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Comparison of Monte Carlo with pencil beam dosimetry for lung CyberKnife SBRT, correlation with local recurrence

  • Original Research
  • Published:
Journal of Radiation Oncology

Abstract

Object

Promising results have been obtained using stereotactic body radiation therapy (SBRT) for early-stage lung cancer. The calculation of dose in pulmonary parenchyma can be inaccurate.

Methods

We retrospectively analyzed 47 cases treated over a 2-year period with CyberKnife SBRT, planned with the standard pencil beam (PB) algorithm. Cases were a mixture of early-stage lung cancer and oligometastatic cases. The median prescribed dose was 50 Gy, in four or five fractions. We compared the planned dose with the dose actually delivered, as estimated with Monte Carlo (MC) dosimetry to the 1 % level. We correlated the dosimetric deficiencies with recurrences, using deformable registration to determine the dose delivered to the site of recurrence.

Results

With a median follow-up of 2 years, the local control at 1 year was 90 %, declining to 70 % at 2 years. The total number of local recurrences was 10, and 8 of these died with progressive disease. Two recurrences occurred synchronously with metastases, and 2 recurrences were in palliative cases treated to lesser doses with tight margins, and disease was never cleared locally. Monte Carlo calculations showed that the mean dose delivered to the planning target volume (PTV), averaged over all cases, was 7 % lower than planned. Most cases were planned with an expansion on the PTV (PTVmicro = GTV + 8 mm expansion in the lung + 3 mm) representing a region at risk for microscopic extension and intended to receive a minimum dose of 80 % of the prescription dose. Monte Carlo calculations showed that the minimum dose to this structure, averaged over all cases, was 47 % lower than the intended dose. For cases that recurred, the mean dose to the PTVmicro was 8 % lower than intended, while only 2 % low for those controlled. There were no other significant differences in target coverage between patients with local control and local recurrence. The PB algorithm and MC estimates for pulmonary exposure were assessed, recording the V5, V10, and V20 for the ipsilateral and total lung volumes. These estimates roughly agreed for the two algorithms, with the MC results almost universally lower than PB, lower by an absolute 1–3 % on average.

Conclusions

Without the use of MC planning, target structures were substantially underdosed. Local failures were associated with PTVmicro undercoverage, which suggests delivering a therapeutic dose to this expanded microscopic disease target volume is beneficial. MC dosimetry is preferable for lung SBRT, while the PB algorithm was adequate for predicting pulmonary toxicity.

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References

  1. Brown WT, Wu X, Fayad F, Fowler JF, Garcia S, Monterroso MI, de la Zerda A, Schwade JG (2009) Application of robotic stereotactic radiotherapy to peripheral stage I non-small cell lung cancer with curative intent. Clinical oncology 21(8):623–631. doi:10.1016/j.clon.2009.06.006

    Article  CAS  PubMed  Google Scholar 

  2. Brown WT, Wu X, Wen BC, Fowler JF, Fayad F, Amendola BE, Garcia S, De La Zerda A, Huang Z, Schwade JG (2007) Early results of CyberKnife image-guided robotic stereotactic radiosurgery for treatment of lung tumors. Computer aided surgery : official journal of the International Society for Computer Aided Surgery 12(5):253–261. doi:10.3109/10929080701684754

    Article  Google Scholar 

  3. Nuyttens JJ, Prevost JB, Praag J, Hoogeman M, Van Klaveren RJ, Levendag PC, Pattynama PM (2006) Lung tumor tracking during stereotactic radiotherapy treatment with the CyberKnife: marker placement and early results. Acta Oncol 45(7):961–965. doi:10.1080/02841860600902205

    Article  CAS  PubMed  Google Scholar 

  4. Whyte RI, Crownover R, Murphy MJ, Martin DP, Rice TW, DeCamp MM Jr, Rodebaugh R, Weinhous MS, Le QT (2003) Stereotactic radiosurgery for lung tumors: preliminary report of a phase I trial. The Annals of thoracic surgery 75(4):1097–1101

    Article  PubMed  Google Scholar 

  5. Disher B, Hajdok G, Gaede S, Battista JJ (2012) An in-depth Monte Carlo study of lateral electron disequilibrium for small fields in ultra-low density lung: implications for modern radiation therapy. Phys Med Biol 57(6):1543–1559

    Article  CAS  PubMed  Google Scholar 

  6. Altunbas C, Kavanagh B, Dzingle W, Stuhr K, Gaspar L, Miften M (2013) Dosimetric errors during treatment of centrally located lung tumors with stereotactic body radiation therapy: Monte Carlo evaluation of tissue inhomogeneity corrections. Med Dosim 38(4):436–441. doi:10.1016/j.meddos.2013.06.002

    Article  PubMed  Google Scholar 

  7. Miura H, Masai N, Oh RJ, Shiomi H, Yamada K, Sasaki J, Inoue T (2014) Clinical introduction of Monte Carlo treatment planning for lung stereotactic body radiotherapy. J Appl Clin Med Phys 15(1):4202

