Three-Dimensional Treatment Planning and Conformal Therapy

  • James A. Purdy
  • Philip Poortmans
  • Carlos A. Perez
Part of the Medical Radiology book series (MEDRAD)


Three-dimensional conformal radiation therapy (3DCRT) is now well established in routine clinical practice as an effective means of achieving higher tumor doses without increasing doses to critical normal structures. 3DCRT emphasizes a volumetric image-based virtual simulation approach based on the delineation of image-based tumor volume(s) and the associated microscopic disease volume(s), as well as the critical normal structures, for every individual patient. It should be understood that the 3D planning process puts increased demands on the radiation oncologist to specify tumor/target volume(s) and organs at risk with far greater accuracy than before. Moreover, this technology also places increased demands on the radiation oncology physicist and radiation technologist to insure adequate treatment planning and quality assurance measures are in place to accommodate the 3DCRT process, e.g., the need for increased precision in tumor imaging, patient set-up reproducibility, organ motion assessment, and treatment delivery verification. Readers will be able to appreciate the 3D planning approach and CRT much more fully, if they view it as a process, rather than viewing it as a particular beam configuration, or considering it simply as implementing certain technology. In this chapter, we discuss the physics and clinical aspects of 3D treatment planning and conformal therapy including volume definitions, planning approaches, planning tools, plan implementation and treatment verification.


Planning Target Volume Dose Distribution Intensity Modulate Radiation Therapy Clinical Target Volume Gross Tumor Volume 
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. Abdel-Wahab M, Rengan R, Curran B, Swerdloff S, Miettinen M, Field C, Ranjitkar S, Palta J, Tripuraneni P (2009) Integrating the healthcare enterprise in radiation oncology plug and play–the future of radiation oncology? Int J Radiat Oncol Biol Phys 76(2):333–336CrossRefGoogle Scholar
  2. Bentzen SM, Tucker SL (1997) Quantifying the position and steepness of radiation dose-response curves. Int J Radiat Biol 71:531–542PubMedCrossRefGoogle Scholar
  3. Bentzen SM, Constine LS, Deasy JO, Eisbruch A, Jackson A, Marks LB, Ten Haken RK, Yorke ED (2010) Quantitative analyses of normal tissue effects in the clinic (QUANTEC): an introduction to the scientific issues. Int J Radiat Oncol Biol Phys 76(3, Supplement 1):S3–S9PubMedCrossRefGoogle Scholar
  4. Bortfeld T, Jiang S, Rietzel E (2004) Effects of motion on the total dose distribution. Semin Radiat Oncol 14(1):41–51PubMedCrossRefGoogle Scholar
  5. Bortfeld T, Schmidt-Ullrich R, De Neve W, Wazer DE (2006) Image-guided IMRT, vol 3. Springer, BerlinCrossRefGoogle Scholar
  6. Brahme A (1984) Dosimetric precision requirements in radiation therapy. Acta Radiol Oncol 23:379–391PubMedCrossRefGoogle Scholar
  7. Caldwell CB, Mah K, Skinner M, Danjoux CE (2003) Can PET provide the 3D extent of tumor motion for individualized internal target volumes? A phantom study of the limitations of CT and the promise of PET. Int J Radiat Oncol Biol Phys 55(5):1381–1393PubMedCrossRefGoogle Scholar
  8. Chen GTY, Kung JH, Beaudette KP (2004) Artifacts in computed tomography scanning of moving objects. Semin Radiat Oncol 14(1):19–26PubMedCrossRefGoogle Scholar
  9. Chino JP, Lee WR, Madden R, Sims EL, Kivell TL, Doyle SK, Mitchell TL, Hoppenworth EJ, Marks LB (2011) Teaching the anatomy of oncology: evaluating the impact of a dedicated oncoanatomy course. Int J Radiat Oncol Biol Phys 79(3):853–859PubMedCrossRefGoogle Scholar
