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Radiation Oncology

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Open Access 01-12-2018 | Research

Dosimetric feasibility of 4DCT-ventilation imaging guided proton therapy for locally advanced non-small-cell lung cancer

Authors: Qijie Huang, Salma K. Jabbour, Zhiyan Xiao, Ning Yue, Xiao Wang, Hongbin Cao, Yu Kuang, Yin Zhang, Ke Nie

Published in: Radiation Oncology | Issue 1/2018

Abstract

Background

The principle aim of this study is to incorporate 4DCT ventilation imaging into functional treatment planning that preserves high-functioning lung with both double scattering and scanning beam techniques in proton therapy.

Methods

Eight patients with locally advanced non-small-cell lung cancer were included in this study. Deformable image registration was performed for each patient on their planning 4DCTs and the resultant displacement vector field with Jacobian analysis was used to identify the high-, medium- and low-functional lung regions. Five plans were designed for each patient: a regular photon IMRT vs. anatomic proton plans without consideration of functional ventilation information using double scattering proton therapy (DSPT) and intensity modulated proton therapy (IMPT) vs. functional proton plans with avoidance of high-functional lung using both DSPT and IMPT. Dosimetric parameters were compared in terms of tumor coverage, plan heterogeneity, and avoidance of normal tissues.

Results

Our results showed that both DSPT and IMPT plans gave superior dose advantage to photon IMRTs in sparing low dose regions of the total lung in terms of V5 (volume receiving 5Gy). The functional DSPT only showed marginal benefit in sparing high-functioning lung in terms of V5 or V20 (volume receiving 20Gy) compared to anatomical plans. Yet, the functional planning in IMPT delivery, can further reduce the low dose in high-functioning lung without degrading the PTV dosimetric coverages, compared to anatomical proton planning. Although the doses to some critical organs might increase during functional planning, the necessary constraints were all met.

Conclusions

Incorporating 4DCT ventilation imaging into functional proton therapy is feasible. The functional proton plans, in intensity modulated proton delivery, are effective to further preserve high-functioning lung regions without degrading the PTV coverage.

Bradley J, Graham MV, Winter K, et al. Toxicity and outcome results of RTOG 9311: a phase I-II dose-escalation study using three-dimensional conformal radiotherapy in patients with inoperable non-small-cell lung carcinoma. Int J Radiat Oncol Biol Phys. 2005;61(2):318–28. https://doi.org/10.1016/j.ijrobp.2004.06.260.CrossRefPubMed

Socinski MA, Morris DE, Halle JS, et al. Induction and concurrent chemotherapy with high-dose thoracic conformal radiation therapy in unresectable stage IIIA and IIIB non-small-cell lung cancer: a dose-escalation phase I trial. J Clin Oncol. 2004;22(21):4341–50. https://doi.org/10.1200/JCO.2004.03.022.CrossRefPubMed

Graham MV, Purdy JA, Emami B, et al. Clinical dose-volume histogram analysis for pneumonitis after 3D treatment for non-small cell lung cancer (NSCLC). Int J Radiat Oncol Biol Phys. 1999;45(2):323–9.CrossRefPubMed

MG L. Pulmonary physiology. McGraw-Hill Medical; 2007.

Yorke ED, Jackson A, Rosenzweig KE, et al. Dose-volume factors contributing to the incidence of radiation pneumonitis in non-small-cell lung cancer patients treated with three-dimensional conformal radiation therapy. Int J Radiat Oncol Biol Phys. 2002;54(2):329–39.CrossRefPubMed

Yamamoto T, Kabus S, Bal M, Keall P, Benedict S, Daly M. The first patient treatment of computed tomography ventilation functional image-guided radiotherapy for lung cancer. Radiother Oncol. 2016;118(2):227–31. https://doi.org/10.1016/j.radonc.2015.11.006.CrossRefPubMed

Yamamoto T, Kabus S, Klinder T, et al. Four-dimensional computed tomography pulmonary ventilation images vary with deformable image registration algorithms and metrics. Med Phys. 2011;38(3):1348–58. https://doi.org/10.1118/1.3547719.CrossRefPubMed

Yamamoto T, Kabus S, von Berg J, Lorenz C, Keall PJ. Impact of four-dimensional computed tomography pulmonary ventilation imaging-based functional avoidance for lung cancer radiotherapy. Int J Radiat Oncol Biol Phys. 2011;79(1):279–88. https://doi.org/10.1016/j.ijrobp.2010.02.008.CrossRefPubMed

Faught AM, Miyasaka Y, Kadoya N, et al. Evaluating the toxicity reduction with computed tomographic ventilation functional avoidance radiation therapy. Int J Radiat Oncol Biol Phys. 2017;99(2):325–33. https://doi.org/10.1016/j.ijrobp.2017.04.024.CrossRefPubMed

10.

