DOI QR코드

DOI QR Code

The Optimum of Respiratory Phase Using the Motion Range of the Diaphragm: Focus on Respiratory Gated Radiotherapy of Lung Cancer

횡격막의 움직임을 이용한 최적화된 호흡 위상의 선택: 폐암의 호흡 동기 방사선치료 중심

  • Kim, Myoungju (Department of Cancer for health promotion & Cancer prevention Center, Dongnam Inst. of Radiological & Medical Science) ;
  • Im, Inchul (Department of Radiological Science, Dongeui University) ;
  • Lee, Jaeseung (Department of Radiological Science, Dongeui University) ;
  • Kang, Suman (Department of Radiological Science, Dongeui University)
  • 김명주 (동남원자력의학원 건강증진센터) ;
  • 임인철 (동의대학교 방사선학과) ;
  • 이재승 (동의대학교 방사선학과) ;
  • 강수만 (동의대학교 방사선학과)
  • Received : 2013.04.05
  • Accepted : 2013.04.19
  • Published : 2013.04.30

Abstract

This study was to analyze quantitatively movement of planning target volume (PTV) and change of PTV volume through movement of diaphragm according to breathing phase. The purpose of present study was to investigate optimized respiration phase for radiation therapy of lung cancer. Simulated breathing training was performed in order to minimize systematic errors which is caused non-specific or irregular breathing. We performed 4-dimensional computed tomography (4DCTi) in accordance with each respiratory phase in the normalized respiratory gated radiation therapy procedures, then not only defined PTVi in 0 ~ 90%, 30 ~ 70% and 40 ~ 60% in the reconstructed 4DCTi images but analyzed quantitatively movement and changes of volume in PTVi. As a results, average respiratory cycle was $3.4{\pm}0.5$ seconds by simulated breathing training. R2-value which is expressed as concordance between clinically induced expected value and actual measured value, was almost 1. There was a statistically significant. And also movement of PTVi according to each respiration phase 0 ~ 90%, 30 ~ 70% and 40 ~ 60% were $13.4{\pm}6.4mm$, $6.1{\pm}2.9mm$ and $4.0{\pm}2.1mm$ respectively. Change of volume in PTVi of respiration phase 30 ~ 70% was decreased by $32.6{\pm}8.7%$ and 40 ~ 60% was decreased by $41.6{\pm}6.2%$. In conclusion, PTVi movement and volume change was reduced, when we apply a short breathing phase (40 ~ 60%: 30% duty cycle) range. Furthermore, PTVi margin considered respiration was not only within 4mm but able to get uniformity of dose.

본 연구는 각 호흡 위상에 따른 계획용표적체적(planning target volume. PTV)의 움직임 및 체적(PTV volume)의 변화를 횡격막(diaphragm)의 움직임을 이용하여 정량적으로 분석함으로써 폐암의 호흡 동기 방사선치료를 위한 최적화된 호흡 위상을 알아보고자 하였다. 비특이적 호흡이나 불규칙적인 호흡에 의한 체계적 오류(system error)를 화하기 위하여 모의 호흡 훈련을 시행하였다. 정규화된 호흡 동기 방사선치료 절차에 따라 각 호흡 위상 i에 따른 4차원 전산화치료계획(4-dimensional computed tomography. 4DCTi)을 시행하였으며 0~90%, 30~70%, 40~60% 호흡 위상으로 재구성된 4DCTi 영상에서 PTV를 정의하고 PTVi의 움직임 및 체적의 변화를 정략적으로 분석하였다. 모의호흡 훈련에 의한 평균 호흡 주기는 $3.4{\pm}0.5$초로 나타났으며 임상적으로 유도되는 예상 값과 실제 측정값의 일치 정도를 나타내는 R-제곱 값은 1에 근접하여 유의하였다. 또한 각 호흡 위상 i에 따른 PTVi의 움직임은 0~90% 호흡 위상의 경우 $13.4{\pm}6.4mm$, 30~70% 호흡 위상의 경우 $6.1{\pm}2.9mm$, 40~60% 호흡 위상의 경우 $4.0{\pm}2.1mm$ 이었으며 PTVi의 체적 변화는 30~70% 호흡 위상의 경우 $32.6{\pm}8.7%$, 40~60% 호흡 위상의 경우 $41.6{\pm}6.2%$ 감소되었다. 결론적으로 짧은 호흡 위상(40~60%: 30% duty cycle) 폭을 적용하였을 때 PTV의 움직임 및 체적의 변화가 감소되어 호흡을 고려한 PTV 마진이 4mm 이내이면서 PTV 내 선량의 균일성을 얻을 수 있었다.

