International Journal of Radiation Oncology * Biology * Physics
Volume 70, Issue 2 , Pages 590-598 , 1 February 2008

Variability of Four-Dimensional Computed Tomography Patient Models

  • Jan-Jakob Sonke, Ph.D.

      Affiliations

    • Corresponding Author InformationReprint requests to: Jan-Jakob Sonke, Ph.D., Department of Radiation Oncology, The Netherlands Cancer Institute/Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands. Tel: (+31) 20-512-1723; Fax: (+31) 20-6691101
    • ,
  • Joos Lebesque, Ph.D., M.D.
    • ,
  • Marcel van Herk, Ph.D.

Received 19 June 2007 ,Revised 22 August 2007 ,Accepted 24 August 2007.

References 

  1. Keall PJ, Mageras GS, Balter JM, et al. The management of respiratory motion in radiation oncology: Report of AAPM Task Group 76. Med Phys. 2006;33:3874–3900
  2. Ford EC, Mageras GS, Yorke E, et al. Respiration-correlated spiral CT: A method of measuring respiratory-induced anatomic motion for radiation treatment planning. Med Phys. 2003;30:88–97
  3. Vedam SS, Keall PJ, Kini VR, et al. Acquiring a four-dimensional computed tomography dataset using an external respiratory signal. Phys Med Biol. 2003;486:45–62
  4. Keall PJ. 4-Dimensional computed tomography imaging and treatment planning. Semin Radiat Oncol. 2004;14:81–90
  5. Rietzel E, Pan T, Chen GT. Four-dimensional computed tomography: Image formation and clinical protocol. Med Phys. 2005;32:874–889
  6. Wolthaus JW, Schneider C, Sonke J-J, et al. Mid-ventilation CT scan construction from four-dimensional respiration-correlated CT scans for radiotherapy planning of lung cancer patients. Int J Radiat Oncol Biol Phys. 2006;65:1560–1571
  7. Jaffray DA, Siewerdsen JH, Wong JW, et al. Flat-panel cone-beam computed tomography for image-guided radiation therapy. Int J Radiat Oncol Biol Phys. 2002;53:1337–1349
  8. Zijp L, Sonke J-J, van Herk M. Extraction of the respiratory signal from sequential thorax cone-beam x-ray images. Proceedings of the 14th ICCR (Seoul, Korea). Seoul, Republic of Korea: Jeong Publishing; 2004;p. 507–509
  9. Sonke J-J, Zijp L, Remeijer P, et al. Respiration correlated cone beam CT. Med Phys. 2005;32:1176–1186
  10. Bel A, Vos PH, Rodrigus PT, et al. High-precision prostate cancer irradiation by clinical application of an offline patient setup verification procedure using portal imaging. Int J Radiat Oncol Biol Phys. 1996;35:321–332
  11. Borst GR, Sonke J-J, Betgen A, et al. Kilovoltage cone beam CT setup measurements for lung cancer patients; First clinical results and comparison with electronic portal-imaging device. Int J Radiat Oncol Biol Phys. 2007;68:555–561
  12. Sonke J-J, van Herk M, Belderbos J, et al. An off-line 4D cone beam CT based correction protocol for lung tumor motion. Int J Radiat Oncol Biol Phys. 2005;63(Suppl. I):S389–S390
  13. van Herk M, Zijp L, van Remeijer P, et al. On-line 4D cone beam CT for daily correction of lung tumor position during hypofractionated radiotherapy. Proceedings of the 15th ICCR (Toronto, Canada). Oakville, ON, Canada: Novel Digital Publishing; 2007;
  14. Wolthaus JW, van Herk M, Muller M, et al. Fusion of respiration-correlated PET and CT scans: Correlated lung tumour motion in anatomical and functional scans. Phys Med Biol. 2005;50:1569–1583
  15. Smitsmans MH, de Bois J, Sonke J-J, et al. Automatic prostate localization on cone-beam CT scans for high precision image-guided radiotherapy. Int J Radiat Oncol Biol Phys. 2005;63:975–984
  16. Roche A, Malandain G, Pennec X, et al. Multimodal image registration by maximization of the correlation ratio, Research Report RR-3378, INRIA, published in MICCAI'98, Cambridge, MA, LNCS 1496, p. 1115–1124 (August 1998). Available at: http://www.inria.fr/rrrt/rr-3378. Accessed May 31, 2007.