Vinogradskiy Y, Castillo R, Castillo E, et al. Use of 4-dimensional computed tomography-based ventilation imaging to correlate lung dose and function with clinical outcomes. Int J Radiat Oncol Biol Phys. 2013;86(2):366–71. https://doi.org/10.1016/j.ijrobp.2013.01.004.CrossRefPubMed

11.

Wang R, Zhang S, Yu H, et al. Optimal beam arrangement for pulmonary ventilation image-guided intensity-modulated radiotherapy for lung cancer. Radiat Oncol. 2014;9:184. https://doi.org/10.1186/1748-717X-9-184.CrossRefPubMedPubMedCentral

12.

Yin Y, Chen J, Li B, et al. Protection of lung function by introducing single photon emission computed tomography lung perfusion image into radiotherapy plan of lung cancer. Chin Med J. 2009;122(5):509–13.PubMed

13.

Shioyama Y, Jang SY, Liu HH, et al. Preserving functional lung using perfusion imaging and intensity-modulated radiation therapy for advanced-stage non-small cell lung cancer. Int J Radiat Oncol Biol Phys. 2007;68(5):1349–58. https://doi.org/10.1016/j.ijrobp.2007.02.015.CrossRefPubMed

14.

Suga K. Technical and analytical advances in pulmonary ventilation SPECT with xenon-133 gas and Tc-99m-Technegas. Ann Nucl Med. 2002;16(5):303–10.CrossRefPubMed

15.

van Beek EJR, Wild JM, Kauczor H-U, Schreiber W, Mugler JP 3rd, de Lange EE. Functional MRI of the lung using hyperpolarized 3-helium gas. J Magn Reson Imaging. 2004;20(4):540–54. https://doi.org/10.1002/jmri.20154.CrossRefPubMed

16.

Fain S, Schiebler ML, McCormack DG, Parraga G. Imaging of lung function using hyperpolarized helium-3 magnetic resonance imaging: review of current and emerging translational methods and applications. J Magn Reson Imaging. 2010;32(6):1398–408. https://doi.org/10.1002/jmri.22375.CrossRefPubMedPubMedCentral

17.

Castillo R, Castillo E, Martinez J, Guerrero T. Ventilation from four-dimensional computed tomography: density versus Jacobian methods. Phys Med Biol. 2010;55(16):4661–85. https://doi.org/10.1088/0031-9155/55/16/004.CrossRefPubMed

18.

Mistry NN, Diwanji T, Shi X, et al. Evaluation of fractional regional ventilation using 4D-CT and effects of breathing maneuvers on ventilation. Int J Radiat Oncol Biol Phys. 2013;87(4):825–31. https://doi.org/10.1016/j.ijrobp.2013.07.032.CrossRefPubMed

19.

Vinogradskiy Y, Koo PJ, Castillo R, et al. Comparison of 4-dimensional computed tomography ventilation with nuclear medicine ventilation-perfusion imaging: a clinical validation study. Int J Radiat Oncol Biol Phys. 2014;89(1):199–205. https://doi.org/10.1016/j.ijrobp.2014.01.009.CrossRefPubMedPubMedCentral

20.

Brennan D, Schubert L, Diot Q, et al. Clinical validation of 4-dimensional computed tomography ventilation with pulmonary function test data. Int J Radiat Oncol Biol Phys. 2015;92(2):423–9. https://doi.org/10.1016/j.ijrobp.2015.01.019.CrossRefPubMed

21.

Yaremko BP, Guerrero TM, Noyola-Martinez J, et al. Reduction of normal lung irradiation in locally advanced non-small-cell lung cancer patients, using ventilation images for functional avoidance. Int J Radiat Oncol Biol Phys. 2007;68(2):562–71. https://doi.org/10.1016/j.ijrobp.2007.01.044.CrossRefPubMedPubMedCentral

22.

Yamamoto T, Kabus S, Klinder T, et al. Investigation of four-dimensional computed tomography-based pulmonary ventilation imaging in patients with emphysematous lung regions. Phys Med Biol. 2011;56(7):2279–98. https://doi.org/10.1088/0031-9155/56/7/023.CrossRefPubMed

23.