  10. Das IJ, Chang C-W, Chopra KL, Mitra RK, Srivastava SP, Glatstein E (2008) Intensity-modulated radiation therapy dose prescription, recording, and delivery: patterns of variability among institutions and treatment planning systems. JNCI 100(5):300–307PubMedCrossRefGoogle Scholar
  11. Drzymala RE, Mohan R, Brewster L, Chu J, Goitein M, Harms W, Urie M (1991) Dose-volume histograms. Int J Radiat Oncol Biol Phys 21(1):71–78PubMedCrossRefGoogle Scholar
  12. Emami B, Lyman J, Brown A, Burman C, Coia L, Goitein M, Munzenrider J, Sloan L, Shank B, Wesson M (1991) Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 21:109–122PubMedCrossRefGoogle Scholar
  13. Girinsky T, Van Der Maazen R, Specht L, Aleman B, Poortmans P, Lievens Y, Meijnders P, Ghalibafian M, Meerwaldt J, Noordijk E (2006) Involved-node radiotherapy (INRT) in patients with early Hodgkin lymphoma: concepts and guidelines. Radiother Oncol 79:270–277PubMedCrossRefGoogle Scholar
  14. Girinsky T, Specht L, Ghalibafian M, Edeline V, Bonniaud G, Van Der Maazen R, Aleman B, Paumier A, Meijnders P, Lievens Y, Noordijk E, Poortmans P (2008) EORTC-GELA Lymphoma group. The conundrum of Hodgkin lymphoma nodes: to be or not to be included in the involved node radiation fields. The EORTC-GELA lymphoma group guidelines. Radiother Oncol 88:202–210PubMedCrossRefGoogle Scholar
  15. Goitein M (1987) The probability of controlling an inhomogeneously irradiated tumor. In: Goitein M, Lyman J, Maor M, Sontag MR (eds) Report of the working groups on the evaluation of treatment planning for particle beam radiotherapy. Radiation Research Program, Division of Cancer Treatment, National Cancer Institute, Bethesda, MDGoogle Scholar
  16. 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
  17. Gregoire V, Coche E, Cosnard G, Hamoir M, Reychler H (2000) Selection and delineation of lymph node target volumes in head and neck conformal radiotherapy. Proposal for standardizing terminology and procedure based on the surgical experience. Radiother Oncol 56(2):135–150PubMedCrossRefGoogle Scholar
  18. Gregoire V, Levendag P, Ang KK, Bernier J, Braaksma M, Budach V, Chao C, Coche E, Cooper JS, Cosnard G (2003) CT-based delineation of lymph node levels and related CTVs in the node-negative neck: DAHANCA, EORTC, GORTEC, NCIC, RTOG consensus guidelines. Radiother Oncol 69(3):227–236PubMedCrossRefGoogle Scholar
  19. Hall WH, Guiou M, Lee NY, Dublin A, Narayan S, Vijayakumar S, Purdy JA, Chen AM (2008) Development and validation of a standardized method for contouring the brachial plexus: preliminary dosimetric analysis among patients treated with IMRT for head-and-neck cancer. Int J Radiat Oncol Biol Phys 72(5):1362–1367PubMedCrossRefGoogle Scholar
  20. Holmes T, Das R, Low D, Yin F-F, Balter J, Palta J, Eifel P (2009) American society for radiation oncology recommendations for documenting intensity-modulated radiation therapy treatments. Int J Radiat Oncol Biol Phys 74(5):1311–1318PubMedCrossRefGoogle Scholar
  21. Hurkmans CW, Meijer GJ, van Vliet-Vroegindeweij C, Van der Sangen MJ, Cassee J (2006) High-dose simultaneously integrated breast boost using intensity-modulated radiotherapy and inverse optimization. Int J Radiat Oncol Biol Phys 66(3):923–930PubMedCrossRefGoogle Scholar
  22. ICRU (1993) ICRU Report 50: prescribing, recording, and reporting photon beam therapy. In: International commission on radiation units and measurements, Bethesda, MDGoogle Scholar
  23. ICRU (1999) ICRU Report 62: prescribing, recording, and reporting photon beam therapy (Supplement to ICRU Report 50). In: International commission on radiation units and measurements, Bethesda, MDGoogle Scholar
