Advertisement

Three-Dimensional Photon Beam Treatment Planning

  • Benedick A. Fraass
  • Daniel L. McShan
Chapter
Part of the Medical Radiology book series (MEDRAD)

Abstract

Treatment planning, in the most general sense, consists of all procedures which are used by the radiation oncologist (and other staff) to help determine the plan with which the patient will be treated. In practice, however, the term “treatment planning” has two different usages:
  1. 1.

    Treatment planning is often considered to be the act of entering the patient shape and beam locations into a computer system (treatment planning system), and then generating a calculated dose distribution which predicts what one expects the actual dose distribution to be if the patient is treated with the chosen plan.

     
  2. 2.

    A more general definition is that treatment planning refers to the quantitative parts of the process (at least) by which the patient’s plan is determined.

     

Keywords

Target Volume Planning System Dose Distribution Dose Calculation 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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. AAPM (1993) AAPM Task Group 35 Report Medical accelerator safety considerations. Med Phys 2014: 1261–1276Google Scholar
  2. AAPM (1992) AAPM Task Group 23 Report Radiation treatment planning dosimetry verificationGoogle Scholar
  3. Ahnesjo A (1989) Collapsed cone convolution of radiant energy for photon dose calculation in heterogeneous media. Med Phys 16: 577–592PubMedCrossRefGoogle Scholar
  4. Austin-Seymour MM, Chen GTY et al. (1986) Dose volume histogram analysis of liver radiation tolerance. Int J Radiat Oncol Biol Phys 12:31–35PubMedCrossRefGoogle Scholar
  5. Bentel G (1992) Radiation therapy planning. Macmillan, New YorkGoogle Scholar
  6. Bezier B (1984) Software system testing and quality assurance. Van Nostrand Reinhold, New YorkGoogle Scholar
  7. Boyer AL (1987) Patient positioning and immobilization devices. In: Kereiakes JG, Elson HR, Born CT (eds) Radiation oncology Physics — 1986. American Institute of Physics, New York (Medical Physics Monograph No. 15)Google Scholar
  8. Brahme A, Agren AK (1987) Optimal dose distribution for eradication of heterogeneous tumors. Acta Oncol 26: 1–9CrossRefGoogle Scholar
  9. Burman C, Kutcher GJ, Hunt M, Brewster L (1989) Acceptance testing criteria for a CT based 3D treatment planning system (abstract). Med Phys 16: 465Google Scholar
  10. Burman C, Kutcher GJ, Emami B, Goitein M (1991) Fitting of normal tissue tolerance data to an analytical function. Int J Radiat Oncol Biol Phys 21: 123–135PubMedCrossRefGoogle Scholar
  11. Chen GTY (1983) Computed tomography in high LET radiotherapy treatment planning. In: Ling CC, Rogers CC, Morton RS, (eds) Computer tomography in radiation therapy. Raven, New York, pp 221–227Google Scholar
  12. Chen GTY, Pelizzari CA (1989) Image correlation techniques in radiation therapy treatment planning. Comp Med Imaging Graphics 13:235–240CrossRefGoogle Scholar
  13. Coffey CW, Hines HC, Wang PC, Smith SL (1984) The early applications and potential usefulness of NMR in radiation therapy treatment planning. Proceedings of the Eighth International Conference on the Use of Computers in Radiation Therapy. IEEE Computer Society, Toronto, Canada, pp 173–180Google Scholar
  14. Cunningham JR (1972) Scatter-air ratios. Phys Med Biol 17: 42–51PubMedCrossRefGoogle Scholar
  15. Cunningham JR (1984) Quality assurance in dosimetry and treatment planning. Int J Radiat Oncol Biol Phys 10 (Suppl 1): 105–109PubMedCrossRefGoogle Scholar
  16. Curran B, Starkschall G (1991) A program for quality assurance of dose planning computers. In: Starkschall G, Horton JL (eds) Quality assurance in radiotherapy physics. Med Phys Publishing, Madison, Wise, pp 207–228Google Scholar
