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Dosimetric accuracy of Acuros® XB and AAA algorithms for stereotactic body radiotherapy (SBRT) lung treatments: evaluation with PRIMO Monte Carlo code

Published online by Cambridge University Press:  02 December 2022

B. Sarin*
Affiliation:
Department of Physics, Noorul Islam Centre for Higher Education, Kumaracoil, Kanyakumari, Tamil Nadu, India Division of Radiation Physics, Regional Cancer Centre, Thiruvananthapuram, Kerala, India
B. Bindhu
Affiliation:
Department of Physics, Noorul Islam Centre for Higher Education, Kumaracoil, Kanyakumari, Tamil Nadu, India
P. Raghu Kumar
Affiliation:
Division of Radiation Physics, Regional Cancer Centre, Thiruvananthapuram, Kerala, India
S. Sumeesh
Affiliation:
Division of Radiation Physics, Regional Cancer Centre, Thiruvananthapuram, Kerala, India
B. Saju
Affiliation:
Division of Radiation Physics, Regional Cancer Centre, Thiruvananthapuram, Kerala, India
*
Author for correspondence: B. Sarin, Department of Physics, Noorul Islam Centre for Higher Education, Kumaracoil, Kanyakumari, Tamil Nadu, India. E-mail: sreesarin@gmail.com

Abstract

Purpose:

The study aimed to compare the dosimetric performance of Acuros® XB (AXB) and anisotropic analytical algorithm (AAA) for lung SBRT plans using Monte Carlo (MC) simulations.

Methods:

We compared the dose calculation algorithms AAA and either of the dose reporting modes of AXB (dose to medium (AXB-Dm) or dose to water (AXB-Dw)) algorithms implemented in Eclipse® (Varian Medical Systems, Palo Alto, CA) Treatment planning system (TPS) with MC. PRIMO code was used for the MC simulations. The TPS-calculated dose profiles obtained with a multi-slab heterogeneity phantom were compared to MC. A lung phantom with a tumour was used to validate TPS algorithms using different beam delivery techniques. 2D gamma values obtained from Gafchromic film measurements in the tumour isocentre plane were compared with TPS algorithms and MC. Ten VMAT SBRT plans generated in TPS with each algorithm were recalculated with a PRIMO MC system for identical beam parameters for the clinical plan validation. A dose–volume histogram (DVH) based plan comparison and a 3D global gamma analysis were performed.

Results:

AXB demonstrated better agreement with MC and film measurements in the lung phantom validation, with good agreement in PDD, profiles and gamma analysis. AAA showed an overestimated PDD, a significant difference in dose profiles and a lower gamma pass rate near the field borders. With AAA, there was a dose overestimation at the periphery of the tumour. For clinical plan validation, AXB demonstrated higher agreement with MC than AAA.

Conclusions:

AXB provided better agreement with MC than AAA in the phantom and clinical plan evaluations.

Type
Original Article
Copyright
© The Author(s), 2022. Published by Cambridge University Press

