Simulation in the Determination and Definition of Treatment Volume and Treatment Planning

  • Sasa Mutic
  • Mary Coffey
  • James A. Purdy
  • Jeff M. Michalski
  • Carlos A. Perez
Part of the Medical Radiology book series (MEDRAD)


One of the cornerstones of modern radiation therapy practice are volumetric patient image datasets from computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and ultrasound (US). Current radiation therapy imaging devices (simulators) include (1) Conventional Simulators (based on conventional x-ray radiography planar imaging); (2) CT-simulators (based on CT scanners); (3) PET/CT-simulators (based on PET/CT scanners and); (4) MR-simulators (based on MR scanners). The radiation therapy simulator has been an integral component of the treatment planning process since the 1960s. Conventional simulators are designed to mimic the linear accelerator geometry while providing a diagnostic-quality x-ray beam for anatomic imaging. Due to the increased use of 3D imaging for treatment planning, conventional simulators are less popular than in the past. Still, this technology continues to be developed and retains its presence in most radiation oncology departments. Shortly after the introduction of clinical CT scanners in early 1970s it was realized that this imaging modality had much to offer in a radiation oncology setting because they provided a volumetric view of the patient’s normal and tumor anatomy with excellent spatial accuracy. In response, CT simulators were developed during the 1980s and 1990s and today CT simulator is the main imaging device in radiation therapy. CT simulators have developed to a point where CT scanner manufacturers are designing scanners specifically for CT simulation purposes. PET imaging can also provide valuable information about tumors and PET/CT scanners have been implemented as radiation therapy simulators and can be found in many radiotherapy centers. Finally, MRI scanners have also been implemented and are used for treatment simulation in radiation therapy. MRI scanners are less commonly found in radiotherapy departments, but due to the imaging advantages that MRI has to offer it is expected that the use of MRI scanner for radiotherapy simulation will experience significant growth. These devices have enabled better delineation of treatment volumes and critical structures while improving our ability to image patients in better treatment positions and with improved immobilization devices. Successful radiation therapy imaging (simulation) program must consider capabilities of individual imaging equipment, immobilization equipment, and the needs of individual techniques and treatment sites. This chapter describes the radiation therapy simulation process, design and features of conventional, CT, PET/CT, and MRI simulators, and their use for treatment planning.


