Evaluation of Dosimetric and Radiobiological Parameters for Different TPS Dose Calculation Algorithms and Plans for Lung Cancer Radiotherapy
DOI:
https://doi.org/10.22399/ijcesen.335Keywords:
Monte Carlo Algorithm ConvolutionSuperpositionAlgorithm AnisotropicAnalytical Algorithm Normal Tissue Complication Equvilant Unifotm DoseAbstract
Lung cancer presents a major public health concern in our country and around the globe. Radiotherapy is one of the main treatment modalities for lung cancer management for several years. This study aims to evaluate differences in the dosimetric and radiobiological parameters and in the dose distributions of Planning Target Volume (PTV) and organs at risk (OAR) in patients with lung tumors using different Treatment Planning System (TPS) algorithms and Volumetric Modulated Arc Therapy (VMAT) technique. This study was accomplished in a group of 19 patients with lung tumors who were treated in our clinic. In the treatment planning of the patients; Elekta-Monaco with Monte Carlo (XVMC), Pencil Beam algorithm; Varian-Eclipse with Anisotropic Analytical Algorithm (AAA), Acuros XB (AXB)algorithms and Tomo-plan Treatment Planning System with Convolution Superposition algorithm of Tomotherapy device were used. In these treatment planning systems, plans were done by 6 MV photon energy using Volumetric Arc Therapy (VMAT) techniques. The prescribed dose to the PTV was 60 Gy in 30 fractions. Statistical analysis was performed using SPSS Statistics v.29.0.2.0 programme. Statistically, significant differences were found in Dmean, Dmax, D2 and D98 values for PTV between the algorithms, while small differences were found in Dmax values of the contralateral lung, total lung and esophagus in critical organs. It is concluded that the difference between algorithms for PTV increases especially as the volume of the target tumor decreases. TPS with C/S algorithm gave closer results with XVMC. Algorithms were found to have an impact on radiobiological parameters.
References
American cancer Society (2023) https://www.cancer.org/research/cancer-facts-statistics/all-cancer-facts-figures/2023-cancer-facts-figures.html
Grills IS, Yan D, Martinez AA, Vicini FA, Wong JW (2003) Potential for reduced toxicity and dose escalation in the treatment of inoperable non-small cell lung cancer: A comparison of intensity-modulated radiation therapy (IMRT), 3D conformal radiation, and elective nodal irradiation. Int J Radiat Oncol Biol Phys 57: 875-890.doi:10.1016/S0360-3016(03)00743-0
Bezjak A, Rumble RB, Rodrigues G, Hope A (2012) Intensitymodulated radiotherapy in the treatment of lung cancer. Clin Oncol 24: 508-520. doi.org/10.1016/j.semradonc.2014.11.002
-4296/
H. Murshed, H. H. Liu, Z. Liao et al.(200) , Dose and volume reduction for normal lung using intensity-modulated radiotherapy for advanced-stage non-small-cell lung cancer. International Journal of Radiation Oncology Biology Physics, vol. 58, no. 4, pp. 1258–1267. doi:10.1016/j.ijrobp.2003.09.08
International Commission on Radiation Units and Measurements (ICRU). Determination of absorbed dose in a patient irradiated by beams of X or gamma rays in radiotherapy procedures. ICRU Report 24. Washington (DC): ICRU, 1976: 67.
C. Bosse, G.Narayanasamy et al (2020). Dose Calculations Comparisons Between Three Modern Treatment Planning Systems. Dose Calculation Comparisons between Three Modern Treatment Planning Systems. J Med Phys.Jul-Sep; 45(3):143–147. doi:10.4103/jmp.JMP_111_19
Knöös T, Wieslander E, Cozzi L, Brink C, Fogliata A, Albers D, Nyström H, Lassen S. (2006) Comparison of dose calculation algorithms for treatment planning in external photon beam therapy for clinical situations. Phys Med Biol; 51: 5785-5807 .DOI: 10.1088/0031-9155/51/22/00
Esch AV, Tillikainen L, Pyykkonen J, Tenhunen Mikko, Helminen H, Siljamäki S, et al. (2006); Testing of the analytical anisotropic algorithm for photon dose calculation. Med Phys 33(11):4130–48.doi: 10.1118/1.2358333
Chow JC, Leung MK, Van Dyk J. (2009) Variations of lung density and geometry on inhomogeneity correction algorithms: a Monte Carlo dosimetric evaluation. Med Phys; 36(8): 3619–30.doi: 10.1118/1.3168966
Ojala J. (2014) The accuracy of the Acuros XB algorithm in external beam radiotherapy – a comprehensive review. Int J Cancer Ther Oncol;2(4):020417.doi:10.14319/ijcto.0204.17
Tsuruta Y, Nakata M, Nakamura M, Matsuo Y, Higashimura K, Monzen H, et al.(2014). Dosimetric comparison of Acuros XB, AAA, XVMC in stereotactic body radiotherapy.Med Phys;41(8):081715. doi: 10.1118/1.4890592
NCCN Guidelines Version 2.2024 Non-Small Cell Lung Cancer.
AAPM Task Group 218 Analysis of clinical patient-specifc pre-treatment quality assurance with the new helical tomotherapy platform, following the AAPM TG-218 report (2021). doi:10.1186/s13014-021-01952
N. Dogan, B. J. Mijnheer et al.AAPM (2023). Task Group 307: Use of EPIDs for Patient-Specific IMRT and VMAT QA.
S.L. Gulliford, M. Partridge, M.R. Sydes, S. Webb, P.M. Evans and D.P. Dearnaley (2012). Parameters for the Lyman Kutcher Burman (LKB) model of Normal Tissue Complication Probability (NTCP) for specific rectal complications observed in clinical practise, Radiother Oncol 102(3) 347–351.
D. Wook Kim, K. Park , H. Kim , J.Kim (2020). History of the Photon Beam Dose Calculation Algorithm in Radiation Treatment Planning System. Medical Physics 31(3), https://doi.org/10.14316/pmp.2020.31.3.54.
Hasenbalg F, Neuenschwander H, Mini R, Born EJ (2007). Collapsed cone convolution and analytical anisotropic algorithm dose calculations compared to VMC++ Monte Carlo simulations in clinical cases. Physics in Medicine & Biology; 52:3679. DOI: 10.1088/0031-9155/52/13/002
M.Mazonakis E. Tzanis, E. Lyraraki and John Damilakis (2022). Automatic Radiobiological Comparison of Radiation Therapy Plans: An Application to Gastric Cancer Cancers, 14, 6098. doi.org/10.3390/cancers1424609.
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