1. bookVolume 63 (2018): Issue 1 (March 2018)
Journal Details
License
Format
Journal
eISSN
1508-5791
First Published
25 Mar 2014
Publication timeframe
4 times per year
Languages
English
access type Open Access

Dependence of tissue inhomogeneity correction factors on photon-beam energy

Published Online: 01 Mar 2018
Volume & Issue: Volume 63 (2018) - Issue 1 (March 2018)
Page range: 3 - 7
Received: 24 Jan 2017
Accepted: 19 Dec 2017
Journal Details
License
Format
Journal
eISSN
1508-5791
First Published
25 Mar 2014
Publication timeframe
4 times per year
Languages
English
Abstract

Introduction: Commissioning of the treatment-planning system includes the accuracy of dose calculations in the inhomogeneous absorber. Several results of measurements with regard to inhomogeneity correction factors (CFs) have been published. However, the dependence of CFs on photon-beam energy may preclude such results from being applied to the photon beams of general users. Purpose: The aim of this study was to assess the dependence of CFs on the photon-beam energy. Materials and methods: CFs were calculated by the Batho method for several slab geometries comprised of concentrations of lung tissue and water of 0.25 and 1.00 g/cm3, respectively. The CFs were calculated at 6 MV (TPR2010 = 0.67 ± k * 0.01) and 15 MV (TPR2010 = 0.76 ± k * 0.01) where k = -3, -2, -1, 0, 1, 2, 3. All calculations were performed in the region where a charged-particle equilibrium exists. Results: Changes in CFs of less than 2% were observed across the considered energy ranges. With a change in TPR20,10 of 0.01, both at 6 and 15 MV at a depth of 5 cm below the lung; and lung thicknesses of 3, 5 and 8 cm over a fi eld surface area of 10 × 10 cm2, the change in CF never exceeded 2.4%. The dependences of changes in CFs in terms of TPR20,10 were 1.74% and 1.20% for field surface areas of 5 × 5 cm2 and 20 × 20 cm2, respectively. A comparison of 42 linear accelerators (LINACs) exhibiting 6 MV and 15 MV of energy installed in Poland showed that the maximum differences in terms of TPR20,10 at 6 MV and 15 MV were 4.2% and 2.2%, respectively. Conclusion: A linear dependence of CFs on energy was observed. According to observations, the smaller the surface area of the field and deeper the point of interest below the lung, the more dependent CFs are on energy.

Keywords

1. Papanikolaou, N., Battista, J. J., Boyer, A. L., Kappas, C., Klein, E., Mackie, T. R., Sharpe, M., & Van Dyk, J. (2004). Tissue inhomogeneity corrections for megavoltage photon beams. Madison WI: Medical Physics Publishing. (AAPM Report No. 85).10.37206/86Search in Google Scholar

2. Das, I. J., Ding, G. X., & Ahnesjö, A. (2008). Small fi elds: Non-equilibrium radiation dosimetry. Med. Phys., 35(1), 206-215. DOI: 10.1118/1.2815356.10.1118/1.281535618293576Open DOISearch in Google Scholar

3. Robinson, D. (2008). Inhomogeneity correction and the analytic anisotropic algorithm. J. Appl. Clin. Med. Phys., 9(2), 112-122.10.1120/jacmp.v9i2.2786572171018714283Open DOISearch in Google Scholar

4. Ding, W., Johnston, P. N., Wong, T. P. Y., & Bubb, I. F. (2004). Investigation of photon beam models in heterogeneous media of modern radiotherapy. Australas Phys. Eng. Sci., 27, 39-48. DOI: 10.1007/ BF03178375.10.1007/BF0317837515462585Open DOISearch in Google Scholar

5. Carrasco, P., Jornet, N., Duch, M., Weber, L., Ginjaume, M., Endaldo, T., Jurado, D., Ruiz, A., & Ribas, M. (2004). Comparison of dose calculation algorithms in phantoms with lung equivalent heterogeneities under conditions of lateral electronic disequilibrium. Med. Phys., 31, 2899-2911. DOI: 10.1118/1.1788932.10.1118/1.178893215543799Open DOISearch in Google Scholar

6. Krieger, T., & Sauer, O. A. (2005). Monte Carlo versus pencil-beam-/collapsed-cone-dose calculation in a heterogeneous multi-layer phantom. Phys. Med. Biol., 50(5), 859-868. DOI: 10.1088/0031-9155/50/5/010.10.1088/0031-9155/50/5/01015798260Open DOISearch in Google Scholar

