Document Type: Original Research

Authors

1 Department of Medical Physics, Isfahan University of Medical Sciences, Isfahan, Iran

2 Department of Medical Physics, Kermanshah University of Medical Sciences, Kermanshah, Iran

3 Faculty of Computer Science and Engineering, Shahid Beheshti University, Tehran, Iran

4 Department of Medical Physics, Royal Adelaide Hospital, Adelaide, SA, Australia.

5 Department of Medical Engineering, Tabriz University of Medical Sciences, Tabriz, Iran.

Abstract

Background: Respiratory motion causes thoracic movement and reduces targeting accuracy in radiotherapy.
Objective: This study proposes an approach to generate a model to track lung tumor motion by controlling dynamic multi-leaf collimators.
Material and Methods: All slices which contained tumor were contoured in the 4D-CT images for 10 patients. For modelling of respiratory motion, the end-exhale phase of these images has been considered as the reference and they were analyzed using neuro-fuzzy method to predict the magnitude of displacement of the lung tumor. Then, the predicted data were used to determine the leaf motion in MLC. Finally, the trained algorithm was figured out using Shaper software to show how MLCs could track the moving tumor and then imported on the Varian Linac equipped with EPID.
Results: The root mean square error (RMSE) was used as a statistical criterion in order to investigate the accuracy of neuro-fuzzy performance in lung tumor prediction. The results showed that RMSE did not have a considerable variation. Also, there was a good agreement between the images obtained by EPID and Shaper for a respiratory cycle.
Conclusion: The approach used in this study can track the moving tumor with MLC based on the 4D modelling, so it can improve treatment accuracy, dose conformity and sparing of healthy tissues because of low error in margins that can be ignored. Therefore, this method can work more accurately as compared with the gating and invasive approaches using markers.