  24. ICRU (2010) ICRU Report 83: prescribing, recording, and reporting photon-beam intensity-modulated radiation therapy (IMRT). J ICRU 10(1) Google Scholar
  25. Jaffray DA, Siewerdsen JH, Wong JW, Martinez AA (2002) Flat-panel cone-beam computed tomography for image-guided radiation therapy. Int J Radiat Oncol Biol Phys 53(5):1337–1349PubMedCrossRefGoogle Scholar
  26. Källman P, Lind BK, Brahme A (1992) An algorithm for maximizing the probability of complication free tumor control in radiation therapy. Int J Radiat Oncol Biol Phys 37:871–890Google Scholar
  27. Kutcher G, Berman C (1989) Calculation of complication probability factors for non-uniform tissue irradiation: the effective volume method. Int J Radiat Oncol Biol Phys 16:1623–1630PubMedCrossRefGoogle Scholar
  28. Langen KM, Jones DTL (2001) Organ motion and its management. Int J Radiat Oncol Biol Phys 50(1):265–278PubMedCrossRefGoogle Scholar
  29. Levitt SH, Perez CA, Hui S, Purdy JA (2008) Evolution of computerized radiotherapy in radiation oncology: potential problems and solutions. Int J Radiat Oncol Biol Phys 70(4):978–986PubMedCrossRefGoogle Scholar
  30. Lyman JT, Wolbarst AB (1987) Optimization of radiation therapy. III. A method of assessing complication probabilities from dose-volume histograms. Int J Radiat Oncol Biol Phys 13:103–109PubMedCrossRefGoogle Scholar
  31. Lyman JT, Wolbarst AB (1989) Optimization of radiation therapy. IV: A dose-volume histogram reduction algorithm. Int J Radiat Oncol Biol Phys 17(2):433–436PubMedCrossRefGoogle Scholar
  32. Marks LB, Ten Haken RK, Martel MK (2010a) Guest editor’s introduction to QUANTEC: a users guide. Int J Radiat Oncol Biol Phys 76(3, Supplement 1):S1–S2PubMedCrossRefGoogle Scholar
  33. Marks LB, Yorke ED, Jackson A, Ten Haken RK, Constine LS, Eisbruch A, Bentzen SM, Nam J, Deasy JO (2010b) Use of normal tissue complication probability models in the clinic. Int J Radiat Oncol Biol Phys 76(3, Supplement 1):S10–S19PubMedCrossRefGoogle Scholar
  34. Matzinger O, Gerber E, Bernstein Z, Maingon P, Haustermans K, Bosset JF, Gulyban A, Poortmans P, Collette L, Kuten A (2009) EORTC-ROG expert opinion: radiotherapy volume and treatment guidelines for neoadjuvant radiation of adenocarcinomas of the gastroesophageal junction and the stomach. Radiother Oncol 92:164–175PubMedCrossRefGoogle Scholar
  35. McGary JE, Grant W, Woo SY, Butler EB (1997) Comment on reporting and analyzing dose distributions: a concept of equivalent uniform dose. Med Phys 24(8):1323–1324 [Med. Phys. 24, 103–109 (1997)]PubMedCrossRefGoogle Scholar
  36. McGary JE, Grant W, Woo SY (2000) Applying the equivalent uniform dose formulation based on the linear-quadratic model to inhomogeneous tumor dose distributions: caution for analyzing and reporting. J Appl Clin Med Phys 1(4):126–137PubMedCrossRefGoogle Scholar
  37. Meyer JL, Purdy JA (eds) (1996) 3-D conformal radiotherapy: a new era in the irradiation of cancer. Karger, BaselGoogle Scholar
  38. Milano MT, Constine LS, Okunieff P (2007) Normal tissue tolerance dose metrics for radiation therapy of major organs. Semin Radiat Oncol 17(2):131PubMedCrossRefGoogle Scholar
  39. Miralbell R, Vees H, Lozano J, Khan H, Mollà M, Hidalgo A, Linero D, Rouzaud M (2007) Endorectal MRI assessment of local relapse after surgery for prostate cancer: a model to define treatment field guidelines for adjuvant radiotherapy in patients at high risk for local failure. Int J Radiat Oncol Biol Phys 67(2):356–361PubMedCrossRefGoogle Scholar
