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2012 | 18 | 2 | 49-58
Article title

Intensity modulated radiotherapy using Monte Carlo for routine postmastectomy radiotherapy

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EN
Abstracts
EN
Radiotherapy given after mastectomy (PMRT) will reduce the risk of local recurrence by about two-thirds. Clinical and dosimetric trials were carried out using various techniques to optimize the treatments by maximizing the dose to the tumour and minimizing it to the healthy tissues at proximity. Different conventional techniques which have been studied suffer from important dose inhomogeneities due to the complex anatomy of the chest, which reduces the benefits from such treatments. Moreover, due to the heterogeneity of breast cancer, the response to therapy and a systematic approach to treatment cannot be derived and treatment regimens must be determined on a patient-by-patient basis. This is only possible if accurate and fast treatment planning systems are available. Intensity Modulated Radiotherapy (IMRT) allows delivering higher doses to the target volume and limits the doses to the surrounding tissues. The objective of this study is to test the feasibility of applying a Monte Carlo-based treatment planning system, Hyperion accurately in routine Intensity Modulated Radiotherapy (IMRT) postmastectomy. In order to use a treatment planning system for routine work it should prove to provide optimized dose delivery in a suitable time. Treatment planning for IMRT application to PMRT was performed using Hyperion. Constraints were set to deliver the prescribed dose to the target and minimize the dose to the organs at risk. Dose Volume Histograms (DVH) were used to evaluate the set up plans. Time taken to optimize the plan was measured. The target coverage was within the accepted values. Approximately 90% of the breast and 80% of the PTV received 45 Gy or above. The volume of the lung that received 40Gy was less than 10% and the volume that received 20Gy (V20) was less than 25%. The volume of the heart receiving 30 Gy (V30) or above was negligible. This indicates low NTCP of these organs. The time taken for optimization, showed it possible to apply Monte Carlo-based treatment-planning systems for patient-to-patient PMRT.
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Year
Volume
18
Issue
2
Pages
49-58
Physical description
Dates
published
1 - 06 - 2012
online
29 - 03 - 2013
Contributors
References
  • [1] Alber, M. and F. Nusslin, 1999. An objective function for radiation treatment optimization based on local biological measures. Phys Med Biol, 44:479-493[Crossref]
  • [2] Alber, M., M. Birkner, W. Laub and F. Nusslin, 2000. Hyperion: An integrated IMRT planning tool. Proceedings of the XIII Conference on the use of Computers in Radiationtherapy. Hrsg. W. Schlegel, T. Bortfeld. Springer, Heidelberg, pp:46-48
  • [3] Carolyn, W., T.A. Nisbet, P. Mcgale and S.C. Darby, 2007. Cardiac exposures in breast cancer radiotherapy: 1950s-1990s. Int. J Radiation Oncology Biol Phys, 69:1484-1495
  • [4] Clenton, S.J.. P.M. Fisher, J. Conway, P. Kirkbride and M.K. Hatton, 2005. The use of lung dose-volume histograms in predicting post-radiation Pneumonitis after non-conventionally fractionated radiotherapy for Thoracic Carcinoma. Clinical Oncology, 17:599-603[Crossref]
  • [5] Early Breast Cancer Trialists’ Collaborative Group (EBCTCG), 2005. Effects of radiotherapy and of differences in the extent of surgery for early breast cancer on local recurrence and 15-year survival: an overview of the randomized trials LANCET, 366:2087-2106
  • [6] Fippel, M., M. Alber, M. Birkner, W. Laub and F. Nϋsslin et al., 2001. Inverse treatment planning for radiation therapy based on fast Monte Carlo Dose calculation 2000 From: Advanced Monte Carlo for radiation physics, particle transport simulation and applications. Proceedings of the Monte Carlo 2000 Conference, Lisbon. Springer Berlin
  • [7] Fogliata, A.A., G.G. Nicolini, M.M. Alber, M.M. Asell and B.B. Dobler et al., 2005. IMRT for breast. Planning Study Radiother Oncol, 76:300-10. PMID 16153730
  • [8] Gagliardi, G., I. Lax, S. Soderstrom, G. Gyenes and LE. Rutqvist, 1998. Prediction of excess risk of long-term cardiac mortality after radiotherapy of stage I breast cancer. Radiother Oncol, 46:63-71
  • [9] Graham, M.V., J.A. Purdy, B. Emami, W. Harms and W. Bosch et al., 1999. Clinical dose-volume histogram analysis for pneumonitis after 3D treatment for Non-Small Cell Lung Cancer (NSCLC). Int. J. Radiation Oncology Biol Phys, 45:323-329[Crossref]
  • [10] Johansson, S., H. Svensson and J. Denekamp, 2002. Dose response and latency for radiation-induced fibrosis, edema and neuropathy in Breast Cancer patients. Int. J. Radiation Oncology Biol Phys, 52:1207-1219[Crossref]
  • [11] Krueger, E.A., M.J. Schipper, T. Koelling, R.B. Marsh and J.B. Butler et al., 2004. Cardiac chamber and coronary artery doses associated with postmastectomy radiotherapy techniques to the chest wall and regional nodes. Int. J. Radiation Oncology Biol Phys, 60:1195-1203[Crossref]
  • [12] Laub, W., M. Alber, M. Birkner and F. Nusslin, 2000. Monte Carlo dose computation for IMRT optimization. Phys Med Biol, 45:1741-1754[Crossref]
  • [13] Papanikolaou, N., J.J. Battista, A.L. Boyer, C. Kappas and E. Klein et al., 2004. AAPM Report 85: Tissue inhomogeneity corrections for megavoltage photon beams Report of Task Group No. 65 of the Radiation Therapy Committee of the American Association of Physicists in Medicine 2004
  • [14] Sohn, M., M. Brinker, Y. Chi, J. Wand and D. Yan et al., 2008. Modelindependent, multimodality deformable image registration by local matching of anatomical features and optimization of elastic energy. Med Phys, 35:866-878[Crossref][WoS]
Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.-psjd-doi-10_2478_v10013-012-0007-x
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