Accuracy of the Small Field Dosimetry Using the Acuros XB Dose Calculation Algorithm within and beyond Heterogeneous Media for 6 MV Photon Beams

Sotirios Stathakis, Carlos Esquivel, Luis Vazquez Quino, Pamela Myers, Oscar Calvo, Panayiotis Mavroidis, Alonso N. Gutiérrez, Niko Papanikolaou

Cancer Therapy and Research Center at University of Texas Health Science Center at San Antonio.

DOI: 10.4236/ijmpcero.2012.13011                

Abstract

Purpose: The dosimetric accuracy of the recently released Acuros XB advanced dose calculation algorithm (Varian Medical Systems, Palo Alto, CA) is investigated for single radiation fields incident on homogeneous and heterogeneous geometries, as well as for two arc (VMAT) cases and compared against the analytical anisotropic algorithm (AAA), the collapsed cone convolution superposition algorithm (CCCS) and Monte Carlo (MC) calculations for the same geometries. Methods and Materials: Small open fields ranging from 1 × 1 cm² to 5 × 5 cm² were used for part of this study. The fields were incident on phantoms containing lung, air, and bone inhomogeneities. The dosimetric accuracy of Acuros XB, AAA and CCCS in the presence of the inhomogeneities was compared against BEAMnrc/DOSXYZnrc calculations that were considered as the benchmark. Furthermore, two clinical cases of arc deliveries were used to test the accuracy of the dose calculation algorithms against MC. Results: Open field tests in a homogeneous phantom showed good agreement between all dose calculation algorithms and MC. The dose agreement was +/?1.5% for all field sizes and energies. Dose calculation in heterogenous phantoms showed that the agreement between Acuros XB and CCCS was within 2% in the case of lung and bone. AAA calculations showed deviation of approximately 5%. In the case of the air heterogeneity, the differences were larger for all calculations algorithms. The calculation in the patient CT for a lung and bone (paraspinal targets) showed that all dose calculation algorithms predicted the dose in the middle of the target accurately; however, small differences (2% - 5%) were observed at the low dose region. Overall, when compared to MC, the Acuros XB and CCCS had better agreement than AAA. Conclusions: The Acuros XB calculation algorithm in the newest version of the Eclipse treatment planning system is an improvement over the existing AAA algorithm. The results are comparable to CCCS and MC calculations especially for both stylized and clinical cases. Dose discrepancies were observed for extreme cases in the presence of air inhomogeneities.