  17. Sharpe MB, Moseley TG, Puidie TG, et al. The stability of mechanical calibration for a kV cone beam computed tomography system integrated with linear accelerator. Med Phys. 2006;33:136–144
  18. van Herk M, Remeijer P, Rasch C, et al. The probability of correct target dosage: Dose-population histograms for deriving treatment margins in radiotherapy. Int J Radiat Oncol Biol Phys. 2000;47:1121–1135
  19. Witte MG, van der Geer J, Schneider C, et al. The effects of target size and tissue density on the minimum margin required for random errors. Med Phys. 2004;31:3068–3079
  20. Lujan AE, Larsen EW, Haken JMBRKT. A method for incorporating organ motion due to breathing into 3D dose calculations. Med Phys. 1999;26:715–720
  21. Steenbakkers RJ, Duppen JC, Fitton I, et al. Observer variation in target volume delineation of lung cancer related to radiation oncologist-computer interaction: A ‘big brother’ evaluation. Radiother Oncol. 2005;77:182–190
  22. Wolthaus M, Sonke J-J, van Herk M, et al. Motion estimation and compensating in 4D CT; Images using phase-based constraint models. Proceedings of the 15th ICCR (Toronto, Canada). Oakville, ON, Canada: Novel Digital Publishing; 2007;
  23. Seppenwoolde Y, Shirato H, Kitamura K, 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. 2000;53:822–834
  24. Hugo G, Vargas C, Liang J, et al. Changes in the respiratory pattern during radiotherapy for cancer in the lung. Radiother Oncol. 2006;78:326–331
  25. Purdie TG, Moseley DJ, Bissonnette J-P, et al. Respiration correlated cone-beam computed tomography and 4DCT for evaluating target motion in stereotactic lung radiation therapy. Acta Oncol. 2006;45:915–922
  26. Blackall JM, Miquel SAME, McClelland JR, et al. MRI-based measurements of respiratory motion variability and assessment of imaging strategies for radiotherapy planning. Phys Med Biol. 2006;51:4147–4169
  27. Wulf J, Hadinger U, Oppitz U, et al. Stereotactic radiotherapy of extracranial targets: CT-simulation and accuracy of treatment in the stereotactic body frame. Radiother Oncol. 2000;57:225–236
  28. Chang J, Mageras GS, Yorke E, et al. Observation of interfractional variations in lung tumor position using respiratory gated and ungated megavoltage cone-beam computed tomography. Int J Radiat Oncol Biol Phys. 2007;67:1548–1558
  29. Hugo GD, Yan D, Liang J. Population and patient-specific target margins for 4D adaptive radiotherapy to account for intra- and interfraction variation in lung tumour position. Phys Med Biol. 2007;52:257–274
  30. Purdie TG, Bissonnette J-P, Franks K, et al. Cone-beam computed tomography for on-line image guidance of lung stereotactic radiotherapy: Localization, verification, and intrafraction tumor position. Int J Radiat Oncol Biol Phys. 2007;68:243–252
  31. Haasbeek CJA, Lagerwaard FJ, Cuijpers JP, et al. Is adaptive treatment planning required for stereotactic radiotherapy of stage I non-small-cell lung cancer?. Int J Radiat Oncol Biol Phys. 2007;67:1370–1374
  32. Nijkamp J, Wolthaus JW, Sonke J-J, et al. Mid-ventilation determination with automatic four-dimensional rigid grey-value registration on respiration-correlated computed tomography scans with moving lung tumours. Proceedings of the 15th ICCR (Toronto, Canada). Oakville, ON, Canada: Novel Digital Publishing; 2007;
  33. Yan D, Lockman D, Brabbins D, et al. An off-line strategy for constructing a patient-specific planning target volume in adaptive treatment process for prostate cancer. Int J Radiat Oncol Biol Phys. 2000;48:289–302

 Conflict of interest: part of this research was sponsored by Elekta Oncology Systems Ltd.

PII: S0360-3016(07)04074-6

doi: 10.1016/j.ijrobp.2007.08.067

International Journal of Radiation Oncology * Biology * Physics
Volume 70, Issue 2 , Pages 590-598 , 1 February 2008

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