Positron Emission Tomography Compute Tomography Image Positron Emission Tomography Image Cone Beam Compute Tomography Treatment Planning System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Bahner ML, Debus J, Zabel A, Levegrun S, Van Kaick G (1999) Digitally reconstructed radiographs from abdominal CT scans as a new tool for radiotherapy planning. Invest Radiol 34:643–647PubMedCrossRefGoogle Scholar
  2. Bailey DL (2003) Data acquisition and performance characterization in PET. In: Valk PE, Bailey DL, Townsend DW, Maisey MN (eds) Positron emission tomography: basic science and clinical practice. Springer, London, pp 69–90Google Scholar
  3. Bailey DL, Karp JS, Surti S (2003) Physics and instrumentation in PET. In: Valk PE, Bailey DL, Townsend DW, Maisey MN (eds) Positron emission tomography: basic science and clinical practice. Springer, London, pp 41–67Google Scholar
  4. Beavis AW, Gibbs P, Dealey RA et al (1998) Radiotherapy treatment planning of brain tumors using MRI alone. Br J Radiol 71:544–548PubMedGoogle Scholar
  5. Beyer T, Townsend DW, Brun T, Kinahan PE, Charron M, Roddy R et al (2000) A combined PET/CT scanner for clinical oncology. J Nucl Med 41:1369–1379PubMedGoogle Scholar
  6. Bushberg JT, Seibert JA, Leidholdt EM, Boone JM (2002) Fluoroscopy, in the essential physics of medical imaging, 2nd edn. Lippincott Williams &Wilkins, Philadelphia, pp 231–254Google Scholar
  7. Chao KSC, Bosch WR, Mutic S, Lewis JS, Dehdashti F, Mintun MA, Dempsey JF, Perez CA, Purdy JA, Welch MJ (2001) A novel approach to overcome hypoxic tumor resistance Cu-ATSM-guided intensity-modulated radiation therapy. Int J Radiat Oncol Biol Phys 49:1171–1182PubMedCrossRefGoogle Scholar
  8. Chen L, Price R, Wang L, Li J, Qin L, McNeeley S, Ma C, Freedman G, Pollack A (2004) MRI-Based treatment planning for radiotherapy: dosimetric verification for prostate IMRT. Int J Radiat Oncol Biol Phys 60:636–647PubMedGoogle Scholar
  9. Coia LR, Schultheiss TE, Hanks G (eds) (1995) A practical guide to CT simultion. Advanced Medical Publishing, Madison, WIGoogle Scholar
  10. Conway J, Robinson MH (1997) CT virtual simulation. Br J Radiol 70:S106–S118PubMedGoogle Scholar
  11. Curry TS, Dowdey JE, Murry RC (1990) Computed tomography. Chriestensen’s physics of diagnostic radiology, 4th edn. Lea & Febiger, Malvern, Pennsylvania, pp 289–322Google Scholar
  12. Dizendorf EV, Baumert BG, von Schulthess GK, Lutolf UM, Steinert HC (2003) Impact of whole-body 18F-FDG PET on staging and managing patients for radiation therapy. J Nucl Med 44:24–29PubMedGoogle Scholar
  13. Garcia-Ramirez JL, Mutic S, Dempsey JF, Low DA, Purdy JA (2002) Performance evaluation of an 85 cm bore X-ray computed tomography scanner designed for radiation oncology and comparison with current diagnostic CT scanners. Int J Radiat Oncol Biol Phys 52:1123–1131PubMedCrossRefGoogle Scholar
  14. Goitein M, Abrams M (1983) Multi-dimensional treatment planning: I. Delineation of anatomy. Int J Radiat Oncol Biol Phys 9:777–787PubMedCrossRefGoogle Scholar
  15. Goitein M, Abrams M, Rowell D, Pollari H, Wiles J (1983) Multi-dimensional treatment planning: II. Beam’s eye-view, back projection, and projection through CT sections. Int J Radiat Oncol Biol Phys 9:789–797PubMedCrossRefGoogle Scholar
  16. Griffiths SE et al (2004) Recommendations on best practice for radiographer set-up of conformal radiotherapy treatment for patients with prostate cancer: experience developed during the MRC RT01 trial (ISRTCN 47772397). J Radiother Pract 4:107–117CrossRefGoogle Scholar
  17. Houweling AC, Van Der Meer S et al (2010) Improved immobilization using an individual head support in head-and-neck cancer patients. Radiother Oncol 96:100–103PubMedCrossRefGoogle Scholar
  18. International Commission of Radiation Units and Measurements (1993) ICRU Report No. 50 Prescribing, recording, and reporting photon beam therapy. International Commission of Radiation Units and Measurements, Bethesda, MDGoogle Scholar
  19. International Commission of Radiation Units and Measurements (1999) ICRU Report No. 62 Prescribing, recording and reporting photon beam therapy (Supplement to ICRU Report 50). International Commission of Radiation Units and Measurements, Bethesda, MDGoogle Scholar
  20. Kalender WA, Polacin A (1991) Physical performance characteristics of spiral CT scanning. Med Phys 18:910–915PubMedCrossRefGoogle Scholar
  21. Kalender WA, Polacin A, Suss C (1994) A comparison of conventional and spiral CT: an experimental study on the detection of spherical lesions. J Comput Assist Tomogr 18:167–176 Published erratum appears in J Comput Assist Tomogr 18:671PubMedCrossRefGoogle Scholar
  22. Keall PJ, Mageras GS, Balter JM, Emery RS, Forester KM, Jiang SB, Kapatoes JM, Kubo HD, Low DA, Murphy MJ, Murray BR, Ramsey CR, van Herk MB, Vedam SS, Wong JW, Yorke E (2006) The management of respiratory motion in radiation oncology. Med Phys 33:3874–3900PubMedCrossRefGoogle Scholar
  23. Klingenbeck_Regn K, Schaller S, Flohr T, Ohnesorge B, Kopp AF, Baum U (1999) Subsecond multi-slice computed tomography: basics and applications. Eur J Radiol 31:110–124PubMedCrossRefGoogle Scholar
