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Acuros XB Algorithm vs. Anisotropic Analytical Algorithm: A Dosimetric Study Using Heterogeneous Phantom and Computed Tomography (CT) Data Sets of Esophageal Cancer Patients

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DOI: 10.4236/jct.2013.41019    9,976 Downloads   24,082 Views   Citations

ABSTRACT

Our purpose in this study was to assess the dosimetric impact of the Acuros XB algorithm (AXB), in comparison with Anisotropic Analytical Algorithm (AAA) calculations, for esophageal cancer treatment plans created with RapidArc technique. First, we performed a phantom study by comparing the percent depth dose (PDD) calculated by AXB and AAA against the measured PDD in a slab phantom containing a 2 cmair gap thickness. Second, we performed a clinical study using a computed tomography (CT) data set from 10 esophageal cancer patients. The treatment plans calculated by AXB and AAA were evaluated for planning target volume (PTV) coverage, doses to the PTV and organs at risk (OARs). Dose calculations by the AXB and AAA were done for identical beam parameters. The AXB showed better agreement (within ±0.5%) with measurements than did the AAA (?4.9% to ?6.2%). In comparison to the AAA, the AXB predicted a higher maximum PTV dose (2.0%), but lower mean (1.1%) and minimum (2.5%) PTV doses as well as reduced PTV coverage (9.1%). The averaged mean doses to all OARs predicted by the AXB were lower (up to 3.6%), and the percentage of lungs volume receiving at least 20 and 5 Gy were lower by about 3.6% in the AXB plans compared to the AAA plans. The AXB is more accurate than the AAA for dose predictions when air medium is involved. The use of AXB is more likely to avoid dose overestimation or underestimation for the esophageal cancer treatment plans compared to AAA.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

S. Rana, K. Rogers, S. Pokharel, T. Lee, D. Reed and C. Biggs, "Acuros XB Algorithm vs. Anisotropic Analytical Algorithm: A Dosimetric Study Using Heterogeneous Phantom and Computed Tomography (CT) Data Sets of Esophageal Cancer Patients," Journal of Cancer Therapy, Vol. 4 No. 1, 2013, pp. 138-144. doi: 10.4236/jct.2013.41019.