Keywords

References

  1. A. Sola, E. Martinez-Lopez, M. Rico, et. al., "Radiotherapy of mobile tumors", An. Sist. Sanit. Navar., Vol.32, No.2, pp.39-49, 2009.
  2. T. Roland, R. Hales, T. McNutt, et. al., "A method for deriving a 4D-interpolated balanced planning target for mobile tumor radiotherapy", Med. Phys., Vol.39, No.1, pp.195-205, 2012. https://doi.org/10.1118/1.3666774
  3. E. W. Pepin, H. Wu, Y. Zhang, et. al., "Correlation and prediction uncertainties in the cyberknife synchrony respiratory tracking system", Med. Phys., Vol.38, No.7, pp.4036-4044, 2011. https://doi.org/10.1118/1.3596527
  4. M. Falk, P. Munck af Rosenschold, P. Keall, et. al., "Real-time dynamic MLC tracking for inversely optimized arc radiotherapy", Radiother. Oncol., Vol.94, No.2, pp.218-223, 2010. https://doi.org/10.1016/j.radonc.2009.12.022
  5. H. Shirato, R. Onimaru, M. Ishikawa, et. al., "Real-time 4-D radiotherapy for lung cancer", Cancer Sci., Vol.103, No.1, pp.1-6, 2012. https://doi.org/10.1111/j.1349-7006.2011.02114.x
  6. H. Onishi, K. Kuriyama, T. Komiyama, et. al., "A new irradiation system for lung cancer combining linear accelerator, computed tomography, patient self-breath-holding, and patient-directed beam-control without respiratory monitoring devices", Int. J. Radiat. Oncol. Biol. Phys., Vol.56, No.1, pp.14-20, 2003. https://doi.org/10.1016/S0360-3016(02)04414-0
  7. P. Giraud, E. Morvan, L. Claude, et. al., "Respiratory gating techniques for optimization of lung cancer radiotherapy", J. Thorac. Oncol., Vol.6, No.12, pp.2058-2068, 2011. https://doi.org/10.1097/JTO.0b013e3182307ec2
  8. J. Hanley, M. M. Debois, D. Mah, et. al., "Deep inspiration breath-hold technique for lung tumors: the potential value of target immobilization and reduced lung density in dose escalation", Int. J. Radiat. Oncol. Biol. Phys., Vol.45, No.3, pp.603-611, 1999. https://doi.org/10.1016/S0360-3016(99)00154-6
  9. D. P. Gierga, J. Brewer, G. C. Sharp, et. al., "The correlation between internal and external markers for abdominal tumors: implications for respiratory gating", Int. J. Radiat. Oncol. Biol. Phys., Vol.16, No.5, pp.1551-1558, 2005.
  10. E. Heath, J. Unkelbach, U. Oelfke., "Incorporating uncertainties in respiratory motion into 4D treatment plan optimization", Med. Phys., Vol.36, No.7, pp. 3059-3071, 2009. https://doi.org/10.1118/1.3148582
  11. ICRU report No. 62, "Prescribing recording, and reporting photon beam therapy", International commission on Radiation Unit and Measuremnet, Bethesda, 1999.
  12. A. Hertanto, Q. Zhang, Y. C. Hu, et. al., "Reduction of irregular breathing artifacts in respiration-correlated CT images using a respiratory motion model", Med. Phys., Vol.39, No.6, pp.3070-3079, 2012. https://doi.org/10.1118/1.4711802
  13. J. W Wong, M. B. Sharpe, D. A. Jaffray, et. al. "The use of active breathing control (ABC) to reduce margin for breathing motion", Int. J. Radiat. Oncol. Biol. Phys., Vol.44, No.4, pp.911-919, 1999. https://doi.org/10.1016/S0360-3016(99)00056-5
  14. S. B. Jiang, "Radiotherapy of mobile tumor", Semin. Radiat. Oncol., Vol.16, No.4, pp.239-248, 2006.
  15. H. H. Liu, P. Balter, T. Tutt, et. al. "Assessing respiration-induced tumor motion and internal target volume using four-dimensional computed tomography for radiotherapy of lung cancer", Int. J. Radiat. Oncol. Biol. Phys., Vol.68, No.2, pp.531-540, 2007. https://doi.org/10.1016/j.ijrobp.2006.12.066
  16. M. van Herk, P. Remeijer, C. Rasch, et. al., "The probability of correct target dosage: dose-population histograms for deriving treatment margins in radiotherapy", Int. J. Radiat. Oncol. Biol. Phys., Vol.47, No.4, pp.1121-1135, 2000. https://doi.org/10.1016/S0360-3016(00)00518-6
  17. J. C. Stroom, B. J. Heijmen, "Geometrical uncertainties, radiotherapy planning margins, and the ICRU-62 report", Radiother. Oncol., Vol.64, No.1, pp.75-83, 2002. https://doi.org/10.1016/S0167-8140(02)00140-8
  18. A. M. Allen, K. M. Siracuse, J. A. Hayman, et. al., "Evaluation of the influence of breathing on the movement and modeling of lung tumors", Int. J. Radiat. Oncol. Biol. Phys., Vol.58, No.4, pp.1251-1257, 2004. https://doi.org/10.1016/j.ijrobp.2003.09.081
  19. J. R. van Sornsen de Koste, F. J. Lagerwaard, R. H. Schuchhard-Schipper, et. al., "Dosimetric consequences of tumor mobility in radiotherapy of stage I non-small cell lung cancer--an analysis of data generated using 'slow' CT scans", Radiother. Oncol., Vol.61, No.1, pp. 93-99, 2001. https://doi.org/10.1016/S0167-8140(01)00373-5

Cited by

  1. Reductions in the variations of respiration signals for respiratory-gated radiotherapy when using the video-coaching respiration guiding system vol.67, pp.1, 2015, https://doi.org/10.3938/jkps.67.163
  2. A Monte Carlo Study of Secondary Electron Production from Gold Nanoparticle in Kilovoltage and Megavoltage X-rays vol.10, pp.3, 2016, https://doi.org/10.7742/jksr.2016.10.3.153
  3. A Study on Abdominal Magnetic Resonance Imaging Using Metronome vol.28, pp.2, 2013, https://doi.org/10.31159/ksmrt.2018.28.2.11
  4. 메트로놈을 이용한 복부 MRI 검사에 대한 연구 vol.24, pp.9, 2013, https://doi.org/10.6109/jkiice.2020.24.9.1138