Huang T-C, Hsiao C-Y, Chien C-R, Liang J-A, Shih T-C, Zhang GG. IMRT treatment plans and functional planning with functional lung imaging from 4D-CT for thoracic cancer patients. Radiat Oncol. 2013;8:3. https://doi.org/10.1186/1748-717X-8-3.CrossRefPubMedPubMedCentral

24.

Li Y, Kardar L, Li X, et al. On the interplay effects with proton scanning beams in stage III lung cancer. Med Phys. 2014;41(2):21721. https://doi.org/10.1118/1.4862076.CrossRef

25.

Kardar L, Li Y, Li X, et al. Evaluation and mitigation of the interplay effects of intensity modulated proton therapy for lung cancer in a clinical setting. Pract Radiat Oncol. 2014;4(6):e259–68. https://doi.org/10.1016/j.prro.2014.06.010.CrossRefPubMedPubMedCentral

26.

Huang Q. Evaluation of deformable image registration for lung motion estimation using hyperpolarized gas tagging MRI. 2014.

27.

Q H, Y Z, Y L, et al. Evaluation of deformable image registration for lung motion estimation using hyperpolarized gas tagging MRI. ; 2014:Mo-G-18C-03.

28.

Y L, W M, F Y, J C. Evaluate deformable image registration for the lung using hyperpolarized gas tagging MRI. In: AAPM; 2013. Tu-C-141-08.

29.

Moyers MF, Miller DW, Bush DA, Slater JD. Methodologies and tools for proton beam design for lung tumors. Int J Radiat Oncol Biol Phys. 2001;49(5):1429–38.CrossRefPubMed

30.

Lomax AJ. Intensity modulated proton therapy and its sensitivity to treatment uncertainties 2: the potential effects of inter-fraction and inter-field motions. Phys Med Biol. 2008;53(4):1043–56. https://doi.org/10.1088/0031-9155/53/4/015.CrossRefPubMed

31.

Lavrenkov K, Christian JA, Partridge M, et al. A potential to reduce pulmonary toxicity: the use of perfusion SPECT with IMRT for functional lung avoidance in radiotherapy of non-small cell lung cancer. Radiother Oncol. 2007;83(2):156–62. https://doi.org/10.1016/j.radonc.2007.04.005.CrossRefPubMed

32.

Seco J, Panahandeh HR, Westover K, Adams J, Willers H. Treatment of non-small cell lung cancer patients with proton beam-based stereotactic body radiotherapy: dosimetric comparison with photon plans highlights importance of range uncertainty. Int J Radiat Oncol Biol Phys. 2012;83(1):354–61. https://doi.org/10.1016/j.ijrobp.2011.05.062.CrossRefPubMed

33.

Welsh J, Gomez D, Palmer MB, et al. Intensity-modulated proton therapy further reduces normal tissue exposure during definitive therapy for locally advanced distal esophageal tumors: a dosimetric study. Int J Radiat Oncol Biol Phys. 2011;81(5):1336–42. https://doi.org/10.1016/j.ijrobp.2010.07.2001.CrossRefPubMedPubMedCentral

34.

Shioyama Y, Tokuuye K, Okumura T, et al. Clinical evaluation of proton radiotherapy for non-small-cell lung cancer. Int J Radiat Oncol Biol Phys. 2003;56(1):7–13.CrossRefPubMed

35.

Chang JY, Zhang X, Wang X, et al. Significant reduction of normal tissue dose by proton radiotherapy compared with three-dimensional conformal or intensity-modulated radiation therapy in stage I or stage III non-small-cell lung cancer. Int J Radiat Oncol Biol Phys. 2006;65(4):1087–96. https://doi.org/10.1016/j.ijrobp.2006.01.052.CrossRefPubMed

36.

Giaddui T, Chen W, Yu J, et al. Establishing the feasibility of the dosimetric compliance criteria of RTOG 1308: phase III randomized trial comparing overall survival after photon versus proton radiochemotherapy for inoperable stage II-IIIB NSCLC. Radiat Oncol. 2016;11:66. https://doi.org/10.1186/s13014-016-0640-8.CrossRefPubMedPubMedCentral

37.

Reinhardt JM, Ding K, Cao K, Christensen GE, Hoffman EA, Bodas SV. Registration-based estimates of local lung tissue expansion compared to xenon CT measures of specific ventilation. Med Image Anal. 2008;12(6):752–63. https://doi.org/10.1016/j.media.2008.03.007.CrossRefPubMedPubMedCentral

38.