  40. Moiseenko V, Deasy JO, Van Dyk J (2005) Radiobiological modeling for treatment planning. In: Van Dyk J (ed) The modern technology of radiation oncology, vol 2. Medical Physics Publishing, Madison, WI, pp 185–220Google Scholar
  41. Mutic S, Palta JR, Butker EK, Das IJ, Huq MS, Loo L-HD, Salter BJ, McCollough CH, Van Dyk J (2003) Quality assurance for computed-tomography simulators and the computed-tomography-simulation process: report of the AAPM radiation therapy committee task group no. 66. Med Phys 30(10):2762–2792PubMedCrossRefGoogle Scholar
  42. Niemierko A (1997a) Reporting and analyzing dose distributions: a concept of equivalent uniform dose. Med Phys 24(1):103–110PubMedCrossRefGoogle Scholar
  43. Niemierko A (1997b) Response to comment on reporting and analyzing dose distributions: a concept of equivalent uniform dose. Med Phys 24(8):1325–1327 [Med. Phys. 24, 1323–1324 (1997)]CrossRefGoogle Scholar
  44. Niemierko A (1999) A generalized concept of equivalent uniform dose (EUD) (abstract). Med Phys 26:1100Google Scholar
  45. Niemierko A, Goitein M (1991) Calculation of normal tissue complication probability and dose-volume histogram reduction schemes for tissues with a critical element architecture. Radiother Oncol 20:166–176PubMedCrossRefGoogle Scholar
  46. Niemierko A, Goitein M (1993) Modeling of normal tissue response to radiation: the critical volume module. Int J Radiat Oncol Biol Phys 25:135–145PubMedCrossRefGoogle Scholar
  47. Olsen DR, Kambestad BK, Kristoffersen DT (1994) Calculation of radiation induced complication probabilities for brain, liver and kidney, and the use of a reliability model to estimate critical volume fractions. Br J Radiol 67:1218–1225PubMedCrossRefGoogle Scholar
  48. Perez CA, Purdy JA, Harms WB, Gerber RL, Matthews JW, Grigsby PW, Graham ML, Emami B, Lee HK, Michalski JM, Baker S (1994) Design of a fully integrated three-dimensional computed tomography simulator and preliminary clinical evaluation. Int J Radiat Oncol Biol Phys 30(4):887–897PubMedCrossRefGoogle Scholar
  49. Poortmans PMP, Ataman F, Bernard Davis J, Bartelink H, Horiot J-C, Pierart M, Collette L, Van Tienhoven G (2007) Guidelines for target volume definition in post-operative radiotherapy for prostate cancer, on behalf of the EORTC radiation oncology group. Radiother Oncol 82:121–127CrossRefGoogle Scholar
  50. Purdy JA (1996) 3-D Radiation treatment planning: a new era. In: Meyer JL, Purdy JA (eds) Frontiers of radiation therapy and oncology. 3-D Conformal radiotherapy: a new era in the irradiation of cancer, vol. 29. Front Radiat Ther Oncol, Karger, Basel, pp 1–16Google Scholar
  51. Purdy JA (2007) From new frontiers to new standards of practice: advances in radiotherapy planning and delivery. In: Meyer JL (ed) IMRT, IGRT, SBRT—Advances in the treatment planning and delivery of radiotherapy, vol. 40. Front Radiat Ther Oncol, Karger, Basel, pp 18–39Google Scholar
  52. Purdy JA, Wong JW, Harms WB, Drzymala RE, Emami B, Matthews JW, Krippner K, Ramchander PK (1987) Three-dimensional radiation treatment planning system. In: Bruinvis IAD, van der Giessen PH, van Kleffens HJ, Wittkamper FW (eds) Proceedings of the 9th international conference on the use of computers in radiation therapy, Elsevier Science Publishers, Scheveningen, The Netherlands, 22–25 June 1987, pp 227–279Google Scholar
  53. Purdy JA, Harms WB, Matthews JW, Drzymala RE, Emami B, Simpson JR, Manolis J, Rosenberger FU (1993) Advances in 3-dimensional radiation treatment planning systems: room-view display with real time interactivity. Int J Radiat Oncol Biol Phys 27(4):933–944PubMedCrossRefGoogle Scholar
