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Conformal Radiotherapy: Simulation and Contouring

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Basics of Planning and Management of Patients during Radiation Therapy

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Abstract

The difference between conventional radiotherapy and conformal radiotherapy lies in the use of planning CT to define tumour volume and design treatment portals wherein treatment positions are checked by CT scans, target volumes and OARs defined and beams positioned. After planning CT is done with patient immobilized in treatment position, the treatment tumour volumes and normal organs are drawn or contoured on the CT images, and the radiation portals are designed to conform to the tumour volumes. Thus, conformal therapy requires more complex shaping of the dose distribution than does conventional radiotherapy since shaping of fields and the selection of beam directions are based on 3D reconstruction of the CT images of the patient. These images projected in a beam’s eye view (BEV) format permit selection of beam directions with better avoidance of normal tissues. After this computer-aided algorithms help in dose calculation and meeting plan objectives.

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References

  1. Xing L, et al. Physics of intensity modulated radiation therapy. In: Mundt AJ, Roeske JC, editors. Intensity modulated radiation therapy: a clinical perspective. Hamilton & London: BC Decker Inc.; 2005. p. 20–52.

    Google Scholar 

  2. Xing L, et al. Dosimetric effects of patient displacement and collimator and gantry angle misalignment on intensity modulated radiation therapy. Radiother Oncol. 2000;56:97–108.

    Article  CAS  PubMed  Google Scholar 

  3. Hwang AB, et al. Can positron emission tomography (PET) or PET/computed tomography (CT) acquired in a nontreatment position be accurately registered to a head-and-neck radiotherapy planning CT? Int J Radiat Oncol Biol Phys. 2009;73(2):578–84.

    Article  PubMed  Google Scholar 

  4. Chen L, et al. MRI-based treatment planning for radiotherapy: dosimetric verification for prostate IMRT. Int J Radiat Oncol Biol Phys. 2004;60(2):636–47.

    Article  PubMed  Google Scholar 

  5. International Commission on Radiation Units and Measurements, (ICRU). Prescribing, recording, and reporting photon beam therapy. International Com-mission on Radiation Units and Measurements, ICRU Report 50, ICRU, Bethesda; 1993.

    Google Scholar 

  6. International Commission on Radiation Units and Measurements, (ICRU). Prescribing, recording, and reporting photon beam therapy (Supplement to ICRU Report 50). ICRU Report 62, ICRU, Bethesda; 1999.

    Google Scholar 

  7. Myerson RJ, et al. Elective clinical target volumes for conformal therapy in anorectal cancer: a Radiation Therapy Oncology Group consensus panel contouring atlas. Int J Radiat Oncol Biol Phys. 2008;74(3):824–30.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Gregoire V, et al. CT-based delineation of lymph node levels and related CTVs in the node-negative neck: DAHANCA, EORTC, GORTEC, NCIC, RTOG consensus guidelines. Radiother Oncol. 2003;69(3):227–36.

    Article  PubMed  Google Scholar 

  9. Chao M, et al. Automated contour mapping with a regional deformable model. Int J Radiat Oncol Biol Phys. 2008;70:5599–608.

    Article  Google Scholar 

  10. Chao M, et al. Automated contour mapping using sparse volume sampling for 4D radiation therapy. Med Phys. 2007;34:4023–9.

    Article  PubMed  Google Scholar 

  11. Kashani R, et al. Objective assessment of deformable image registration in radiotherapy: a multi-institution study. Med Phys. 2008;35(12):5944–53.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Wang H, et al. Implementation and validation of a three-dimensional deformable registration algorithm for targeted prostate cancer radiotherapy. Int J Radiat Oncol Biol Phys. 2005;61(3):725–35.

    Article  PubMed  Google Scholar 

  13. Ling CC, Humm J, Larson S, et al. Towards multidimensional radiotherapy (MD-CRT): biological imaging and biological conformality. Int J Radiat Oncol Biol Phys. 2000;47:551–60.

    Article  CAS  PubMed  Google Scholar 

  14. Frank SJ, Chao KS, Schwartz DL, et al. Technology insight: PET and PET/CT in head and neck tumor staging and radiation therapy planning. Nat Clin Pract Oncol. 2005;2:526–33.

    Article  PubMed  Google Scholar 

  15. Bentzen SM, Constine LS, Deasy JO, Eisbruch A, Jackson A, Marks LB, Ten Haken RK, Yorke ED. Quantitative analyses of normal tissue effects in the clinic (QUANTEC): an introduction to the scientific issues. Int J Radiat Oncol Biol Phys. 2010;76:S36–41.

