Log in

Evaluation of breathing patterns for respiratory-gated radiation therapy using the respiration regularity index

  • Published:
Journal of the Korean Physical Society Aims and scope Submit manuscript

Abstract

Despite the considerable importance of accurately estimating the respiration regularity of a patient in motion compensation treatment, not to mention the necessity of maintaining that regularity through the following sessions, an effective and simply applicable method by which those goals can be accomplished has rarely been reported. The authors herein propose a simple respiration regularity index based on parameters derived from a correspondingly simplified respiration model. In order to simplify a patient’s breathing pattern while preserving the data’s intrinsic properties, we defined a respiration model as a cos4(ω(t) · t) wave form with a baseline drift. According to this respiration formula, breathing-pattern fluctuation could be explained using four factors: the sample standard deviation of respiration period (s f ), the sample standard deviation of amplitude (s a ) and the results of a simple regression of the baseline drift (slope as β, and standard deviation of residuals as σ r ) of a respiration signal. The overall irregularity (δ) was defined as \(\left\| {\vec \omega } \right\|\), where \(\vec \omega \) is a variable newly-derived by using principal component analysis (PCA) for the four fluctuation parameters and has two principal components (ω 1, ω 2). The proposed respiration regularity index was defined as ρ = ln(1 + (1/δ))/2, a higher ρ indicating a more regular breathing pattern. We investigated its clinical relevance by comparing it with other known parameters. Subsequently, we applied it to 110 respiration signals acquired from five liver and five lung cancer patients by using real-time position management (RPM; Varian Medical Systems, Palo Alto, CA). Correlations between the regularity of the first session and the remaining fractions were investigated using Pearson’s correlation coefficient. Additionally, the respiration regularity was compared between the liver and lung cancer patient groups. The respiration regularity was determined based on ρ; patients with ρ < 0.3 showed worse regularity than the others whereas ρ > 0.7 was suitable for respiratory-gated radiation therapy (RGRT). Fluctuations in the breathing cycle and the amplitude were especially determinative of ρ. If the respiration regularity of a patient’s first session was known, it could be estimated through subsequent sessions. Notably, the breathing patterns of the lung cancer patients were more irregular than those of the liver cancer patients. Respiration regularity could be objectively determined by using a composite index, ρ. Such a single-index testing of respiration regularity can facilitate determination of RGRT availability in clinical settings, especially for free-breathing cases.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (France)

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. K. M. Langen and D. T. Jones, Int. J. Radiat. Oncol. Biol. Phys. 50, 265 (2001).

    Article  Google Scholar 

  2. P. J. Keall et al., Med. Phys. 33, 3874 (2006).

    Article  Google Scholar 

  3. A. Krauss, S. Nill and U. Oelfke, Phys. Med. Biol. 56, 5303 (2011).

    Article  Google Scholar 

  4. D. Ruan, J. A. Fessler and J. M. Balter, Med. Phys. 35, 782 (2008).

    Article  Google Scholar 

  5. G. C. Sharp, S. B. Jiang, S. Shimizu and H. Shirato, Phys. Med. Biol. 49, 425 (2004).

    Article  Google Scholar 

  6. D. Verellen, T. Depuydt, T. Gevaert, N. Linthout, K. Tournel, M. Duchateau, T. Reynders, G. Storme, and M. De Ridder, Cancer Radiother. 14, 446 (2010).

    Article  Google Scholar 

  7. M. Hoogeman, J. B. Prevost, J. Nuyttens, J. Poll, P. Levendag and B. Heijmen, Int. J. Radiat. Oncol. Biol. Phys. 74, 297 (2009).

    Article  Google Scholar 

  8. E. W. Pepin, H. Wu, Y. Zhang and B. Lord, Med. Phys. 38, 4036 (2011).

    Article  Google Scholar 

  9. F. Ernst, Compensating for Quasi-Periodic Motion in Robotic Radiosurgery, (Springer, New York, 2012).

    Book  Google Scholar 

  10. S. H. Benedict et al., Med. Phys. 37, 4078 (2010).

    Article  Google Scholar 

  11. W. Lu, P. J. Parikh, J. P. Hubenschmidt, J. D. Bradley and D. A. Low, Med. Phys. 33, 2964 (2006).

    Article  Google Scholar 

  12. P. S. Verma, H. Wu, M. P. Langer, I. J. Das and G. Sandison, Comput. Sci. Engin. 13, 24 (2011).

    Article  Google Scholar 

  13. H. Shirato, Y. Seppenwoolde, K. Kitamura, R. Onimura and S. Shimizu, Semin. Radiat. Oncol. 14, 10 (2004).

    Article  Google Scholar 

  14. S. S. Vedam, P. J. Keall, V. R. Kini, H. Mostafavi, H. P. Shukla and R. Mohan, Phys. Med. Biol. 48, 45 (2003).

    Article  Google Scholar 

  15. D. Ruan, J. A. Fessler, J. M. Balter and P. J. Keall, Phys. Med. Biol. 54, 4777 (2009).

    Article  Google Scholar 

  16. F. Ernst, A. Schlaefer and A. Schweikard, Med. Phys. 38, 5569 (2011).

    Article  Google Scholar 

  17. M. W. Kissick, X. Mo, K. C. McCall, L. K. Schubert, D. C. Westerly and T. R. Mackie, Phys. Med. Biol. 55, 2983 (2010).

    Article  Google Scholar 

  18. Y. D. Mutaf, J. A. Antolak and D. H. Brinkmann, Med. Phys. 34, 1615 (2007).

    Article  Google Scholar 

  19. S. Nishioka, T. Nishioka, M. Kawahara, S. Tanaka, T. Hiromura, K. Tomita and H. Shirato, Radiother. Oncol. 86, 69 (2008).

    Article  Google Scholar 

  20. S. Vedam, L. Archambault, G. Starkschall, R. Mohan and S. Beddar, Med. Phys. 34, 4247 (2007).

    Article  Google Scholar 

  21. http://www.Rob.Uni-Luebeck.De/Node/117#downloads.

  22. F. Ernst and A. Schweikard, Int. J. CARS. 3, 85 (2008).

    Article  Google Scholar 

  23. F. Ernst and A. Schweikard, Int. J. Comput. Assist. Radiol. Surg. 4, 439 (2009).

    Article  Google Scholar 

  24. D. Ruan, Phys. Med. Biol. 55, 3885 (2010).

    Article  Google Scholar 

  25. G. C. Sharp, Q. Zhao, H. Shirato and S. B. Jiang, Phys. Med. Biol. 52, 4761 (2007).

    Article  Google Scholar 

  26. S. S. Vedam, P. J. Keall, A. Docef, D. A. Todor, V. R. Kini and R. Mohan, Med. Phys. 31, 2274 (2004).

    Article  Google Scholar 

  27. K. C. McCall and R. Jeraj, Phys. Med. Biol. 52, 3455 (2007).

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hoonsik Bae.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cheong, KH., Lee, M., Kang, SK. et al. Evaluation of breathing patterns for respiratory-gated radiation therapy using the respiration regularity index. Journal of the Korean Physical Society 66, 301–313 (2015). https://doi.org/10.3938/jkps.66.301

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3938/jkps.66.301

Keywords

Navigation