  54. Qi XS, White J, Rabinovitch R, Merrell K, Sood A, Bauer A, Wilson JF, Miften M, Li XA (2010) Respiratory organ motion and dosimetric impact on breast and nodal irradiation. Int J Radiat Oncol Biol Phys 78(2):609–617PubMedCrossRefGoogle Scholar
  55. Reinstein LE, McShan D, Webber BM, Glicksman AS (1978) A computer-assisted three-dimensional treatment planning system. Radiology 127:259–264PubMedGoogle Scholar
  56. Rietzel E, Chen GT, Choi NC, Willet CG (2005a) Four-dimensional image-based treatment planning: target volume segmentation and dose calculation in the presence of respiratory motion. Int J Radiat Oncol Biol Phys 61(5):1535–1550PubMedCrossRefGoogle Scholar
  57. Rietzel E, Pan T, Chen GT (2005b) Four-dimensional computed tomography: image formation and clinical protocol. Med Phys 32(4):874–889PubMedCrossRefGoogle Scholar
  58. Schultheiss TE, Orton CG, Peck RA (1983) Models in radiotherapy: volume effects. Med Phys 10:410–415PubMedCrossRefGoogle Scholar
  59. Senan S, De Ruysscher D, Giraud P, Mirimanoff R, Budach V (2004) Literature-based recommendations for treatment planning and execution in high-dose radiotherapy for lung cancer; on behalf of the radiotherapy group of the European organization for research and treatment of cancer (EORTC). Radiother Oncol 71(2):139–146PubMedCrossRefGoogle Scholar
  60. Sherouse GW, Novins K, Chaney EL (1990) Computation of digitally reconstructed radiographs for use in radiotherapy treatment design. Int J Radiat Oncol Biol Phys 18(3):651–658PubMedCrossRefGoogle Scholar
  61. Stroom JC, Heijmen BJM (2006) Limitations of the planning organ at risk volume (PRV) concept. Int J Radiat Oncol Biol Phys 66(1):279–286PubMedCrossRefGoogle Scholar
  62. Symon Z, Tsvang L, Wygoda M, Ben-Yoseph R, Corn BW, Poortmans P, Portnoy O, Pfeffer MR (2011) An interobserver study of prostatic fossa clinical target volume delineation in clinical practice: Are regions of recurrence adequately targeted?. Am J Clin Oncol, [Epub ahead of print] Google Scholar
  63. van der Laan HP, Dolsma WV, Maduro JH, Korevaar EW, Hollander M, Langendijk JA (2007) Three-dimensional conformal simultaneously integrated boost technique for breast-conserving radiotherapy. Int J Radiat Oncol Biol Phys 68(4):1018–1023PubMedCrossRefGoogle Scholar
  64. van Herk M (2004) Errors and margins in radiotherapy. Semin Radiat Oncol 14(1):52–64PubMedCrossRefGoogle Scholar
  65. van Herk M, Remeijer P, Lebesque JV (2002) Inclusion of geometric uncertainties in treatment plan evaluations. Int J Radiat Oncol Biol Phys 52(5):1407–1422PubMedCrossRefGoogle Scholar
  66. van Mourik AM, Elkhuizen PHM, Minkema D, Duppen JC, van Vliet-Vroegindeweij C (2010) Multiinstitutional study on target volume delineation variation in breast radiotherapy in the presence of guidelines. Radiother Oncol 94(3):286–291PubMedCrossRefGoogle Scholar
  67. Webb S (2000) Intensity-modulated radiation therapy. Institute of Physics Publishing, BristolGoogle Scholar
  68. Willins J, Kachnic L (2008) Clinically relevant standards for intensity-modulated radiation therapy dose prescription. JNCI 100(5):288–290PubMedCrossRefGoogle Scholar
  69. Withers HR, Taylor JMG, Maciejewski B (1988) Treatment volume and tissue tolerance. Int J Radiat Oncol Biol Phys 14:751–759PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • James A. Purdy
    • 1
  • Philip Poortmans
    • 2
  • Carlos A. Perez
    • 3
  1. 1.Department of Radiation OncologyUniversity of California Davis Medical CenterSacramentoUSA
  2. 2.Department of Radiation OncologyInstituteVerbeetenTilburgThe Netherlands
  3. 3.Department of Radiation OncologyMallinckrodt Institute of Radiology, Washington University School of MedicineSt. LouisUSA

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