  24. Lavely WC, Scarfone C, Cevikalp H, Rui L, Byrne DW, Cmelak AJ, Dawant B, Price RR, Hallahan DE, Fitzpatrick JM (2004) Phantom validation of coregistration of PET and CT for image-guided radiotherapy. Med Phys 31:1083–1092PubMedCrossRefGoogle Scholar
  25. Lee YK, Bollet M, Charles-Edwards G et al (2003) Radiotherapy treatment planning of prostate cancer using magnetic resonance imaging alone. Radiother Oncol 2:203–216CrossRefGoogle Scholar
  26. Ling CC, Humm J, Larson S, Amols H, Fuks Z, Leibel S, Koutcher JA (2000) Towards multidimensional radiotherapy (MD-CRT): biological imaging and biological conformality. Int J Radiat Oncol Biol Phys 47:551–560PubMedCrossRefGoogle Scholar
  27. Mah D, Steckner M, Palacio E et al (2002) Characteristics and quality assurance of dedicated open 0.23 T MRI for radiation therapy simulation. Med Phys 29:2541–2547PubMedCrossRefGoogle Scholar
  28. McGee KP, Das IJ, Sims C (1995) Evaluation of digitally reconstructed radiographs (DRRs) used for clinical radiotherapy: a phantom study. Med Phys 22:1815–1827PubMedCrossRefGoogle Scholar
  29. Mubata CD et al (1998) Portal imaging protocol for radical dose-escalated radiotherapy treatment of prostate cancer. Int J Radiat Oncol Biol Phys 40:221–231PubMedCrossRefGoogle Scholar
  30. Mutic S, Dempsey JF, Bosch WR, Low DA, Drzymala RE, Chao KSC, Goddu SM, Cutler PD, Purdy JA (2001) Multimidality image registration quality assurance for conformal three-dimensional treatment planning. Int J Radiat Oncol Biol Phys 51:255–260PubMedCrossRefGoogle Scholar
  31. Mutic S, Palta JR, Butker E, Das IJ, Huq MS, Loo LD, Salter BJ, McCollough CH, Van Dyk J (2003) Quality assurance for CT simulators and the CT simulation process: report of the AAPM radiation therapy committee task group No. 66. Med Phys 30:2762–2792PubMedCrossRefGoogle Scholar
  32. National Electrical Manufacturers Association (NEMA) (1998) DICOM PS 3 (set). Digital imaging communictaions in medicine (DICOM)Google Scholar
  33. Okamoto Y, Kodama A, Kono M (1997) Development and clinical application of MR simulation system for radiotherapy planning: with reference to intracranial and head and neck regions. Nippon Igaku Hoshasen Gakkai Zasshi 57(4):203–210PubMedGoogle Scholar
  34. Piwnica-Worms D (2000) Molecular imaging. In: Presented at the 48th annual meeting of the association of university radiologists, Orlando, FL, 6–9 Apr 2000Google Scholar
  35. Potter R, Heil B, Schneider L et al (1992) Sagittal and coronal planes from MRI for treatment planning in tumors of brain, head and neck: MRI assisted simulation. Radiother Oncol 23:127–130PubMedCrossRefGoogle Scholar
  36. Schubert K, Wenz F, Krempien R, Schramm O, Sroka-Perez G, Schraul P, Wannenmacher M (1999) Possibilities of an open magnetic resonance scanner integration in therapy simulation and three-dimensional radiotherapy planning. Strahlenther Onkol 175(5):225–231PubMedCrossRefGoogle Scholar
  37. Sherouse G, Mosher KL, Novins K, Rosenman EL, Chaney EL (1987) Virtual simulation: concept and implementation. In: Bruinvis IAD, van der Giessen PH, van Kleffens HJ, Wittkamper FW (eds) 9th international conference on the use of computers in radiation therapy. North-Holland Publishing Co., Amsterdam, pp 433–436Google Scholar
  38. Sherouse GW, Novins K, Chaney EL (1990a) Computation of digitally reconstructed radiographs for use in radiotherapy treatment design. Int J Radiat Oncol Biol Phys 18:651–658PubMedCrossRefGoogle Scholar
  39. Sherouse GW, Bourland JD, Reynolds K (1990b) Virtual simulation in the clinical setting: some practical considerations. Int J Radiat Oncol Biol Phys 19:1059–1065PubMedCrossRefGoogle Scholar
  40. Townsend DW, Carney JP, Yap JT, Hall NC (2004) PET/CT today and tomorrow. J Nucl Med 45(Supl(1)):4S–14SPubMedGoogle Scholar
  41. Van Lin NJTH, Van Der Vight L et al (2003) Set-up improvement in head and neck radiotherapy using a 3D off-line EPID-based correction protocol and a customized head and neck support. Radiother Oncol 68(2):137–148PubMedCrossRefGoogle Scholar
  42. Yang C, Guiney M, Hughes P, Leung S, Liew KH, Matar J et al (2000) Use of digitally reconstructed radiographs in radiotherapy treatment planning and verification. Australas Radiol 44:439–443PubMedCrossRefGoogle Scholar
  43. Young H, Baum R, Cremerius U, Herholz K, Hoekstra O, Lammertsma AA, Pruim J, Price P (1999) Measurement of clinical and subclinical tumour response using [18F]-fluorodeoxyglucose and positron emission tomography: review and 1999 EORTC recommendations. European Organization for Research and Treatment of Cancer (EORTC) PET Study Group. Eur J Cancer 13:1773–1782CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg  2011

Authors and Affiliations

  • Sasa Mutic
    • 1
  • Mary Coffey
    • 2
  • James A. Purdy
    • 3
  • Jeff M. Michalski
    • 1
  • Carlos A. Perez
    • 4
  1. 1.Department Of Radiation OncologyWashington University School of Medicine, Mallinckrodt Institute of Radiology, Siteman Cancer CenterSt. LouisUSA
  2. 2.Discipline of Radiation TherapySchool of Medicine, Trinity Centre for Health Sciences, St. James’ HospitalDublin 8Ireland
  3. 3.Department of Radiation OncologyUniversity of California, DavisSacramentoUSA
  4. 4.Department of Radiation OncologyWashington University School of Medicine, Mallinckrodt Institute of Radiology, Siteman Cancer CenterSt. LouisUSA

Personalised recommendations