  17. Dritschilo A, Chaffey JT, Bloomer WD, March A (1987) The complication probability factor: a method for selection of radiation treatment plans. Br J Radiol 51: 37Google Scholar
  18. 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: 71–78PubMedCrossRefGoogle Scholar
  19. Emami B, Lyman J, Brown A, et al. (1991) Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 21: 109–122PubMedCrossRefGoogle Scholar
  20. Fraass BA, McShan DL (1987) 3-D treatment planning. I. Overview of a clinical planning system. In: Bruinvis IAD, van der Giessen PH, van Kleffens HJ, Wittkamper FW (eds) The use of computers in radiation therapy. Elsevier Science, North-Holland, pp 273–276Google Scholar
  21. Fraass BA, McShan DL, Diaz RF, et al. (1987a) Integration of MRI into radiation therapy treatment planning. Int J Radiat Oncol Biol Phys 13: 1897–1908PubMedCrossRefGoogle Scholar
  22. Fraass BA, McShan DL, Weeks KJ (1987b) 3-D treatment planning: III. Complete beam’s-eye-view planning capabilities. In: Bruinvis IAD, van der Giessen PH, van Kleffens HJ, Wittkamper FW (eds) The use of computers in radiation therapy. Elsevier Science, North-Holland, pp 193–196Google Scholar
  23. Fraass BA, McShan DL, Weeks KJ (1990) Computerized beam shaping. In: Benedetto AR, Huang HK, Ragan DP (eds) Computers in medical physics. Amer Inst Physics, Woodbury, N.Y. (Medical Physics Monograph 17, pp 333–340)Google Scholar
  24. Fraass BA (1992) Clinical application of 3-D treatment planning. In: Purdy JA (ed) Advances in radiation oncology physics. Dosimetry, Treatment planning and Brachytherapy. American Institute of Physics, Woodburg, NY, pp 967–997Google Scholar
  25. Fraass BA, Matrone GM, McShan DL (1994a) An electronic chart for computercontrolled conformal therapy. In: Hounsell AR, Wilkinson JM, Williams PC (eds) Proceedings of the Xlth International conference on the use of computers in radiation therapy. Medical Physics Publishing, Madison, Wise, pp 218–219Google Scholar
  26. Fraass BA, Martel MK, McShan DL (1994b) Tools for dose calculation verification and QA for conformal therapy treatment techniques. In: Hounsell AR, Wilkinson JM, Williams PC (eds) Proceedings of the Xlth International conference on the use of computers in radiation therapy. Medical Physics Publishing, Madison, Wise, pp 256–257Google Scholar
  27. Glatstein E, Lichter AS, Fraass BA, van de Geijn J (1985) The imaging revolution and radiation oncology: use of CT, ultrasound and NMR for localization, treatment planning and treatment delivery. Int J Radiat Oncol Biol Phys 11:1299–1311PubMedCrossRefGoogle Scholar
  28. Goitein M (1986) Causes and consequences of inhomogeneous dose distributions in radiation therapy. Int J Radiat Oncol Biol Phys 12: 701–704PubMedCrossRefGoogle Scholar
  29. Goitein M, Abrams M (1983) Multi-dimensional treatment planning. I. Delineation of anatomy. Int J Radiat Oncol Biol Phys 9: 777–787PubMedCrossRefGoogle Scholar
  30. Goitein M, Schultheiss TE (1985) Strategies for treating possible tumor extension: some theoretical considerations. Int J Radiat Oncol Biol Phys 11: 1519PubMedCrossRefGoogle Scholar
  31. Goitein M, Wittenberg J, Mendiondo M, et al. (1979) The value of CT scanning in radiation therapy treatment planning: a prospective study. Int J Radiat Oncol Biol Phys 5: 1787–1798PubMedCrossRefGoogle Scholar
  32. Goitein M, Abrams M, Rowell D, Pollari H, Wiles J (1983) Multidimensional treatment planning. II. Beam’s eye-view, back projection, and projection through CT sections. Int J Radiat Oncol Biol Phys 9: 789–797PubMedCrossRefGoogle Scholar
  33. Hall E (1987) Computer image processing and recognition. Academic Press, New York pp 76–78Google Scholar