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References

Fakiris, AJ, McGarry, RC, Yiannoutsos, CT et al. Stereotactic body radiation therapy for early-stage non–small-cell lung carcinoma: four-year results of a prospective phase II study. Int J Radiat Oncol Biol Phys 2009; 75: 677682.CrossRefGoogle ScholarPubMed
Onishi, H, Shirato, H, Nagata, Y et al. Stereotactic body radiotherapy (SBRT) for operable stage I non–small-cell lung cancer: can SBRT be comparable to surgery? Int J Radiat Oncol Biol Phys 2011; 81: 13521358.CrossRefGoogle Scholar
Khan, F M. The Physics of Radiation Therapy, 4th edition. Philadelphia: Lippincott Williams & Wilkins, 2010.Google Scholar
Ojala, J, Kapanen, M. Quantification of dose differences between two versions of Acuros XB algorithm compared to Monte Carlo simulations – the effect on clinical patient treatment planning. J Appl Clin Med Phys 2015; 16: 213225. https://doi.org/10.1120/jacmp.v16i6.5642.CrossRefGoogle ScholarPubMed
Knöös, T, Wieslander, E, Cozzi, L et al. Comparison of dose calculation algorithms for treatment planning in external photon beam therapy for clinical situations. Phys Med Biol 2006; 51: 57855807. https://doi.org/10.1088/0031-9155/51/22/005.CrossRefGoogle ScholarPubMed
Failla, G A, Wareing, T, Archambault, Y, Thompson, S. Acuros XB Advanced Dose Calculation for the Eclipse Treatment Planning System. Palo Alto, CA: Varian Medical Systems, 2010: 20.Google Scholar
Zhou, C, Bennion, N, Ma, R et al. A comprehensive dosimetric study on switching from a Type-B to a Type-C dose algorithm for modern lung SBRT. Radiat Oncol 2017; 12: 111.CrossRefGoogle Scholar
Han, T, Mikell, JK, Salehpour, M, Mourtada, F. Dosimetric comparison of Acuros XB deterministic radiation transport method with Monte Carlo and model-based convolution methods in heterogeneous media. Med Phys 2011; 38: 26512664. https://doi.org/10.1118/1.3582690.CrossRefGoogle ScholarPubMed
Rana, S, Rogers, K, Lee, T, Reed, D, Biggs, C. Verification and dosimetric impact of Acuros XB algorithm for stereotactic body radiation therapy (SBRT) and RapidArc planning for non-small-cell lung cancer (NSCLC) patients. Int J Med Phys Clin Eng Radiat Oncol 2013; 2: 6.CrossRefGoogle Scholar
Hasenbalg, F, Neuenschwander, H, Mini, R, Born, EJ. Collapsed cone convolution and analytical anisotropic algorithm dose calculations compared to VMC++ Monte Carlo simulations in clinical cases. Phys Med Biol 2007; 52: 3679.CrossRefGoogle ScholarPubMed
Han, T, Mikell, JK, Salehpour, M, Mourtada, F. Dosimetric comparison of Acuros XB deterministic radiation transport method with Monte Carlo and model-based convolution methods in heterogeneous media. Med Phys 2011; 38: 26512664.CrossRefGoogle ScholarPubMed
Vassiliev, ON, Wareing, TA, McGhee, J, Failla, G, Salehpour, MR, Mourtada, F. Validation of a new grid-based Boltzmann equation solver for dose calculation in radiotherapy with photon beams. Phys Med Biol 2010; 55: 581.CrossRefGoogle ScholarPubMed
Fogliata, A, Nicolini, G, Clivio, A, Vanetti, E, Mancosu, P, Cozzi, L. Dosimetric validation of the Acuros XB Advanced Dose Calculation algorithm: fundamental characterization in water. Phys Med Biol 2011; 56: 1879.CrossRefGoogle ScholarPubMed
Bush, K, Gagne, IM, Zavgorodni, S, Ansbacher, W, Beckham, W. Dosimetric validation of Acuros® XB with Monte Carlo methods for photon dose calculations. Med Phys 2011; 38: 22082221. https://doi.org/10.1118/1.3567146.CrossRefGoogle ScholarPubMed
Ojala, JJ, Kapanen, MK, Hyödynmaa, SJ, Wigren, TK, Pitkänen, MA. Performance of dose calculation algorithms from three generations in lung SBRT: comparison with full Monte Carlo-based dose distributions. J Appl Clin Med Phys 2014; 15: 418. https://doi.org/10.1120/jacmp.v15i2.4662.CrossRefGoogle ScholarPubMed
Fogliata, A, Nicolini, G, Clivio, A, Vanetti, E, Cozzi, L. Dosimetric evaluation of Acuros XB advanced dose calculation algorithm in heterogeneous media. Radiat Oncol 2011; 6: 115.CrossRefGoogle ScholarPubMed
Seniwal, B, Bhatt, CP, Fonseca, TCF. Comparison of dosimetric accuracy of acuros XB and analytical anisotropic algorithm against Monte Carlo technique. Biomed Phys Eng Express 2020; 6: 15035.CrossRefGoogle ScholarPubMed
Ojala, J. The accuracy of the Acuros XB algorithm in external beam radiotherapy – a comprehensive review. Int J Cancer Ther Oncol 2014; 2: 020417. https://doi.org/10.14319/ijcto.0204.17.CrossRefGoogle Scholar
Tsuruta, Y, Nakata, M, Nakamura, M et al. Dosimetric comparison of Acuros XB, AAA, and XVMC in stereotactic body radiotherapy for lung cancer. Med Phys 2014; 41: 81715.CrossRefGoogle ScholarPubMed
Muñoz-Montplet, C, Marruecos, J, Buxó, M et al. Dosimetric impact of Acuros XB dose-to-water and dose-to-medium reporting modes on VMAT planning for head and neck cancer. Phys Med 2018; 55: 107115.CrossRefGoogle ScholarPubMed