References

[1] B. Minsky, T. Pajak, R. Ginsberg, T. Pisansky, J. Martenson, R. Komaki, G. Okawara, S. Rosenthal and D. Kelsen “INT 0123 (Radiation Therapy Oncology Group 94-05) Phase III Trial of Combined-Modality Therapy for Esophageal Cancer: High-Dose Versus Standard-Dose Radiation Therapy,” Journal of Clinical Oncology, Vol. 20, No. 5, 2002, pp. 1167-1174. doi:10.1200/JCO.20.5.1167
[2] C. C. Ling, P. Zhang, Y. Archambault, J. Bocanek, G. Tang and T. Losasso, “Commissioning and Quality Assurance of RapidArc Radiotherapy Delivery System,” Journal of Clinical Oncology, Vol. 72, No. 2, 2008, pp. 575-581. doi:10.1016/j.ijrobp.2008.05.060
[3] International Commission on Radiation Units and Measurements (ICRU), “Determination of Absorbed Dose in a Patient Irradiated by Beams of X and Gamma Rays in Radiotherapy Procedures,” ICRU Report, Bethesda, 1976.
[4] B. Fraas, J. Smathers and J. Deye, “Summary and Recommendations of a National Cancer Institute Workshop on Issues Limiting the Clinical Use of Monte Carlo Dose Calculation Algorithms for Megavoltage External Beam Radiation Therapy,” Medical Physics, Vol. 30, No. 12, 2003, pp. 3206-3216. doi:10.1118/1.1626990
[5] O. Vassiliev, T. Wareing, J. McGhee, G. Failla, M. Salehpour and F. Mourtada, “Validation of a New Grid Based Blotzmann Equation Solver for Dose Calculation in Radiotherapy with Photon Beams,” Physics in Medicine and Biology, Vol. 55, No. 3, 2010, pp. 581-598. doi:10.1088/0031-9155/55/3/002
[6] K. Bush, I. M. Gagne, S. Zavgorodni, W. Ansbacher and W. Beckham, “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
[7] A. Fogliata, G. Nicolini, A. Clivio, E. Vanetti, P. Mancosu and L. Cozzi, “Dosimetric Validation of Acuros XB Advanced Dose Calculation Algorithm: Fundamental Characterization in Water,” Physics in Medicine and Biology, Vol. 56, No. 6, 2011, pp. 1879-1904. doi:10.1088/0031-9155/56/6/022
[8] L. Tillikainen, H. Helminen, T. Torsti, S. Siljamaki, J. Alakuijala, J. Pyyry and W. Ulmer, “3D Pencil-Beam-Based Superposition Algorithm for Photon Dose Calculation in Heterogeneous Media,” Physics in Medicine and Biology, Vol. 53, No. 14, 2008, pp. 3821-3839. doi:10.1088/0031-9155/53/14/008
[9] L. Tillikainen, S. Siljam?ki, H. Helminen, J. Alakuijala and J. Pyyry, “Determination of Parameters for a Multiple-Source Model of Megavoltage Photon Beams Using Optimization Methods,” Physics in Medicine and Biology, Vol. 52, No. 5, 2007, pp. 1441-1467. doi:10.1088/0031-9155/52/5/015
[10] T. Han, J. Mikell, M. Salehpour and F. Mourtada, “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
[11] A. Fogliata, G. Nicolini, A. Clivio, E. Vanetti and L. Cozzi, “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
[12] M. Kan, L. Leung and P. Yu, “Verification and Dosimetric Impact of Acuros XB Algorithm on Intensity Modulated Stereotactic Radiotherapy for Locally Persistent Nasopharyngeal Carcinoma,” Medical Physics, Vol. 39, No. 8, 2012, pp. 4705-4714. doi:10.1118/1.4736819
[13] T. Han, F. Mourtada, K. Kisling, J. Mikell, D. Followill and R. Howell, “Experimental Validation of Deterministic Acuros XB Algorithm for IMRT and VMAT Dose Calculations with the Radiological Physics Center’s Head and Neck Phantom,” Medical Physics, Vol. 39, No. 4, 2012, pp. 2193-2202. doi:10.1118/1.3692180
[14] L. Hoffmann, M. Jorgensen, L. Muren and J. Petersen, “Clinical Validation of the Acuros XB Photon Dose Calculation Algorithm, a Grid-Based Boltzmann Equation Solver,” Acta Oncologica, Vol. 51, No. 3, 2012, pp. 376-385. doi:10.3109/0284186X.2011.629209
[15] A. Fogliata, G. Nicolini, A. Clivio, E. Vanetti and L. Cozzi, “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
[16] A. Fogliata, G. Nicolini, A. Clivio, E. Vanetti and L. Cozzi, “Critical Appraisal of Acuros XB and Anisotropic Analytic Algorithm Dose Calculation in Advanced Non-Small-Cell Lung Cancer Treatments,” Journal of Clinical Oncology, Vol. 83, No. 5, 2012, pp. 1587-1595. doi:10.1016/j.ijrobp.2011.10.078
[17] D. M. Robinson, “Inhomogeneity Correction and the Analytic Anisotropic Algorithm,” Journal of Applied Clinical Medical Physics, Vol. 9, No. 2, 2008, pp. 112-122.
[18] K. Breitman, S. Rathee, C. Newcomb, B. Murray, D. Robinson, C. Field, H. Warkentin, S. Connors, M. Mackenzie, P. Dunscombe and G. Fallone, “Experimental Validation of the Eclipse AAA Algorithm,” Journal of Applied Clinical Medical Physics, Vol. 10, No. 2, 2007, pp. 76-92.
[19] A. Van Esch, L. Tillikainen, J. Pyykkonen, M. Tenhunen, H. Helminen, S. Siljam¨aki, J. Alakuijala, M. Paiusco, M. Iori and D. Huyskens, “Testing of the Analytical Anisotropic Algorithm for Photon Dose Calculation,” Medical Physics, Vol. 33, No. 11, 2006, pp. 4130-4148. doi:10.1118/1.2358333

  
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