7. Van Esch, A., Tillikainen, L., Pyykkonen, J., Tenhunen, M., Helminen, H., Siljamaki, S., Alakuijala, J., Paiusco, M., Iori, M., & Huyskens, D. (2006). Testing of the analytical anisotropic algorithm for photon dose calculation. Med. Phys., 33(11), 4130-4148. DOI: 10.1118/1.2358333.10.1118/1.235833317153392Open DOISearch in Google Scholar

8. Dobler, B., Walter, C., Knopf, A., Fabri, D., Loeschel, R., Polednik, M., Schneider, F., Wenz, F., & Lohr, F. (2006). Optimization of extracranial stereotactic radiation therapy of small lung lesions using accurate dose calculation algorithms. Radiat. Oncol., 1, 45(11pp.). DOI: 10.1186/1748-717X-1-45.10.1186/1748-717X-1-45176938717132177Search in Google Scholar

9. Vanderstraeten, B., Reynaert, N., Paelinck, L., Madani, I., De Wagter, C., De Gersem, W., De Neve, W., & Thierens, H. (2006). Accuracy of patient dose calculation for lung IMRT: A comparison of Monte Carlo, convolution/superposition and pencil beam computations. Med. Phys., 33(9), 3149-3158. DOI: 10.1118/1.2241992.10.1118/1.224199217022207Open DOISearch in Google Scholar

10. Gray, A., Oliver, L. D., & Johnston, P. N. (2009). The accuracy of the pencil beam convolution and anisotropic analytical algorithms in predicting the dose effects due to attenuation from immobilization devices large air gaps. Med. Phys., 36(7), 3181-3191. DOI: 10.1118/1.3147204.10.1118/1.314720419673217Search in Google Scholar

11. Rana, S., Rogers, K., Lee, T., Reed, D., & Biggs, C. (2013). Verifi cation and dosimetric impact of Acuros XB algorithm for stereotactic body radiation therapy (SBRT) and RapidArc planning for non-small-cell lung (NSCLC) patients. Int. J. Med. Phys. Clin. Eng. Radiat. Oncol., 2(1), 6-14. DOI: 10.4236/ ijmpcero.2013.21002.10.4236/ijmpcero.2013.21002Open DOISearch in Google Scholar

12. Han, T., Mourtada, F., Kisling, K., Mikell, J., Followill, D., & Howell, R. (2012). Experimental validation of deterministic Acuros XB algorithm for IMRT and VMAT dose calculations with the Radiological Physics Center’s head and neck phantom. Med. Phys., 39(4), 2193-2202. DOI: 10.1118/1.3692180.10.1118/1.3692180Open DOISearch in Google Scholar

13. Rana, S., & Rogers, K. (2013). Dosimetric evaluation of Acuros XB dose calculation algorithm with measurements in ness for smaller and larger fi eld sizes. Med. Phys., 38, 9-14.10.4103/0971-6203.106600Open DOISearch in Google Scholar

14. Stephen, O. (2013). Dose prediction accuracy of collapsed cone convolution superposition algorithm in a multi-layer inhomogenous phantom. Int. J. Cancer Ther. Oncol., 1(1), 01016(4pp.). DOI: 10.14319/ijcto.0101.6.10.14319/ijcto.0101.6Open DOISearch in Google Scholar

15. El-Khatib, E. E., Evans, M., Pla, M., & Cunningham, J. R. (1989). Evaluation of lung dose correction methods for photon irradiations of thorax phantoms. Int. J. Radiat. Oncol. Biol. Phys., 17, 871-878.10.1016/0360-3016(89)90081-3Open DOISearch in Google Scholar

16. Orton, C. G., Chungbin, S., & Klein, E. E., Gillin, M. T., Schultheiss, T. E., & Sanse, W. T. (1998). Study of lung density corrections in a clinical trial (RTOG 88-08). Radiation Therapy Oncology Group. Int. J. Radiat. Oncol. Biol. Phys., 41(4), 787-794. DOI: 10.1016/S0360-3016(98)00117-5.10.1016/S0360-3016(98)00117-5Search in Google Scholar

17. Batho, H. F. (1964). Lung corrections in cobalt 60 beam therapy. J. Can. Assoc. Radiol., 15, 79-83.Search in Google Scholar

18. Gerbi, B. J. (1991). A mathematical expression for %DD accurate from Co-60 to 24 MV. Med. Phys. , 18(4), 724-726. DOI: 10.1118/1.596666.10.1118/1.596666Open DOISearch in Google Scholar