Kipritidis J, Siva S, Hofman MS, Callahan J, Hicks RJ, Keall PJ. Validating and improving CT ventilation imaging by correlating with ventilation 4D-PET/CT using 68Ga-labeled nanoparticles. Med Phys. 2014;41(1):11910. https://doi.org/10.1118/1.4856055.CrossRef

39.

Mathew L, Wheatley A, Castillo R, et al. Hyperpolarized (3)he magnetic resonance imaging: comparison with four-dimensional x-ray computed tomography imaging in lung cancer. Acad Radiol. 2012;19(12):1546–53. https://doi.org/10.1016/j.acra.2012.08.007.CrossRefPubMed

40.

Seppenwoolde Y, Muller SH, Theuws JC, et al. Radiation dose-effect relations and local recovery in perfusion for patients with non-small-cell lung cancer. Int J Radiat Oncol Biol Phys. 2000;47(3):681–90.CrossRefPubMed

41.

Kang Y, Zhang X, Chang JY, et al. 4D proton treatment planning strategy for mobile lung tumors. Int J Radiat Oncol • Biol • Phys. 2018;67(3):906–14. https://doi.org/10.1016/j.ijrobp.2006.10.045.CrossRef

42.

Bortfeld T, Jokivarsi K, Goitein M, Kung J, Jiang SB. Effects of intra-fraction motion on IMRT dose delivery: statistical analysis and simulation. Phys Med Biol. 2002;47(13):2203–20.CrossRefPubMed

43.

Phillips MH, Pedroni E, Blattmann H, Boehringer T, Coray A, Scheib S. Effects of respiratory motion on dose uniformity with a charged particle scanning method. Phys Med Biol. 1992;37(1):223–34.CrossRefPubMed

44.

Lambert J, Suchowerska N, McKenzie DR, Jackson M. Intrafractional motion during proton beam scanning. Phys Med Biol. 2005;50(20):4853–62. https://doi.org/10.1088/0031-9155/50/20/008.CrossRefPubMed

45.

Kraus KM, Heath E, Oelfke U. Dosimetric consequences of tumour motion due to respiration for a scanned proton beam. Phys Med Biol. 2011;56(20):6563–81. https://doi.org/10.1088/0031-9155/56/20/003.CrossRefPubMed

46.

Bert C, Grozinger SO, Rietzel E. Quantification of interplay effects of scanned particle beams and moving targets. Phys Med Biol. 2008;53(9):2253–65. https://doi.org/10.1088/0031-9155/53/9/003.CrossRefPubMed

47.

Grassberger C, Dowdell S, Lomax A, et al. Motion interplay as a function of patient parameters and spot size in spot scanning proton therapy for lung cancer. Int J Radiat Oncol Biol Phys. 2013;86(2):380–6. https://doi.org/10.1016/j.ijrobp.2013.01.024.CrossRefPubMedPubMedCentral

48.

Inoue T, Widder J, van Dijk LV, et al. Limited impact of setup and range uncertainties, breathing motion, and interplay effects in robustly optimized intensity modulated proton therapy for stage III non-small cell lung Cancer. Int J Radiat Oncol Biol Phys. 2016;96(3):661–9. https://doi.org/10.1016/j.ijrobp.2016.06.2454.CrossRefPubMed

49.

Ireland RH, Tahir BA, Wild JM, Lee CE, Hatton MQ. Functional image-guided radiotherapy planning for normal lung avoidance. Clin Oncol (R Coll Radiol). 2016;28(11):695–707. https://doi.org/10.1016/j.clon.2016.08.005.CrossRef

Title: Dosimetric feasibility of 4DCT-ventilation imaging guided proton therapy for locally advanced non-small-cell lung cancer
Authors: Qijie Huang
Salma K. Jabbour
Zhiyan Xiao
Ning Yue
Xiao Wang
Hongbin Cao
Yu Kuang
Yin Zhang
Ke Nie
Publication date: 01-12-2018
Publisher: BioMed Central
Published in: Radiation Oncology / Issue 1/2018
Electronic ISSN: 1748-717X
DOI: https://doi.org/10.1186/s13014-018-1018-x

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Springer Medicine

Dosimetric feasibility of 4DCT-ventilation imaging guided proton therapy for locally advanced non-small-cell lung cancer

Abstract

Background

Methods

Results

Conclusions

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

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