background. Acta Oncol. 1981;20(2):147–158.
[4] Hogstrom KR, Mills MD, Almond PR. Electron beam dose calculations. Phys Med Biol. 1981;26(3):445–459.
[5] Mohan R, Chui C, Lidofsky L. Differential pencil beam dose computation model for photons. Med Phys.1986;13(1):64–73.
[6] Ulmer W, Pyyry J, Kaissl W. A 3D photon superposition/convolution algorithm and its foundation on results of Monte Carlo calculations. Phys Med Biol. 2005;50(8):1767–1790.
[7] Boyer A, Mok E. A photon dose distribution model employing convolution calculations. Med Phys. 1985;12(2):169–177.
[8] Ahnesjö A. Collapsed cone convolution of radiant energy for photon dose calculation in heterogeneous media. Med Phys. 1989;16(4):577–592.
[9] Antonella Fogliata et. al,. Dosimetric validation of the anisotropic analytical algorithm for photon dose calculation: fundamental characterization in water. Phys. Med. Bio. 2006; 51:1421-1438.
[10] Fippel M, Kawrakow I, Friedrich K. Electron beam dose calculations with the VMC algorithm and the verification data of the NCI working group. Phys Med Biol. 1997;42(3):501–520.
[11] Kawrakow I, Fippel M. Investigation of variance reduction techniques for Monte Carlo photon dose calculation using XVMC. Phys Med Biol. 2000;45(8):2163–2183.
[12] Hartmann Siantar CL, Walling RS, Daly TP, et al. Description and dosimetric verification of the PEREGRINE Monte Carlo dose calculation system for photon beams incident on a water phantom. Med Phys. 2001;28(7):1322–1337.
[13] Neuenschwander H, Mackie TR, Reckwerdt PJ. MMC—a high-performance Monte Carlo code for electron beam treatment planning. Phys Med Biol. 1995;40(4):543–574.
[14] Fippel M. Fast Monte Carlo dose calculation for photon beams based on the VMC electronalgorithm. Med Phys.1999;26(8):1466–1475.
[15] Kawrakow I. Proceeding of the Monte Carlo 2000 Meeting Lisbon. In: Kling A, Barao FJC, Nakaqawa M, et al., editors. Advanced Monte Carlo for radiation physics, particle transport simulation and applications. Berlin (Germany): Springer; 2001: 229–236
[16] Paelinck L, Reynaert N, Thierens H, De NW, De WC. Experimental verification of lung dose with radiochromic film: comparison with Monte Carlo simulations and commercially available treatment planning systems. Phys Med Biol. 2005;50(9):2055–2069.
[17] Werner BL, Das IJ, Salk WN. Dose perturbations at interfaces in photon beams: secondary electron transport. Med Phys. 1990;17(2):212–226.
[18] Van DJ, Barnett RB, Cygler JE, Shragge PC. Commissioning and quality assurance of treatment planning computers. Int J Radiat Oncol Biol Phys. 1993;26(2):261–273.
[19] Brahme A, Chavaudra J, Landberg T, et al. Accuracy requirements and quality assurance of external beam therapy with photons and electrons. Acta Oncol. 1988;27(1 Suppl):1–76.
[20] Jeff Craig, Mike Oliver, Adam Gladwish, Matt Mulligan, Jeff Chen and Eugene Wong. Commissioning a fast Monte Carlo dose calculation algorithm for lung cancer treatment Planning. Journal of Applied Clinical Medical Physics. 2008; 9(2): 83-93.
[21] Fox R. A. & Webb S. A comparison of inhomogeneity correction methods with Monte Carlo data. Australasian Physical Sciences in Medicine, 2 – 8, no.85, 452-462. Nov/Dec. 1979.
[22] Chow JC, Wong E, Chen JZ, Van Dyk J., Comparison of dose calculation algorithms with Monte Carlo methods for photon arcs, Med. Phys. 30(10), Am. Assoc. Phys. Med, 2003, 30(10), 2686-2694.
[23] George X Ding, Dennis M Duggan, Charles W Coffey, Parvaneh Shokrani and Joanna E Cygler. First macro Monte Carlo based commercial Dose calculation module for electron beam Treatment Planning, new issues for clinical consideration. Phys. Med. Biol. 51, 2781-2799, 2006.
