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Modelling the effects of lung cancer motion due to respiration

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Background and objectives: To justify the concept of validating conformal versus intensity-modulated approach in the treatment of non-small cell lung cancer (NSCLC). Materials and methods: For 10 patients representative of the spectrum of tumour sizes and locations, two plans were prepared: one with three-dimensional conformal radiation therapy (3DCRT) technique and the other with intensity-modulated radiation therapy (IMRT) technique. Preliminary measurements were performed in static conditions. For each of the field angles considered, the motion kernel was generated to simulate tumour motion trajectories, with the largest amplitude in the cranio-caudal direction of 4, 6, and 8 mm. The measurement results determined the agreement between the planned and measured doses. Results: No statistically significant differences were found between the motion patterns, with the smallest amplitudes for clinical target volume in 3DCRT. For IMRT, the significant differences between 0 mm vs. 6 mm and 0 mm vs. 8 mm amplitudes were found. The motion impact on delivered vs. planned doses had less effect on the oesophagus in 3DCRT compared to that in IMRT. The observed differences were comparable for the heart. Interpretation and conclusions: For maximal amplitudes below 4 mm, the disagreement between planned and delivered doses can be neglected. However, the amplitudes above 5 mm and 7 mm lead to significant changes in IMRT and 3DCRT dose distribution, respectively.
Czasopismo
Rocznik
Strony
95--103
Opis fizyczny
Bibliogr. 33 poz., rys.
Twórcy
autor
  • Medical Physics Department Greater Poland Cancer Centre 15 Garbary St., 61-866 Poznan, Poland
autor
  • Medical Physics Department Greater Poland Cancer Centre 15 Garbary St., 61-866 Poznan, Poland
  • IntraOp Medical, 570 Del Rey Ave, 94085 Sunnyvale, CA, USA
  • Medical Physics Department Greater Poland Cancer Centre 15 Garbary St., 61-866 Poznan, Poland
  • Department of Electroradiology, University of Medical Sciences, 15 Garbary St., 61-866 Poznan, Poland
Bibliografia
  • 1. Lambin, P., Petit, S. F., Aerts, H. J. W. L., van Elmpt, W. J. C., Oberije, C. J. G., Starmans, M. H. W., van Stiphout, R. G. P. M., van Dongen, G. A. M. S., Muylle, K., Flamen, P., Dekker, A. L. A. J., & De Ruysscher, D. (2010). The ESTRO Breur Lecture 2009. From population to voxel-based radiotherapy:Exploiting intra-tumour and intra-organ heterogeneity for advanced treatment of non-small cell lung cancer. Radiother. Oncol., 96, 145–152. DOI: 10.1016/j.radonc.2010.07.001.
  • 2. Isa, N. (2014). Evidence based radiation oncology with existing technology. Rep. Pract. Oncol. Radiother., 19, 259–266. DOI: 10.1016/j.rpor.2013.09.002.
  • 3. Pan, T., Lee, T. Y., Rietzel, E., & Chen, G. T. (2004). 4D-CT imaging of a volume influenced by respiratory motion on multi-slice CT. Med. Phys., 31, 333–3340.DOI: 10.1118/1.1639993.
  • 4. Ehler, E. D., & Tomé, W. A. (2009). Step and shoot IMRT to mobile targets and techniques to mitigate the interplay effect. Phys. Med. Biol., 54, 4311–4324.DOI: 10.1088/0031-9155/54/13/023.
  • 5. Nelms, B. E., Opp, D., Zhang, G., Moros, E., & Feygelman, V. (2014). Motion as perturbation. II. Development of the method for dosimetric analysis of motion effects with fi xed-gantry IMRT. Med. Phys., 41, 061704. DOI: 10.1118/1.4873691.
  • 6. Bortfeld, T., Jokivarsi, K., Goitein, M., Kung, J., & Jiang, S. B. (2002). Effects of intra-fraction motion on IMRT dose delivery: statistical analysis and simulation. Phys. Med. Biol., 47, 2203–2220. DOI: http://dx.doi.org/10.1088/0031-9155/47/13/302.
  • 7. Sterpin, E., Janssens, G., de Xivry, J. O., Goossens,S., Wanet, M., Lee, J. A., Delor, A., Bol, V., Vynckier, S., Gregoire, V., & Geets, X. (2012). Helical tomotherapy for SIB and hypo-fractionated treatments in lung carcinomas: A 4D Monte Carlo treatment planning study. Radiother. Oncol., 104, 173–180. DOI: 10.1016/j.radonc.2012.06.005.