  34. Henkelman RM, Poon PY, Bronskill MJ (1984) Is magnetic resonance imaging useful for radiation therapy planning. In: Proceedings of the Eighth International Conference on the Use of Computers in Radiation Therapy. IEEE Computer Society, Toronto, Canada, pp 181–185Google Scholar
  35. Hunt M, Kutcher G, Burman C, Fass D, Harrison L, Leibel S, Fuks Z (1989) Effect of positional uncertainties on the treatment of nasopharynx cancer. Med Phys 16: 456 (Abstract)Google Scholar
  36. ICRU (1987) ICRU Report 29. Dose specification for reporting external beam therapy with photons and electrons. International Commission on Radiation Units and Measurements, Washington, D.C.Google Scholar
  37. ICRU (1993) ICRU Report 50. Prescribing, recording and reporting photon beam therapy. International commission on radiation units and Measurements. Washington, DCGoogle Scholar
  38. IEEE Computer Society Press (1990) Proceedings of the First Conference on Visualization in Biomedical Computing, May, 1990, Atlanta, Ga.Google Scholar
  39. Jacky J, White CP (1990) Testing a 3-D radiation therapy planning program. Int J Radiat Oncol Biol Phys 17: 253–261CrossRefGoogle Scholar
  40. Jakobsen A, Iversen P, Gadeberg C, Hansen JL, Hjelm-Hansen M (1987) A new system for patient fixation in radiotherapy. Radiotheronco l8: 145–151Google Scholar
  41. Kessler ML (1987) Computer techniques for correlating NMR x-ray CT imaging for radiotherapy treatment planning. In: Bruinvis IAD, van der Giessen PH, van Kleffens HJ, Wittkamper FW (eds) The use of computers in radiation therapy. Elsevier Science, North-Holland, pp 441–444Google Scholar
  42. Kessler ML, Pitluck S, Petti P, Castro JR (1991) Integration of multimodality imaging data for radiotherapy treatment planning. Int J Radiat Oncol Biol Phys 21: 1653–1667PubMedCrossRefGoogle Scholar
  43. Kessler ML, McShan DL, Fraass BA (1992) Displays for 3-D treatment planning. Semin Radiat Oncol 2(4): 226–234PubMedCrossRefGoogle Scholar
  44. Kessler ML, McShan DL, Fraass BA (1994a) A graphical simulator for design and verification of computercontrolled treatment in delivery. In: Hounsell AR, Wilkinson JM, Williams PC (eds) Proceedings of the Xlth International conference on the use of computers in radiation therapy. Medical Physics Publishing, Madison, Wise, pp 80–81Google Scholar
  45. Kessler ML, Ten Haken RK, Fraass BA, McShan DL (1994b) Expanding the use and effectiveness of dose-volume histograms for 3-D treatment planning I: integration of 3-D dose-display. Int J Rad Oncol Bio Phys (in press)Google Scholar
  46. Koral KF, Ten Haken RK, McShan DL (1990) Superimposition of SPECT and CT images and transfer of Rol for quantification. 37th Annual Meeting of the Society of Nuclear Medicine, June 19–22, 1990, Washington, D.C.Google Scholar
  47. Kutcher GJ, Burman C (1989) Calculation of complication probability factors for non-uniform normal tissue irradiation: the effective volume method. Int J Radiat Oncol Biol Phys 16: 1623–1630PubMedCrossRefGoogle Scholar
  48. Kutcher GJ, Burman C, Brewster L, Goitein M, Mohan R (1991) Histogram reduction method for calculating complication probabilities for 3D treatment planning evaluations. Int J Radiat Oncol Biol Phys 21: 137–146PubMedCrossRefGoogle Scholar
  49. Lawrence TS, Tesser RJ, Ten Haken RK (1990) An application of dose volume histograms to treatment of intrahepatic malignancies with radiation therapy. Int J Radiat Oncol Biol Phys 19: 1041–1047PubMedCrossRefGoogle Scholar
  50. Lawrence TS, Ten Haken RK, Kessler ML, et al. (1992) The use of 3D dosevolume analysis to predict radiation hepatitis. Int J Radiat Oncol Biol Phys 23: 781–788PubMedCrossRefGoogle Scholar
  51. Lepinoy D, Aletti P, Boisserie G, et al. (SFPH) (1984) Quality assurance program for computers in radiotherapy: progress report. IEEE, pp 322–327Google Scholar