Moiseenko, V, Liu, M, Bergman, AM et al. Monte Carlo calculation of dose distribution in early stage NSCLC patients planned for accelerated hypofractionated radiation therapy in the NCIC-BR25 protocol. Phys Med Biol 2010; 55: 723.CrossRefGoogle ScholarPubMed
Tsuruta, Y, Nakata, M, Nakamura, M et al. Dosimetric comparison of Acuros XB, AAA, and XVMC in stereotactic body radiotherapy for lung cancer. Med Phys 2014; 41: 19. https://doi.org/10.1118/1.4890592.CrossRefGoogle ScholarPubMed
Zhuang, T, Djemil, T, Qi, P et al. Dose calculation differences between Monte Carlo and pencil beam depend on the tumor locations and volumes for lung stereotactic body radiation therapy. J Appl Clin Med Phys 2013; 14: 3851.CrossRefGoogle ScholarPubMed
Boiset, G R, Batista, D V S, Coutinho, C S. Clinical verification of treatment planning dose calculation in lung SBRT with GATE Monte Carlo simulation code. Phys Med 2021; 87: 110. https://doi.org/10.1016/j.ejmp.2021.05.028.CrossRefGoogle Scholar
Andreo, P. Monte Carlo techniques in medical radiation physics. Phys Med Biol 1991; 36: 861.CrossRefGoogle ScholarPubMed
Verhaegen, F, Seuntjens, J. Monte Carlo modelling of external radiotherapy photon beams. Phys Med Biol 2003; 48: R107.CrossRefGoogle ScholarPubMed
Rodriguez, M, Sempau, J, Brualla, L. PRIMO: a graphical environment for the Monte Carlo simulation of Varian and Elekta linacs. Strahlenther Onkol 2013; 189: 881886.CrossRefGoogle Scholar
Baro, J, Sempau, J, Fernández-Varea, JM, Salvat, F. PENELOPE: an algorithm for Monte Carlo simulation of the penetration and energy loss of electrons and positrons in matter. Nucl Instrum Methods Phys Res B 1995; 100: 3146.CrossRefGoogle Scholar
Sempau, J, Wilderman, SJ, Bielajew, AF. DPM, a fast, accurate Monte Carlo code optimized for photon and electron radiotherapy treatment planning dose calculations. Phys Med Biol 2000; 45: 2263.CrossRefGoogle ScholarPubMed
Brualla, L, et al. PRIMO user’s manual version 0.3.1.1600. www.primoproject.net, 2020, www.primoproject.net/primo/system/files/UserManual.pdf.Google Scholar
Fogliata, A, De Rose, F, Stravato, A, Reggiori, G, Tomatis, S, Scorsetti, M, Cozzi, L. Evaluation of target dose inhomogeneity in breast cancer treatment due to tissue elemental differences. Radiat Oncol 2018; 13(1): 1–7.CrossRefGoogle ScholarPubMed
Rodriguez, M, Brualla, L. Treatment verification using Varian’s dynalog files in the Monte Carlo system PRIMO. Radiat Oncol 2019; 14: 17.CrossRefGoogle ScholarPubMed
Sarin, B, Bindhu, B, Saju, B, Nair, R. Validation of PRIMO Monte Carlo model of clinac® ix 6mv photon beam. J Med Phys 2020; 45: 24. https://doi.org/10.4103/jmp.JMP_75_19.CrossRefGoogle ScholarPubMed
Popescu, IA, Shaw, CP, Zavgorodni, SF, Beckham, WA. Absolute dose calculations for Monte Carlo simulations of radiotherapy beams. Phys Med Biol 2005; 50: 3375.CrossRefGoogle ScholarPubMed
Lewis, D, Micke, A, Yu, X, Chan, MF. An efficient protocol for radiochromic film dosimetry combining calibration and measurement in a single scan. Med Phys 2012; 39: 63396350.CrossRefGoogle Scholar
Low, DA, Harms, WB, Mutic, S, Purdy, JA. A technique for the quantitative evaluation of dose distributions. Med Phys 1998; 25: 656661.CrossRefGoogle ScholarPubMed
Bezjak, A, Papiez, L, Bradley, J et al. NRG oncology RTOG 0813 seamless phase I/II study of stereotactic lung radiotherapy (SBRT) for early stage, centrally located, non-small cell lung cancer (NSCLC) in medically inoperable patients. Update 2012; 3: 1516.Google Scholar
Videtic, GMM, Hu, C, Singh, AK et al. NRG Oncology RTOG 0915 (NCCTG N0927): a randomized phase II study comparing 2 stereotactic body radiation therapy (SBRT) schedules for medically inoperable patients with stage I peripheral non-small cell lung cancer. Int J Radiat Oncol Biol Phys 2015; 93: 757.CrossRefGoogle Scholar
Feuvret, L, Noël, G, Mazeron, J-J, Bey, P. Conformity index: a review. Int J Radiat Oncol Biol Phys 2006; 64: 333342.CrossRefGoogle ScholarPubMed
Paddick, I, Lippitz, B. A simple dose gradient measurement tool to complement the conformity index. J Neurosurg 2006; 105: 194201.CrossRefGoogle ScholarPubMed
Alhakeem, EA, AlShaikh, S, Rosenfeld, AB, Zavgorodni, SF. Comparative evaluation of modern dosimetry techniques near low-and high-density heterogeneities. J Appl Clin Med Phys 2015; 16: 142158.CrossRefGoogle ScholarPubMed
Reggiori, G, Stravato, A, Paganini, L et al. Evaluation of a radiotherapy-dedicated Monte Carlo environment in clinical VMAT plans. Radiother Oncol 2018; 127: 167168. https://doi.org/10.1016/S0167-8140(18)32148-0.CrossRefGoogle Scholar
Mampuya, WA, Matsuo, Y, Nakamura, A et al. Differences in dose-volumetric data between the analytical anisotropic algorithm and the x-ray voxel Monte Carlo algorithm in stereotactic body radiation therapy for lung cancer. Med Dosimetry 2013; 38: 9599. https://doi.org/10.1016/j.meddos.2012.07.007.CrossRefGoogle ScholarPubMed