  • 8. Keall, P. J., Mageras, G. S., Balter, M. J., Emery, R. S., Forster, K. M., Jiang, S. B., Kapatoes, J. M., Low, D. A., Murphy, M., Murray, B. R., Ramsey, C. R., van Herk, M., Vedam, S. S., Wong, J. W., & Yorke, E. (2006). The management of respiratory motion in radiation oncology report of AAPM Task Group 76. Med. Phys., 33, 3874–3900. DOI: 10.1118/1.2349696.
  • 9. Tudor, G. S. J., Harden, S. V., & Thomas, S. J. (2014). Three-dimensional analysis of the respiratory interplay effect in helical tomotherapy: Baseline variations cause the greater part of dose inhomogeneities seen. Med. Phys., 41, 031704. DOI: 10.1118/1.4864241.
  • 10. Adamczyk, M., & Piotrowski, T. (2017). Respiratory motion and its compensation possibilities in the modern external beam radiotherapy of lung cancer. Nowotwory J. Oncol., 67, 292–296. DOI: 10.5603/NJO.2017.0048.
  • 11. Ehrhardt, J., Werner, R., Säring, D., Frenzel, T., Lu, W., Low, D., & Handels, H. (2007). An optical flow based method for improved reconstruction of 4D CT data sets acquired during free breathing. Med. Phys., 34, 711–721. DOI: 10.1118/1.2431245.
  • 12. Bai, L., Zhao, J., Yu, H., Zhao, N., Liu, D., Zhong, W., & Zhao, Y. (2013). The CD36 dynamic change after radiation therapy in lung cancer patients and its correlation with symptomatic radiation pneumonitis. Radiother. Oncol., 107, 389–391. DOI: 10.1016/j.radonc.2013.04.014.
  • 13. Farr, K. P., Khalil, A. A., Knap, M. M., Møller, D. S., & Grau, C. (2013). Development of radiation pneumopathy and generalised radiological changes after radiotherapy are independent negative prognostic factors for survival in non-small cell lung cancer patients. Radiother. Oncol., 107, 382–388. DOI: 10.1016/j.radonc.2013.04.024.
  • 14. Piotrowski, T., Matecka-Nowak, M., & Milecki, P. (2005). Prediction of radiation pneumonitis: dose volume histogram analysis in 62 patients with non-small cell lung cancer after three dimensional conformal radiotherapy. Neoplasma, 52, 56–62.
  • 15. Maciejczyk, A., Skrzypczyńska, I., & Janiszewska, M. (2014). Lung cancer. Radiotherapy in lung cancer: Actual methods and future trends. Rep. Pract. Oncol. Radiother., 19, 353–360. DOI: 10.1016/j.rpor.2014.04.012.
  • 16. Peguret, N., Dahele, M., Cuijpers, J. P., Slotman, B. J., & Verbakel, W. F. (2013). Frameless high dose rate stereotactic lung radiotherapy: Intrafraction tumor position and delivery time. Radiother. Oncol., 107, 419–422. DOI: 10.1016/j.radonc.2013.04.019.
  • 17. Kępka, L., Bujko, K., Bujko, M., Matecka-Nowak, M., Sałata, A., Janowski, H., Rogowska, D., Cieślak-Żerańska, E., Komosińska, K., & Zawadzka, A. (2013). Target volume for postoperative radiotherapy in non-small cell lung cancer: results from a prospective trial. Radiother. Oncol., 108, 61–65. DOI: 10.1016/j.radonc.2013.05.023.
  • 18. Din, O. S., Harden, S. V., Hudson, E., Mohammed, N., Pemberton, L. S., Lester, J. F., Biswas, D., Magee, L. O., Tufail, A., Carruthers, R., Sheikh, G., Gilligan, D., & Hatton, M. Q. F. (2013). Accelerated hypo-fractionated radiotherapy for non small cell lung cancer: Results from 4 UK centres. Radiother. Oncol., 109, 8–12. DOI: 10.1016/j.radonc.2013.07.014.
  • 19. Filippi, A. R., Franco, P., & Ricardi, U. (2014). Is stereotactic ablative radiotherapy an alternative to surgery in operable stage I non-small cell lung cancer? Rep. Pract. Oncol. Radiother., 19, 275–279. DOI: 10.1016/j.rpor.2013.05.005.
