Hostname: page-component-586b7cd67f-dsjbd Total loading time: 0 Render date: 2024-11-28T16:10:12.601Z Has data issue: false hasContentIssue false
  • English
  • Français

Characterisation of small photon field outputs in a heterogeneous medium using X-ray voxel Monte Carlo dose calculation algorithm

Published online by Cambridge University Press:  23 August 2017

Karthikeyan Nithiyanantham ,
Ganesh K. Mani ,
Sambasivaselli Raju ,
Senniandavar Velliangiri ,
Maniyan Paramasivam ,
Karrthick K. Palaniappan  and
Sandeep Jain
Karthikeyan Nithiyanantham
Affiliation:
Radiation Physics, Kidwai Memorial Institute of Oncology, Bengaluru 560029, Karnataka, India
Ganesh K. Mani*
Affiliation:
Radiation Physics, Kidwai Memorial Institute of Oncology, Bengaluru 560029, Karnataka, India
Sambasivaselli Raju
Affiliation:
Radiation Physics, Kidwai Memorial Institute of Oncology, Bengaluru 560029, Karnataka, India
Senniandavar Velliangiri
Affiliation:
Radiation Physics, Kidwai Memorial Institute of Oncology, Bengaluru 560029, Karnataka, India
Maniyan Paramasivam
Affiliation:
Radiation Physics, Kidwai Memorial Institute of Oncology, Bengaluru 560029, Karnataka, India
Karrthick K. Palaniappan
Affiliation:
Radiation Physics, Kidwai Memorial Institute of Oncology, Bengaluru 560029, Karnataka, India
Sandeep Jain
Affiliation:
Radiation Physics, Kidwai Memorial Institute of Oncology, Bengaluru 560029, Karnataka, India
*
Correspondence to: Ganesh K Mani, Ph.D, Radiation Physics, Kidwai Memorial Institute of Oncology, Hosur Road, Bengaluru 560099, Karnataka, India. Tel: +91 9481289421; E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Aim

To characterise small photon beams using the Monte Carlo dose calculation algorithm for small field ranges in a heterogeneous medium.

Materials and method

An in-house phantom constructed with three different mediums, foam, polymethyl methacrylate and delrin resembling the densities of lung, soft tissue and bone respectively, was used in this study. Photon beam energies of 6 and 15 MV and field sizes of 8×8, 16×16, 24×24, 32×32 and 40×40 mm using X-ray voxel Monte Carlo (XVMC) algorithm using different detectors were validated. The relative output factor was measured in three different mediums having six different tissue interfaces; at the depth of 0, 1, 2 and 3 cm. The planar dose verification was undertaken using gafchromic films and considered dose at the lung and bone medium interfaces. For all the measurements, 104×104 mm was taken as the reference field size. The relative output factor for all other field sizes was taken and compared with planning system calculated values.

Results

From field size 16×16 mm and above, the relative output factors were analysed in bone and soft tissue medium having lung as first medium. The maximum deviations were observed as 1·8 and 1·3% for 6 MV and 2·5 and 1·1% for 15 MV photon beams for bone and soft tissue, respectively. For lung as measurement medium, the maximum deviation of 14·8 and 19·2% were observed and having bone as first medium with 8×8 mm for 6 and 15 MV photon beams, respectively. The fluence verification of dose spectrum for the lung–bone interface scenarios with smaller field sizes were found within 2% of deviation with treatment planning system (TPS).

Conclusion

The accuracy of dose calculations for small field sizes in XVMC-based treatment planning algorithm was studied in different inhomogeneous mediums. It was found that the results correlated with measurement data for field size 16×16 mm and above. Noticeable deviation was observed for the smallest field size of 8×8 mm with interfaces of significant change in density. The observed results demands further analysis of work with smaller field sizes.