[24] Hideharu Miura et al.: Evaluation and Commissioning of Commercial Monte Carlo Dose Algorithm for Air Cavity. Int J Medical Physics, Clinical Engineering and Radiation Oncology, 2014: 3: 9-13.
[25] Alam M.J. et.al. Calculation Accuracy and Quality Assurance of Computer Aided Radiation Therapy Planning. Ph.D., Thesis, University of Dhaka, 2012.
[26] E. G. A. Aird et.al, Central Axis Depth Dose data for Use in Radiotherapy. British Journal of Radiology Supplement-25.
[27] M. J. Alam, K. S. Rabbani, S. M. A. Husain, A. Kabir and T. Bagi. A modified formula for defining tissue phantom ratio of photon beams. Bangladesh Med Res Counc Bull 2007; 33: 92-921996.
[28] M. Jahangir Alam, M. Ashrafur Rahman, Khandoker Siddique-E. Rabbani. Dosimetric Accuracy Using the New Mathematical Tools for Inhomogeneous Denser Medium. International Journal of Clinical and Experimental Medical Sciences. Vol. 3, No. 2, 2017, pp. 23-29. doi: 10.11648/j.ijcems.20170302.12.
[29] J R Greening. Fundamentals of Radiation Dosimetry, Second Edition: Institute of Physics Pub., in collaboration with the Hospital Physicists' Association. 1992; p-176.
[30] Webb S. & Fox R. A,. Verification by Monte Carlo methods of power law tissue-air ratio algorithm for inhomogeneity corrections in photon beam Dose calculations. Phys. Med. Biol. 1980, 25(2); 225-240.
[31] Pedro Andreo et.al,. Absorbed Dose Determination in External Beam Radiotherapy. An International Code of Practice for Dosimetry Based on Standards of Absorbed Dose to Water. Technical Report Series no. IAEA TRS-398, 2004.
[32] S. A. Memon, N. A. Laghari, F. H. Mangi, F. Ahmad, M. M. Hussain, S. Palijo, N. Jhatyal and A. Adeel. “Analysis and verification of percent depth dose and tissue maximum ratio for Co-60 gamma ray beam.” Worl App Sci J 2015;33(1):109-13. http://dx.doi.org/10.5829/idosi.wasj.2015.33.01.9261.
[33] Samuelsson A. and Johansson K.A., Dose Accuracy Check of the 3-D Electron Beam Algorithm in Cad Plan. Sahlgrenska University Hospital, September 1995.
[34] William L. Saylor, M. S., D. A. B. R. and Thomas E., Dosage Calculations in Radiation Therapy, Ames, B. S., R. T. Urban & Schwarzenberg, 1979.
[35] Webb S., The Physics of Three-Dimensional Radiation Therapy: Conformal Radiotherapy, Radiosurgery, and Treatment Planning, (Ph. D.) p- 373 Jan 1, 1993.
[36] M. R. Sontag and J. R. Cunningham. The equivalent tissue–air ratio method for making absorbed dose calculations in a heterogeneous medium. Radiology 129, 787–794(1978).
@article{"International Journal of Medical, Medicine and Health Sciences:77324", author = "Md Abdullah Al Mashud and M. Tariquzzaman and M. Jahangir Alam and Tapan Kumar Godder and M. Mahbubur Rahman", title = "A Dose Distribution Approach Using Monte Carlo Simulation in Dosimetric Accuracy Calculation for Treating the Lung Tumor", abstract = "This paper presents a Monte Carlo (MC) method-based dose distributions on lung tumor for 6 MV photon beam to improve the dosimetric accuracy for cancer treatment. The polystyrene which is tissue equivalent material to the lung tumor density is used in this research. In the empirical calculations, TRS-398 formalism of IAEA has been used, and the setup was made according to the ICRU recommendations. The research outcomes were compared with the state-of-the-art experimental results. From the experimental results, it is observed that the proposed based approach provides more accurate results and improves the accuracy than the existing approaches. The average %variation between measured and TPS simulated values was obtained 1.337±0.531, which shows a substantial improvement comparing with the state-of-the-art technology.
", keywords = "Lung tumor, Monte Carlo, polystyrene, elekta synergy, Monaco Planning System.", volume = "12", number = "4", pages = "151-6", }