    PubMed  Google Scholar 

  8. Wu VW, Tam KW, Tong SM (2013) Evaluation of the influence of tumor location and size on the difference of dose calculation between Ray Tracing algorithm and Fast Monte Carlo algorithm in stereotactic body radiotherapy of non-small cell lung cancer using CyberKnife. J Appl Clin Med Phys 14(5):68–78

    PubMed  Google Scholar 

  9. Zhuang T, Djemil T, Qi P, Magnelli A, Stephans K, Videtic G, Xia P (2013) Dose calculation differences between Monte Carlo and pencil beam depend on the tumor locations and volumes for lung stereotactic body radiation therapy. J Appl Clin Med Phys 14(2):4011

    PubMed  Google Scholar 

  10. Lax I, Panettieri V, Wennberg B, Amor Duch M, Naslund I, Baumann P, Gagliardi G (2006) Dose distributions in SBRT of lung tumors: comparison between two different treatment planning algorithms and Monte-Carlo simulation including breathing motions. Acta Oncol 45(7):978–988

    Article  PubMed  Google Scholar 

  11. Panettieri V, Wennberg B, Gagliardi G, Duch MA, Ginjaume M, Lax I (2007) SBRT of lung tumours: Monte Carlo simulation with PENELOPE of dose distributions including respiratory motion and comparison with different treatment planning systems. Phys Med Biol 52(14):4265–4281

    Article  PubMed  Google Scholar 

  12. Wilcox EE, Daskalov GM, Lincoln H, Shumway RC, Kaplan BM, Colasanto JM (2010) Comparison of planned dose distributions calculated by Monte Carlo and Ray-Trace algorithms for the treatment of lung tumors with cyberknife: a preliminary study in 33 patients. Int J Radiat Oncol Biol Phys 77(1):277–284

    Article  PubMed  Google Scholar 

  13. Chang JY, Balter PA, Dong L, Yang Q, Liao Z, Jeter M, Bucci MK, McAleer MF, Mehran RJ, Roth JA, Komaki R (2008) Stereotactic body radiation therapy in centrally and superiorly located stage I or isolated recurrent non-small-cell lung cancer. Int J Radiat Oncol Biol Phys 72(4):967–971. doi:10.1016/j.ijrobp.2008.08.001

    Article  PubMed  Google Scholar 

  14. Chen VJ, Oermann E, Vahdat S, Rabin J, Suy S, Yu X, Collins SP, Subramaniam D, Banovac F, Anderson E, Collins BT (2012) CyberKnife with tumor tracking: an effective treatment for high-risk surgical patients with stage I non-small cell lung cancer. Frontiers in oncology 2:9. doi:10.3389/fonc.2012.00009

    PubMed Central  CAS  PubMed  Google Scholar 

  15. Li J, Galvin J, Harrison A, Timmerman R, Yu Y, Xiao Y (2012) 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 84(2):508–513. doi:10.1016/j.ijrobp.2011.12.005

    Article  PubMed Central  PubMed  Google Scholar 

  16. Siedschlag C, Boersma L, van Loon J, Rossi M, van Baardwijk A, Gilhuijs K, Stroom J (2011) The impact of microscopic disease on the tumor control probability in non-small-cell lung cancer. Radiother Oncol 100(3):344–350. doi:10.1016/j.radonc.2011.08.046

    Article  PubMed  Google Scholar 

  17. van Loon J, Siedschlag C, Stroom J, Blauwgeers H, van Suylen RJ, Knegjens J, Rossi M, van Baardwijk A, Boersma L, Klomp H, Vogel W, Burgers S, Gilhuijs K (2012) Microscopic disease extension in three dimensions for non-small-cell lung cancer: development of a prediction model using pathology-validated positron emission tomography and computed tomography features. Int J Radiat Oncol Biol Phys 82(1):448–456. doi:10.1016/j.ijrobp.2010.09.001

    Article  PubMed  Google Scholar 

  18. Altman MB, Jin JY, Kim S, Wen N, Liu D, Siddiqui MS, Ajlouni MI, Movsas B, Chetty IJ (2012) 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 13(6):4007

    PubMed  Google Scholar 

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Ethical standard

This manuscript does not describe experimental procedures on human or animal subjects and was performed as part of an IRB-approved study. A waiver of informed consent was authorized by the authors’ IRB.

Conflict of interest

Roger Ove, Colbert Parker, Madhu Chilukuri, and Suzanne Russo declare that they have no conflict of interest.

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Correspondence to Roger Ove.

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Ove, R., Parker, C.A., Chilukuri, M.B. et al. Comparison of Monte Carlo with pencil beam dosimetry for lung CyberKnife SBRT, correlation with local recurrence. J Radiat Oncol 4, 257–263 (2015). https://doi.org/10.1007/s13566-015-0185-8

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  • DOI: https://doi.org/10.1007/s13566-015-0185-8

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