    Article  Google Scholar 

  16. Goitein M, et al. Multidimensional treatment planning. II: beam’s eye view, back projection and projection through CT sections. Int J Radiat Oncol Biol Phys. 1983;9:789–97.

    Article  CAS  PubMed  Google Scholar 

  17. McShan DL, Fraass BA, Lichter AS. Full integration of the beam’s eye view concept into computerized treatment planning. Int J Radiat Oncol Biol Phys. 1990;18:1485–94.

    Article  CAS  PubMed  Google Scholar 

  18. Pugachev A, et al. Role of beam orientation optimization in intensity-modulated radiation therapy. Int J Radiat Oncol Biol Phys. 2001;50(2):551–60.

    Article  CAS  PubMed  Google Scholar 

  19. Pugachev A, Xing L. Computer assisted beam orientation selection in IMRT. Phys Med Biol. 2001;46:2467–76.

    Article  CAS  PubMed  Google Scholar 

  20. Schreibmann E, Xing L. Dose-volume based ranking of incident beam direction and its utility in facilitating IMRT beam placement. Int J Radiat Oncol Biol Phys. 2005;63(2):584–93.

    Article  PubMed  Google Scholar 

  21. Vicini FA, et al. Optimizing breast cancer treatment efficacy with intensity-modulated radiotherapy. Int J Radiat Oncol Biol Phys. 2002;54(5):1336–44.

    Article  PubMed  Google Scholar 

  22. Kestin LL, et al. Intensity modulation to improve dose uniformity with tangential breast radiotherapy: initial clinical experience. Int J Radiat Oncol Biol Phys. 2000;48(5):1559–68.

    Article  CAS  PubMed  Google Scholar 

  23. Mayo CS, Urie MM, Fitzgerald TJ. Hybrid IMRT plans—concurrently treating conventional and IMRT beams for improved breast irradiation and reduced planning time. Int J Radiat Oncol Biol Phys. 2005;61(3):922–32.

    Article  PubMed  Google Scholar 

  24. Brahme A. Optimization of stationary and moving beam radiation therapy techniques. Radiother Oncol. 1988;12:129–40.

    Article  CAS  PubMed  Google Scholar 

  25. Bortfeld T, et al. Physical vs. biological objectives for treatment plan optimization. Radiother Oncol. 1996;40(2):185–7.

    Article  CAS  PubMed  Google Scholar 

  26. Brahme A. Optimized radiation therapy based on radiobiological objectives. Semin Radiat Oncol. 1999;9(1):35–47.

    Article  CAS  PubMed  Google Scholar 

  27. Bortfeld T. Optimized planning using physical objectives and constraints. Semin Radiat Oncol. 1999;9(1):20–34.

    Article  CAS  PubMed  Google Scholar 

  28. Shou Z, et al. Quantitation of the a priori dosimetric capabilities of spatial points in inverse planning and its significant implication in defining IMRT solution space. Phys Med Biol. 2005;50(7):1469–82.

    Article  CAS  PubMed  Google Scholar 

  29. Xing L, Chen GTY. Iterative algorithms for inverse treatment planning. Phys Med Biol. 1996;41(2):2107–23.

    Article  CAS  PubMed  Google Scholar 

  30. Webb S. Intensity-modulated radiation therapy. Series in Medical Physics. Bristol and Philadelphia: Institute of Physics Publishing; 2000.

    Google Scholar 

  31. Xing L, et al. Optimization of importance factors in inverse planning. Phys Med Biol. 1999;44(10):2525–36.

    Article  CAS  PubMed  Google Scholar 

  32. Chan LW, et al. Proposed rectal dose constraints for patients undergoing definitive whole pelvic radiotherapy for clinically localized prostate cancer. Int J Radiat Oncol Biol Phys. 2008;72(1):69–77.

    Article  PubMed  Google Scholar 

  33. Odrazka K, et al. Comparison of rectal dose-volume constraints for IMRT prostate treatment planning. Phys Med. 2005;21(4):129–35.

    Article  PubMed  Google Scholar 

  34. Xia P, et al. A study of planning dose constraints for treatment of nasopharyngeal carcinoma using a commercial inverse treatment planning system. Int J Radiat Oncol Biol Phys. 2004;59(3):886–96.

    Article  PubMed  Google Scholar 

  35. Hunt MA, et al. Geometric factors influencing dosimetric sparing of the parotid glands using IMRT. Int J Radiat Oncol Biol Phys. 2006;66(1):296–304.