Keywords

  1. Keall PJ, Mageras GS, Balter JM, Emery RS, Forster KM, Jiang SB, et al. The management of respiratory motion in radiation oncology report of AAPM Task Group 76. Med Phys. 2006;33:3874-900. doi.org/10.1118/1.2349696. PubMed PMID: 17089851.
  2. Hanley J, Debois MM, Mah D, Mageras GS, Raben A, Rosenzweig K, 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. 1999;45:603-11. doi.org/10.1016/S0360-3016(99)00154-6. PubMed PMID: 10524412.
  3. Kubo HD, Len PM, Minohara S, Mostafavi H. Breathing-synchronized radiotherapy program at the University of California Davis Cancer Center. Med Phys. 2000;27:346-53. doi.org/10.1118/1.598837. PubMed PMID: 10718138.
  4. Li XA, Stepaniak C, Gore E. Technical and dosimetric aspects of respiratory gating using a pressure-sensor motion monitoring system. Med Phys. 2006;33:145-54. doi.org/10.1118/1.2147743. PubMed PMID: 16485421.
  5. Van Herk M, Errors and margins in radiotherapy. Semin Radiat Oncol. 2004;14:52-64. doi: 10.1053/j.semradonc.2003.10.003. PubMed PMID: 14752733.
  6. Vedam SS, Keall PJ, Kini VR, Mohan R. Determining parameters for respiration-gated radiotherapy. Med Phys. 2001;28:2139-46. doi.org/10.1118/1.1406524. PubMed PMID: 11695776.
  7. Wink NM, Chao M, Antony J, Xing L. Individualized gating windows based on four-dimensional CT information for respiration-gated radiotherapy. Phys Med Biol. 2008;53:165-75. doi.org/10.1088/0031-9155/53/1/011. PubMed PMID: 18182694.
  8. Ohara K, Okumura T, Akisada M, Inada T, Mori T, Yokota H, et al. Irradiation synchronized with respiration gate. Int J Radiat Oncol Biol Phys. 1989;17:853-7. doi.org/10.1016/0360-3016(89)90078-3. PubMed PMID: 2777676.
  9. Seppenwoolde Y, Shirato H, Kitamura K, Shimizu S, Van Herk M, Lebesque JV, et al. Precise and real-time measurement of 3D tumor motion in lung due to breathing and heartbeat, measured during radiotherapy. Int J Radiat Oncol Biol Phys. 2002;53:822-34. doi.org/10.1016/S0360-3016(02)02803-1. PubMed PMID: 12095547.
  10. Shirato H, Shimizu S, Kunieda T, Kitamura K, Van Herk M, Kagei K, et al. Physical aspects of a real-time tumor-tracking system for gated radiotherapy. Int J Radiat Oncol Biol Phys. 2000;48:1187-95. doi.org/10.1016/S0360-3016(00)00748-3. PubMed PMID: 11072178.
  11. Keall PJ, Kini VR, Vedam SS, Mohan R. Motion adaptive x-ray therapy: a feasibility study. Phys Med Biol. 2001;46:1-10. doi.org/10.1088/0031-9155/46/1/301. PubMed PMID: 11197664.
  12. Murphy MJ, editor Tracking moving organs in real time. Seminars in radiation oncology; 2004: Elsevier.
  13. Neicu T, Shirato H, Seppenwoolde Y, Jiang SB. Synchronized moving aperture radiation therapy (SMART): average tumour trajectory for lung patients. Phys Med Biol. 2003;48:587-98. doi.org/10.1088/0031-9155/48/5/303. PubMed PMID: 12696797.
  14. Schweikard A, Shiomi H, Adler J. Respiration tracking in radiosurgery. Med Phys. 2004;31:2738-41. doi.org/10.1118/1.1774132. PubMed PMID: 15543778.
  15. Berbeco RI, Jiang SB, Sharp GC, Chen GT, Mostafavi H, Shirato H. Integrated radiotherapy imaging system (IRIS): design considerations of tumour tracking with linac gantry-mounted diagnostic x-ray systems with flat-panel detectors. Phys Med Biol. 2004;49:243-55. doi.org/10.1088/0031-9155/49/2/005. PubMed PMID: 15083669.
  16. Britton KR, Takai Y, Mitsuya M, Nemoto K, Ogawa Y, Yamada S. Evaluation of inter- and intrafraction organ motion during intensity modulated radiation therapy (IMRT) for localized prostate cancer measured by a newly developed on-board image-guided system. Radiat Med. 2005;23:14-24. PubMed PMID: 15786747.
  17. Takai Y, Mitsuya M, Nemoto K, Ogawa Y, Matsusita H, Yamada S, et al. Development of a new linear accelerator mounted with dual x-ray fluoroscopy using amorphous silicon flat panel x-ray sensors to detect a gold seed in a tumor at real treatment position. Int J Radiat Oncol Biol Phys. 2001;51:381. doi.org/10.1016/S0360-3016(01)02528-7.
  18. Wiersma RD, Mao W, Xing L. Combined KV and MV imaging for real-time tracking of implanted fiducial markers. Med Phys. 2008;35:1191-8. doi.org/10.1118/1.2842072. PubMed PMID: 18491510. PubMed PMCID: 2811551.
  19. Kubo HD, Hill BC. Respiration gated radiotherapy treatment: a technical study. Phys Med Biol. 1996;41:83-91. doi.org/10.1088/0031-9155/41/1/007. PubMed PMID: 8685260.
  20. Ozhasoglu C, Murphy MJ. Issues in respiratory motion compensation during external-beam radiotherapy. Int J Radiat Oncol Biol Phys. 2002;52:1389-99. doi.org/10.1016/S0360-3016(01)02789-4. PubMed PMID: 11955754.
  21. Simon L, Giraud P, Servois V, Rosenwald JC. Lung volume assessment for a cross-comparison of two breathing-adapted techniques in radiotherapy. Int J Radiat Oncol Biol Phys. 2005;63:602-9. doi.org/10.1016/j.ijrobp.2005.05.020. PubMed PMID: 16168852.
  22. Cervino LI, Du J, Jiang SB. MRI-guided tumor tracking in lung cancer radiotherapy. Phys Med Biol. 2011;56:3773-85. doi.org/10.1088/0031-9155/56/13/003. PubMed PMID: 21628775.
  23. Hughes S, McClelland J, Tarte S, Lawrence D, Ahmad S, Hawkes D, et al. Assessment of two novel ventilatory surrogates for use in the delivery of gated/tracked radiotherapy for non-small cell lung cancer. Radiother Oncol. 2009;91:336-41. doi.org/10.1016/j.radonc.2009.03.016. PubMed PMID: 19395076.
  24. Shah AP, Kupelian PA, Willoughby TR, Meeks SL. Expanding the use of real-time electromagnetic tracking in radiation oncology. J Appl Clin Med Phys. 2011;12:3590. doi.org/10.1120/jacmp.v12i4.3590. PubMed PMID: 22089017.
  25. Shimizu S, Shirato H, Kitamura K, Ogura S, Akita-Dosaka H, Tateishi U, et al. Fluoroscopic real-time tumor-tracking radiation treatment (RTRT) can reduce internal margin (IM) and set-up margin (SM) of planning target volume (PTV) for lung tumors. Int J Radiat Oncol Biol Phys. 2000;48:166-7. doi.org/10.1016/S0360-3016(00)80127-3.
  26. Zhong Y, Stephans K, Qi P, Yu N, Wong J, Xia P. Assessing feasibility of real-time ultrasound monitoring in stereotactic body radiotherapy of liver tumors. Technol Cancer Res Treat. 2013;12:243-50. doi.org/10.7785/tcrt.2012.500323. PubMed PMID: 23369158.
  27. Jang J-S. ANFIS: adaptive-network-based fuzzy inference system. IEEE transactions on systems, man, and cybernetics. 1993;23:665-85. doi.org/10.1109/21.256541.
  28. Vandemeulebroucke J, Rit S, Kybic J, Clarysse P, Sarrut D. Spatiotemporal motion estimation for respiratory-correlated imaging of the lungs. Med Phys. 2011;38:166-78. doi.org/10.1118/1.3523619. PubMed PMID: 21361185.
  29. Jang J-S, Sun C-T. Neuro-fuzzy modeling and control. Proceedings of the IEEE. 1995;83:378-406. doi.org/10.1109/5.364486.
  30. Loukas YL. Adaptive neuro-fuzzy inference system: an instant and architecture-free predictor for improved QSAR studies. J Med Chem. 2001;44:2772-83. doi.org/10.1021/jm000226c. PubMed PMID: 11495588.
  31. Yushkevich PA, Piven J, Hazlett HC, Smith RG, Ho S, Gee JC, et al. User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage. 2006;31:1116-28. doi.org/10.1016/j.neuroimage.2006.01.015. PubMed PMID: 16545965.
  32. Arimura H. Image-Based Computer-Assisted Radiation Therapy. Springer; 2017.