Keywords

heterogeneityMonacoMonte Carlosmall field dosimetryXVMC
Type
Original Articles
Information
Journal of Radiotherapy in Practice , Volume 17 , Issue 1 , March 2018 , pp. 114 - 123
Check for updates
Copyright
© Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Alfonso, R, Andreo, P, Capote, R et al. A new formalism for reference dosimetry of small and nonstandard fields. Med Phys 2008; 35: 5179–5186.CrossRefGoogle ScholarPubMed
2. Calvo, O I, Gutiérrez, A N, Stathakis, S, Esquivel, C, Papanikolaou, N. On the quantification of the dosimetric accuracy of collapsed cone convolution superposition (CCCS) algorithm for small lung volumes using IMRT. J Appl Clin Med Phys 2012; 13 (3): 43–59.CrossRefGoogle ScholarPubMed
3. Altman, M B, Jin, J Y, Kim, S et al. Practical methods for improving dose distributions in Monte Carlo-based IMRT planning of lung wall-seated tumors treated with SBRT. J Appl Clin Med Phys 2012; 13 (6): 112–125.Google Scholar
4. Fragoso, M, Wen, N, Kumar, S et al. Dosimetric verification and clinical evaluation of a new commercially available Monte Carlo-based dose algorithm for application in stereotactic body radiation therapy (SBRT) treatment planning. Phys Med Biol 2010; 55 (16): 4445–4464.Google Scholar
5. Rassiah-Szegedi, P, Salter, B J, Fuller, C D, Blough, M, Papanikolaou, N, Fuss, M. Monte Carlo characterization of target doses in stereotactic body radiation therapy (SBRT). Acta Oncol 2006; 45 (7): 989–994.CrossRefGoogle ScholarPubMed
6.Task Group No. 65, the Radiation Therapy Committee of the American Association of Physicists in Medicine. Tissue Inhomogeneity Corrections for Megavoltage Photon Beams. Madison, WI, USA: Medical Physics Publishing, 2004.Google Scholar
7. CF Behrens. Dose build-up behind air cavities for Co-60, 4, 6 and 8 MV. Measurements and Monte Carlo simulations. Phys Med Biol 2006; 51 (22): 5937–5950.Google Scholar
8. Jones, A O, Das, I J. Comparison of inhomogeneity correction algorithms in small photon fields. Med Phys 2005; 32 (3): 766–776.Google Scholar
9. 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 (22): 5785–5807.Google Scholar
10. Davidson, S E, Ibbott, G S, Prado, K L, Dong, L, Liao, Z, Followill, D S. Accuracy of two heterogeneity dose calculation algorithms for IMRT in treatment plans designed using an anthropomorphic thorax phantom. Med Phys 2007; 34 (5): 1850–1857.CrossRefGoogle ScholarPubMed
11. Fogliata, A, Vanetti, E, Albers, D et al. On the dosimetric behaviour of photon dose calculation algorithms in the presence of simple geometric heterogeneities: comparison with Monte Carlo calculations. Phys Med Biol 2007; 52 (5): 1363–1385.Google Scholar
12. Van Kleffens, H F, Mijnheer, B J. Determination of the accuracy of the tissue inhomogeneity correction in some computer planning systems for megavoltage photon beams. In: Cunningham J R, Ragan D, Van Dyk J (eds). Proceedings of the Eighth International Conference on the Use of Computers in Radiation Therapy. Silver Spring, MD: IEEE Computer Society Press, 1984: 45–49.Google Scholar
13. Rustgi, A K, Samuels, A, Rustgi, S N. Influence of air inhomogeneities in radiosurgical beams. Med Dosim 1997; 22 (2): 95–100.Google Scholar
14. Rustgi, S N, Rustgi, A K, Jiang, S B, Ayyangar, K M. Dose perturbation caused by high-density inhomogeneities in small beams in stereotactic radiosurgery. Phys Med Biol 1998; 43 (12): 3509–3518.CrossRefGoogle ScholarPubMed
15.International Atomic Energy Agency Technical Report Series 430. Commissioning and Quality Assurance of Computerized Planning Systems for Radiation Treatment of Cancer. Vienna: International Atomic Energy Agency, 2005.Google Scholar
16. Mijnheer, B, Olszewska, A, Fiorino, C. Quality Assurance of Treatment Planning Systems Practical examples for non IMRT photon beams ESRTO Booklet No. 7 Brussels: European Society for Radiotherapy and Oncology, 2005.Google Scholar
17. International Atomic Energy Agency TECDOC 1583. Commissioning of Radiotherapy Treatment Planning Systems: Testing for Typical External Beam Treatment Techniques. Vienna: International Atomic Energy Agency, 2008.Google Scholar
18. Lopez-Tarjuelo, J, Garcia-Molla, R, Juan-Senabre, X J et al. Acceptance and commissioning of a treatment planning system based on Monte Carlo calculations. Technol Cancer Res Treat 2014; 13 (2): 129–138.Google Scholar
19. IMPAC Medical Systems Inc. Monaco Dose Calculation Technical Reference. Sunnyvale, CA: IMPAC Medical Systems, 2013.Google Scholar
20. Francescon, P, Kilby, W, Satariano, N. Monte Carlo simulated correction factors or output factor measurement with the CyberKnife system—results for new detectors and correction factor dependence on measurement distance and detector orientation. Phys Med Biol 2014; 59 (6): N7–N11.Google Scholar
21. Francescon, P, Kilby, W, Satariano, N, Cora, S. Monte Carlo simulated correction factors for machines specific reference field dose calibration and output factor measurement using fixed and iris collimators on the CyberKnife system. Phys Med Biol 2012; 57 (12): 3741–3758.Google Scholar
22.Role of inhomogeneity corrections in three dimensional photon treatment planning. Photon Treatment Planning Collaborative Working Group. Int J Radiat Oncol Biol 1991; 21: 59-66.Google Scholar
23. Ojala, J J, Kapanen, M K, Hyödynmaa, S J, Wigren, T K, 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 (2): 4–16.Google Scholar
24. Li, J, Galvin, J, Harrison, A, Timmerman, R, Yu, Y, Xiao, Y. Dosimetric verification using monte carlo calculations for tissue heterogeneity-corrected conformal treatment plans following RTOG 0813 dosimetric criteria for lung cancer stereotactic body radiotherapy. Int J Radiat Oncol Biol Phys 2012; 84 (2): 508–513.CrossRefGoogle ScholarPubMed
25. Li, X A, Yu, C, Holmes, T. A systematic evaluation of air cavity dose perturbation in megavoltage x-ray beams. Med Phys 2000; 27 (5): 1011–1017.CrossRefGoogle ScholarPubMed
26. Petoukhova, A L, van Wingerden, K, Wiggenraad, R G et al. Verification measurements and clinical evaluation of the iPlan RT Monte Carlo dose algorithm for 6 MV photon energy. Phys Med Biol 2010; 55 (16): 4601–4614.Google Scholar
27. Benmakhlouf, H, Sempau, J, Andreo, P. Output correction factors for nine small field detectors in 6 MV radiation therapy photon beams: a PENELOPE Monte Carlo study. Med Phys 2014; 41 (4): 041711.CrossRefGoogle Scholar