    Article  PubMed  Google Scholar 

  36. Sykes JR, Williams PC. An experimental investigation of the tongue and groove effect for the Philips multileaf collimator. Phys Med Biol. 1998;43(10):3157–65.

    Article  CAS  PubMed  Google Scholar 

  37. Bortfeld TR, et al. X-ray field compensation with multileaf collimators. Int J Radiat Oncol Biol Phys. 1994;28(3):723–30.

    Article  CAS  PubMed  Google Scholar 

  38. Galvin JM, Chen XG, Smith RM. Combining multileaf fields to modulate fluence distributions. Int J Radiat Oncol Biol Phys. 1993;27(3):697–705.

    Article  CAS  PubMed  Google Scholar 

  39. Spirou SV, Chen-Shou C. Generation of arbitrary intensity profiles by combining the scanning beam with dynamic multileaf collimation. Med Phys. 1996;23(1):1–8.

    Article  CAS  PubMed  Google Scholar 

  40. Xia P, Verhey LJ. Multileaf collimator leaf sequencing algorithm for intensity modulated beams with multiple static segments. Med Phys. 1998;25(8):1424–34.

    Article  CAS  PubMed  Google Scholar 

  41. Chui CS, et al. Delivery of intensity-modulated radiation therapy with a conventional multileaf collimator: comparison of dynamic and segmental methods. Med Phys. 2001;28(12):2441–29.

    Article  CAS  PubMed  Google Scholar 

  42. Chang SX, et al. Compensators: an alternative IMRT delivery technique. J Appl Clin Med Phys. 2004;5(3):15–36.

    Article  PubMed  Google Scholar 

  43. Chang SX, et al. A comparison of different intensity modulation treatment techniques for tangential breast irradiation. Int J Radiat Oncol Biol Phys. 1999;45(5):1305–14.

    Article  CAS  PubMed  Google Scholar 

  44. Yu CX, et al. A method for implementing dynamic photon beam intensity modulation using independent jaws and a multileaf collimator. Phys Med Biol. 1995;40(5):769–87.

    Article  CAS  PubMed  Google Scholar 

  45. Ma Y, et al. Beam’s-eye-view dosimetrics guided inverse planning for aperture modulated arc therapy. Int J Radiat Oncol Biol Phys. 2009;75:1587–95.

    Article  PubMed  Google Scholar 

  46. Galvin JM, et al. Implementing IMRT in clinical practice: a joint document of the American Society for Therapeutic Radiology and Oncology and the American Association of Physicists in Medicine. Int J Radiat Oncol Biol Phys. 2004;58(5):1616–34.

    Article  PubMed  Google Scholar 

  47. Mohan RA, et al. The impact of fluctuations in intensity patterns on the number of monitor units and the quality and accuracy of intensity modulated radiotherapy. Med Phys. 2000;27(6):1226–37.

    Article  CAS  PubMed  Google Scholar 

  48. Hall EJ, Wuu CS. Radiation-induced second cancers: the impact of 3D-CRT and IMRT. Int J Radiat Oncol Biol Phys. 2003;56(1):83–8.

    Article  PubMed  Google Scholar 

  49. Crooks SM, et al. Minimizing delivery time and monitor units in static IMRT by leaf-sequencing. Phys Med Biol. 2002;47(17):3105–16.

    Article  CAS  PubMed  Google Scholar 

  50. Langer M, Thai V, Papiez L. Improved leaf sequencing reduces segments or monitor units needed to deliver IMRT using multileaf collimators. Med Phys. 2001;28(12):2450–8.

    Article  CAS  PubMed  Google Scholar 

  51. Siebers JV, et al. Incorporating multi-leaf collimator leaf sequencing into iterative IMRT optimization. Med Phys. 2002;29(6):952–9.

    Article  PubMed  Google Scholar 

  52. Chui C-S, et al. A simplified intensity modulated radiation therapy technique for the breast. Med Phys. 2002;29(4):522–9.

    Article  PubMed  Google Scholar 

  53. Sun X, Xia P. A new smoothing procedure to reduce delivery segments for static MLC-based IMRT planning. Med Phys. 2004;31(5):1158–65.

    Article  PubMed  Google Scholar 

  54. Bedford JL, Webb S. Constrained segment shapes in direct-aperture optimization for step-and-shoot IMRT. Med Phys. 2006;33(4):944–58.

    Article  PubMed  Google Scholar 

  55. Shepard DM, et al. Direct aperture optimization: a turnkey solution for step-and-shoot IMRT. Med Phys. 2002;29:1007–18.