19. Li, X. A. (1999). Peak scatter factors for high-energy photon beams. Med. Phys., 26(6), 962-966. DOI: 10.1118/1.598489.10.1118/1.598489Open DOISearch in Google Scholar

20. ICRU. (1987). Use of computers in external beam radiotherapy procedures with high-energy photons and electrons. Maryland: ICRU Publications. (ICRU Report No. 42).Search in Google Scholar

21. Ekstrand, K. E., & Barnes, W. H. (1990). Pitfalls in the use of high energy X rays to treat tumors in the lung. Int. J. Radiat. Oncol. Biol. Phys., 18(1), 249-252.10.1016/0360-3016(90)90290-ZOpen DOISearch in Google Scholar

22. Hunt, M. A., Desobry, G. E., Fowble, B., & Coia, L. R. (1997). Effect of low-density lateral interfaces on soft-tissue doses. Int. J. Radiat. Oncol. Biol. Phys., 37(2), 475-482.10.1016/S0360-3016(96)00499-3Open DOISearch in Google Scholar

23. Kornelsen, R. O., & Young, M. E. (1982). Changes in the dose-profi le of a 10 MV x-ray beam within and beyond low-density material. Med. Phys., 9, 114-116. DOI: 10.1118/1.595059.10.1118/1.595059Search in Google Scholar

24. Rice, R. K., Mijnheer, B. J., & Chin, L. M. (1988). Benchmark measurements for lung dose corrections for X-ray beams. Int. J. Radiat. Oncol. Biol. Phys., 15(2), 399-409. DOI: 10.1016/S0360- 3016(98)90022-0.10.1016/S0360-3016(98)90022-0Open DOISearch in Google Scholar

25. Yorke, E., Harisiadis, L., Wessels, B., Aghdam, H., & Altemus, R. (1996). Dosimetric considerations in radiation therapy of coin lesions of the lung. Int. J. Radiat. Oncol. Biol. Phys., 34(2), 481-487.10.1016/0360-3016(95)02036-5Open DOISearch in Google Scholar

26. Young, M. E., & Kornelsen, R. O. (1983). Dose corrections for low-density tissue inhomogeneities and air channels for 10-MV x rays. Med. Phys., 10, 450-455.10.1118/1.5953926888356Search in Google Scholar

27. Lulu, B. A., & Bjärngard, B. E. (1982). A derivation of Batho’s correction factor for heterogeneities. Med. Phys., 9, 907-909. DOI: 10.1118/1.595201.10.1118/1.5952017162477Open DOISearch in Google Scholar

28. El-Khatib, E., & Battista, J. J. (1984). Improved lung dose calculation using tissue-maximum ratios in the Batho correction. Med. Phys., 11(3), 279-286. DOI: 10.1118/1.595495.10.1118/1.5954956429498Open DOISearch in Google Scholar

29. du Plessis, F. C. P., Willemse, C. A., Lötter, M. G., & Goedhals, L. (2001). Comparison of the Batho, ETAR and Monte Carlo dose calculation methods in CT based patient models. Med. Phys., 28(4), 582-589. DOI: 10.1118/1.1357223.10.1118/1.135722311339755Open DOISearch in Google Scholar

30. Sontag, M. R., & Cunningham, J. R. (1977). Corrections to absorbed dose calculations for tissue inhomogeneities. Med. Phys., 4(5), 431-436. DOI: 10.1118/1.59432930.10.1118/1.59432930Open DOISearch in Google Scholar

31. Wong, J. W., & Henkelman, R. M. (1982). Reconsideration of the power-law (Batho) equation for inhomogeneity corrections. Med. Phys., 9(4), 421-430. DOI: 10.1118/1.595098.10.1118/1.5950987110083Open DOISearch in Google Scholar

32. Lulu, B. A., & Bjärngard, B. E. (1982). Batho’s correction factor combined with scatter summation. Med. Phys., 9(3), 372-377. DOI: 10.1118/1.595174.10.1118/1.5951747110065Open DOISearch in Google Scholar

33. Wong, J. W., & Purdy, J. A. (1990). On methods of inhomogeneity corrections for photon transport. Med. Phys., 17(5), 807-814. DOI: 10.1118/1.596555.10.1118/1.5965552233566Open DOISearch in Google Scholar

Recommended articles from Trend MD

Plan your remote conference with Sciendo