  • 20. Marks, L. B., Yorke, E. D., Jackson, A., Ten Haken, R. T., Constine, L. S., Eisbruch, A., Bentzen, S. M., Nam, J., & Desay, J. O. (2010). The use of normal tissue complication probability (NTCP) models in the clinic. Int. J. Radiat. Oncol. Biol. Phys., 76, S10–S19.DOI: 10.1016/j.ijrobp.2009.07.1754.
  • 21. Ehler, E. D., Nelms, B. E., & Tomé, W. A. (2007). On the dose to a moving target while employing different IMRT delivery mechanisms. Radiother. Oncol., 83, 49–56. DOI: 10.1016/j.radonc.2007.02.007.
  • 22. Adamczyk, S., Piotrowski, T., & Adamczyk, M. (2013). Dose distribution verification in a moving target using moving platform and 2D diode array. Med. Phys., 40(6,Pt.14), S255. DOI: https://doi.org/10.1118/1.4814658.
  • 23. Gendrin, C., Furtado, H., Weber, C., Bloch, C., Figl, M., Pawiro, S. A., Bergmann, H., Stock, M., Fichtinger, G., Georg, D., & Birkfellner, W. (2012). Monitoring tumor motion by real time 2D/3D registration during radiotherapy. Radiother. Oncol., 102, 274–280. DOI: 10.1016/j.radonc.2011.07.031.
  • 24. Udrescu, C., Jalade, P., de Bari, B., Michel-Amadry, G., & Chapet, O. (2012). Evaluation of the respiratory prostate motion with four-dimensional computed tomography scan acquisitions using three implanted markers. Radiother. Oncol., 103, 266–269. DOI: 10.1016/j.radonc.2012.03.016.
  • 25. Low, D. A., Harms, W. B., Mutic, S., & Purdy, J. A. (1998). A technique for the quantitative evaluation of dose distributions. Med. Phys., 25, 656–661. DOI: 10.1118/1.598248.
  • 26. Cai, J., Malhotra, H. K., & Orton, C. G. (2014). A 3D-conformal technique is better than IMRT or VMAT for lung SBRT. Med. Phys., 41, 040601. DOI: 10.1118/1.4856175.
  • 27. Chui, C. S., Yorke, E., & Hong, L. (2003). The effects of intra-fraction organ motion on the delivery of intensity-modulated field with a multileaf collimator. Med. Phys., 30, 1736–1746. DOI: 10.1118/1.1578771.
  • 28. Kang, H., Yorke, E. D., Yang, J., Chui, C. S., Rosenzweig, K. E., & Amols, H. I. (2010). Evaluation oftumor motion effects on dose distribution for hypofractionated intensity-modulated radiotherapy of non-small-cell lung cancer. J. Appl. Clin. Med. Phys., 1(3), 78–89.
  • 29. Jiang, S. B., Pope, C., Jarrah, K. M., Kung, J. H., Bortfeld, T., & Chen, G. T. (2003). An experimental investigation on intra-fractional organ motion effects in lung IMRT treatments. Phys. Med. Biol., 48, 1773–1784. DOI: https://dx.doi.org/10.1088/0031-9155/48/12/307.
  • 30. Court, L. E., Wagar, M., Ionascu, D., Berbeco, R., & Chin, L. (2008). Management of the interplay effect when using dynamic MLC sequences to treat moving targets. Med. Phys., 35(5), 1926–1931. DOI: 10.1118/1.2896083.
  • 31. Ge, Y., O’Brien, R. T., Shieh, C. C., Booth, J. T.,& Keall, P. J. (2014). Toward the development of intrafraction tumor deformation tracking using a dynamic multi-leaf collimator. Med. Phys., 41, 061703. DOI: 10.1118/1.4873682.
  • 32. Erridge, S. C., Seppenwoolde, Y., Muller, S. H., vanHerk, M., De Jaeger, K., Belderbos, J. S. A., Boersma, L. J., & Lebesque, J. V. (2003). Portal imaging to assess set-up errors, tumor motion and tumor shrinkage during conformal radiotherapy of non-small cell lung cancer. Radiother. Oncol., 66, 75–85. DOI: http://dx.doi.org/10.1016/S0167-8140(02)00287-6.
  • 33. White, B. M., Santhanam, A., Thomas, D., Min, Y., Lamb, J. M., Neylon, J., Jani, S., Gaudio, S., Srinivasan, S., Ennis, D., & Low, D. A. (2014). Modeling and incorporating cardiac-induced lung tissue motion in a breathing motion model. Med. Phys., 41, 043501.DOI: 10.1118/1.4866888.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-21db68b3-5b2b-4671-90dc-21c2036a027b
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