    Article  CAS  PubMed  Google Scholar 

  56. Van Asselen B, et al. Intensity-modulated radiotherapy of breast cancer using direct aperture optimization. Radiother Oncol. 2006;79(2):162–9.

    Article  PubMed  Google Scholar 

  57. Ludlum E, Xia P. Comparison of IMRT planning with two-step and one-step optimization: a way to simplify IMRT. Phys Med Biol. 2008;53(3):807–21.

    Article  CAS  PubMed  Google Scholar 

  58. Wang X, et al. Dosimetric verification of intensity-modulated fields. Med Phys. 1996;23(3):317–27.

    Article  CAS  PubMed  Google Scholar 

  59. Chen-Shou C, LoSasso T, Spirou S. Dose calculation for photon beams with intensity modulation generated by dynamic jaw or multileaf collimations. Med Phys. 1994;21(8):1237–44.

    Article  Google Scholar 

  60. Jin H, et al. Dose-volume thresholds and smoking status for the risk of treatment-related pneumonitis in inoperable non-small cell lung cancer treated with definitive radiotherapy. Radiother Oncol. 2008;91(3):427–32.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Yom SS, et al. Initial evaluation of treatment-related pneumonitis in advanced-stage non-small-cell lung cancer patients treated with concurrent chemotherapy and intensity-modulated radiotherapy. Int J Radiat Oncol Biol Phys. 2007;68(1):94–102.

    Article  CAS  PubMed  Google Scholar 

  62. Murdoch-Kinch CA, et al. Dose-effect relationships for the submandibular salivary glands and implications for their sparing by intensity modulated radiotherapy. Int J Radiat Oncol Biol Phys. 2008;72(2):373–82.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Eisbruch A, et al. Xerostomia and its predictors following parotid-sparing irradiation of head-and-neck cancer. Int J Radiat Oncol Biol Phys. 2001;50(3):695–704.

    Article  CAS  PubMed  Google Scholar 

  64. Niemierko A. Reporting and analyzing dose distributions: a concept of equivalent uniform dose. Med Phys. 1997;24(1):103–10.

    Article  CAS  PubMed  Google Scholar 

  65. Park CS, et al. Method to account for dose fractionation in analysis of IMRT plans: modified equivalent uniform dose. Int J Radiat Oncol Biol Phys. 2005;62(3):925–32.

    Article  PubMed  Google Scholar 

  66. Lyman JT. Complication probability as assessed from dose volume histograms. Radiat Res. 1985;8:104–13.

    Google Scholar 

  67. Kutcher GJ, et al. Histogram reduction method for calculating complication probabilities for three-dimensional treatment planning evaluations. Int J Radiat Oncol Biol Phys. 1991;21(1):137–46.

    Article  CAS  PubMed  Google Scholar 

  68. Burman C, et al. Fitting of normal tissue tolerance data to an analytic function. Int J Radiat Oncol Biol Phys. 1991;21(1):123–35.

    Article  CAS  PubMed  Google Scholar 

  69. Kutcher GJ, Burman C. Calculation of complication probability factors for non-uniform normal tissue irradiation: the effective volume method. Int J Radiat Oncol Biol Phys. 1989;16(6):1623–30.

    Article  CAS  PubMed  Google Scholar 

  70. Kung J, Chen G. A monitor unit verification calculation in intensity modulated radiotherapy as a dosimetric quality assurance. Med Phys. 2000;27:2226–30.

    Article  CAS  PubMed  Google Scholar 

  71. Beavis A, et al. Slide and shoot: a new method for MLC delivery of IMRT. The use of computers in radiation therapy. Heidelberg: Springer; 2000.

    Google Scholar 

  72. Yang Y, et al. Independent dosimetric calculation with inclusion of head scatter and MLC transmission for IMRT. Med Phys. 2003;30:2937–47.

    Article  CAS  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Radiotherapy, Regional Cancer Centre, JIPMER Department of Radiotherapy, Puducherry, India

    Ashutosh Mukherji

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  1. Ashutosh Mukherji
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Mukherji, A. (2018). Conformal Radiotherapy: Simulation and Contouring. In: Basics of Planning and Management of Patients during Radiation Therapy. Springer, Singapore. https://doi.org/10.1007/978-981-10-6659-7_10

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  • DOI: https://doi.org/10.1007/978-981-10-6659-7_10

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  • Publisher Name: Springer, Singapore

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  • Online ISBN: 978-981-10-6659-7

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