Keywords

Photon Dose Calculation; Inhomogeneities; Acuros XB

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	T.C. Zhu and B. E. Bjarngard, “The Fraction of Photons Undergoing Head Scatter in X-Ray Beams,” Physics in Medicine and Biology, Vol. 40, No. 6, 1995, pp. 1127-1134. doi:10.1088/0031-9155/40/6/011
[2]	T. C. Zhu and B. E. Bjarngard, “The Head-Scatter Factor for Small Field Sizes,” Medical Physics, Vol. 21, No. 1, 1994, pp. 65-68. doi:10.1118/1.597256
[3]	T. R. Mackie, J. W. Scrimger, J. J. Battista, “A Convolution Method of Calculating Dose for 15-MV X-Rays,” Medical Physics, Vol. 12, No. 2, 1985, pp. 188-196. doi:10.1118/1.595774
[4]	H. A. Al-Hallaq, C. S. Reft and J. C. Roeske, “The Dosimetric Effects of Tissue Heterogeneities in Intensity-Modulated Radiation Therapy (IMRT) of the Head and Neck,” Physics in Medicine and Biology, Vol. 51, No. 5, 2006, pp. 1145-1156. doi:10.1088/0031-9155/51/5/007
[5]	I. J. Chetty, P. M. Charland, N. Tyagi, et al., “Photon Beam Relative Dose Validation of the DPM Monte Carlo Code in Lung-Equivalent Media,” Medical Physics, Vol. 30, No. 4, 2003, pp. 563-573. doi:10.1118/1.1555671
[6]	H. Saitoh, T. Fujisaki, R. Sakai, et al., “Dose Distribution of Narrow Beam Irradiation for Small Lung Tumor,” International Journal of Radiation Oncology, Biology, Physics, Vol. 53, No. 5, 2002, pp. 1380-1387.
[7]	A. L. Boyer and E. C. Mok, “Calculation of Photon Dose Distributions in an Inhomogeneous Medium Using Convolutions,” Medical Physics, Vol. 13, No. 4, 1986, pp. 503-509. doi:10.1118/1.595964
[8]	C. M. Bragg and J. Conway, “Dosimetric Verification of the Anisotropic Analytical Algorithm for Radiotherapy Treatment Planning,” Radiotherapy and Oncology: Journal of the European Society for Therapeutic Radiology and Oncology, Vol. 81, No. 3, 2006, pp. 315-323.
[9]	J. Craig, M. Oliver, A. Gladwish, et al., “Commissioning a Fast Monte Carlo Dose Calculation Algorithm for Lung Cancer Treatment Planning,” Journal of Applied Clinical Medical Physics/American College of Medical Physics, Vol. 9, No. 2, 2008, p. 2702.
[10]	I. M. Gagne and S. Zavgorodni, “Evaluation of the Analytical Anisotropic Algorithm in an Extreme Water-Lung Interface Phantom Using Monte Carlo Dose Calculations,” Journal of Applied Clinical Medical Physics/American College of Medical Physics, Vol. 8, No. 1, 2007, pp. 33-46.
[11]	F. Garcia-Vicente, A. Minambres, I. Jerez, et al., “Experimental Validation Tests of Fast Fourier Transform Convolution and Multigrid Superposition Algorithms for Dose Calculation in Low-Density Media,” Radiotherapy and Oncology: Journal of the European Society for Therapeutic Radiology and Oncology, Vol. 67, No. 2, 2003, pp. 239-249.
[12]	E. Kunieda, H. M. Deloar, N. Kishitani, et al., “Variation of Dose Distribution of Stereotactic Radiotherapy for Small-Volume Lung Tumors under Different Respiratory Conditions,” Physica Medica, Vol. 24, No. 4, 2008, pp. 204-211.
[13]	C. Scholz, C .Schulze and U. Oelfke, et al., “Development and Clinical Application of a Fast Superposition Algorithm in Radiation Therapy,” Radiotherapy and Oncology: Journal of the European Society for Therapeutic Radiology and Oncology, Vol. 69, No. 1, 2003, pp. 79-90.
[14]	L. Tillikainen, H. Helminen, T. Torsti, et al., “A 3D Pencil-Beam-Based Superposition Algorithm for Photon Dose Calculation in Heterogeneous Media,” Physics in Medi- cine and Biology, Vol. 53, No. 14, 2008, pp. 3821-3839. doi:10.1088/0031-9155/53/14/008
[15]	A. Ahnesjo, “Collimator Scatter in Photon Therapy Beams,” Medical Physics, Vol. 22, No. 3, 1995, pp. 267-278. doi:10.1118/1.597450
[16]	G. X. Ding, “Dose Discrepancies between Monte Carlo Calculations and Measurements in the Buildup Region for a High-Energy Photon Beam,” Medical Physics, Vol. 29, No. 11, 2002, pp. 2459-2463. doi:10.1118/1.1514237
[17]	G. X. Ding, D. M. Duggan and C. W. Coffey, “Commissioning Stereotactic Radiosurgery Beams Using Both Experimental and Theoretical Methods,” Physics in Medicine and Biology, Vol. 51, No. 10, 2006, pp. 2549-2566. doi:10.1088/0031-9155/51/10/013
[18]	P. K. Kijewski, B. E. Bjarngard and P. L. Petti, “Monte Carlo Calculations of Scatter Dose for Small Field Sizes in a 60 Co Beam,” Medical Physics, Vol. 13, No. 1, 1986, pp. 74-77. doi:10.1118/1.595925
[19]	T. Han, J. K. Mikell, M. Salehpour, et al., “Dosimetric Comparison of Acuros XB Deterministic Radiation Transport Method with Monte Carlo and Model-Based Convolution Methods in Heterogeneous Media,” Medical Physics, Vol. 38, No. 5, 2011, pp. 2651-2664. doi:10.1118/1.3582690
[20]	A. Fogliata, G. Nicolini, A. Clivio, et al., “On the Dosimetric Impact of Inhomogeneity Management in the Acuros XB Algorithm for Breast Treatment,” Radiation Oncology, Vol. 6, No. 1, 2011, p. 103. doi:10.1186/1748-717X-6-103
[21]	A. Fogliata, G. Nicolini, A. Clivio, et al., “Dosimetric Evaluation of Acuros XB Advanced Dose Calculation Algorithm in Heterogeneous Media,” Radiation Oncology, Vol. 6, No. 1, 2011, p. 82. doi:10.1186/1748-717X-6-82
[22]	K. Bush, I. M. Gagne, S. Zavgorodni, et al., “Dosimetric Validation of Acuros XB with Monte Carlo Methods for Photon Dose Calculations,” Medical Physics, Vol. 38, No. 4, 2011, pp. 2208-2221. doi:10.1118/1.3567146
[23]	D. W. Rogers, B. A. Faddegon, G. X. Ding, et al., “BEAM: A Monte Carlo Code to Simulate Radiotherapy Treatment Units,” Medical Physics, Vol. 22, No. 5, 1995, pp. 503-524. doi:10.1118/1.597552
[24]	B. Walters and I. Kawrakow, “Rogers DWO: DOSXYZnrc User Manual,” NRCC Report PIRS-794revB, 2009.
[25]	A. Gray, L. D. Oliver and P. N. Johnston, “The Accuracy of the Pencil Beam Convolution and Anisotropic Ana- lytical Algorithms in Predicting the Dose Effects Due to Attenuation from Immobilization Devices and Large Air Gaps,” Medical Physics, Vol. 36, No. 7, 2009, pp. 3181-3191. doi:10.1118/1.3147204
[26]	K. Bush, S. Zavgorodni, I. Gagne, et al., “Monte Carlo Evaluation of RapidArc Oropharynx Treatment Planning Strategies for Sparing of Midline Structures,” Physics in Medicine and Biology, Vol. 55, No. 16, 2010, pp. 4465-4479. doi:10.1088/0031-9155/55/16/S03
[27]	P. Carrasco, N. Jornet, M. A. Duch, et al., “Comparison of Dose Calculation Algorithms in Slab Phantoms with Cortical Bone Equivalent Heterogeneities,” Medical Physics, Vol. 34, No. 8, 2007, pp. 3323-3333. doi:10.1118/1.2750972
[28]	P. Dvorak, M. Stock, B. Kroupa, et al., “Analysis of the Dose Calculation Accuracy for IMRT in Lung: A 2D Approach,” Acta Oncologica, Vol. 46, No. 7, 2007, pp. 928-936. doi:10.1080/02841860701253052