  52. Lichter AS, Fraass BA, van de Geijn J, Fredrickson HA, Glatstein E (1983) An overview of clinical requirements and clinical utility of computer tomography (CT)-based radiotherapy treatment planning. In: Ling CC, Rogers CC, Morton RS (eds) Computer tomography in radiation therapy. Raven, New York, pp 1–21Google Scholar
  53. Lifshitz LM, Pizer SM (1990) A multiresolution hierarchial approach to image segmentation based on intensity extrema. IEEE Transactions on Pattern Analysis and Machine Intelligence 12 (6): 29–540CrossRefGoogle Scholar
  54. Ling CC, Rogers CC, Morton RS (eds) (1983) Computer tomography in radiation therapy. Raven, New YorkGoogle Scholar
  55. Lyman JT (1985) Complication probability as assessed from dose volume histograms. Radiat Res 104: S-13–S-19CrossRefGoogle Scholar
  56. Lyman JT (1991) Normal tissue complication probabilities: variable dose per fraction. Int J Radiat Oncol Biol Phys 22:247–250CrossRefGoogle Scholar
  57. 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
  58. Lyman JT, Wolbarst AB (1989) Optimization of radiation therapy. IV. A dose volume histogram reduction method. Int J Radiat Oncol Biol Phys 17: 433–436PubMedCrossRefGoogle Scholar
  59. Mackie TR, Bielajew AF, Rogers DWO, Battista JJ (1988) Generation of photon energy deposition kernels using the EGS Monte Carlo code. Phys Med Biol 33: 1–20PubMedCrossRefGoogle Scholar
  60. Mageras GS, Podmaniczky KC, Mohan R (1992) A model for computercontrolled delivery of 3-D conformal treatments. Med Phys 19: 945–953PubMedCrossRefGoogle Scholar
  61. McCullough EC (1987) Potentials of computed tomography in radiation therapy treatment planning. Radiology 129: 765–768Google Scholar
  62. McCullough EC, Krueger AM (1980) Performance evaluation of computerized treatment planning systems for radiotherapy: external photon beams. Int J Radiat Oncol Biol Phys 6: 1599–1605PubMedCrossRefGoogle Scholar
  63. McShan DL (1990) Conformal treatment planning. Med Phys Bull Assoc Med Phys India 15: 190–199Google Scholar
  64. McShan DL, Fraass BA (1987) Integration of multi-modality imaging for use in radiation therapy treatment planning. In: Lemke HU, Rhodes ML, Jaffee CC, Felix R (eds) Computer assisted radiology. Springer, Berlin Heidelberg New York, pp 300–304CrossRefGoogle Scholar
  65. McShan DL, Glicksman AS (1984) Graphical simulation and design of beam portal blocking. In: Proceedings of the Eighth International Conference on the Use of Computers in Radiation Therapy. IEEE Computer Society, Toronto, Canada, pp 114–118Google Scholar
  66. McShan DL, Silverman A, Lanza D, Reinstein LE, Glicksman AS (1979) A computerized three-dimensional treatment planning system utilizing interactive color graphics. Br J Radiol 52: 478–181PubMedCrossRefGoogle Scholar
  67. McShan DL, Fraass BA, Lichter AS (1990) Full integration of the beam’s eye view concept into computerized treatment planning. Int J Radiat Oncol Biol Phys 18: 1485–1494PubMedCrossRefGoogle Scholar
  68. McShan DL, Matrone G, Fraass BA, Lichter AS (1993) A large screen digitizer system for radiation therapy treatment planning. Int J Radiat Oncol Biol Phys 26: 681–684PubMedCrossRefGoogle Scholar
  69. McShan DL, Fraass BA (1994) UM-CCRS/SP: sequence processor for computer controlled radiotherapy treatment delivery. In: Hounsell AR, Wilkinson JM, Williams PC (eds) Proceedings of the Xlth International conference on the use of computers in radiation therapy. Medical Physics Publishing, Madison, Wise, pp 210–211Google Scholar
  70. Meyers GJ (1979) The art of software testing. John Wiley, New YorkGoogle Scholar
  71. Mohan R, Barest G, Brewster LJ, Chui CS, Kutcher GJ, Laughlin JS, Fuks Z (1988) A comprehensive three-dimensional radiation treatment planning system. Int J Radiat Oncol Biol Phys 15: 481–495PubMedCrossRefGoogle Scholar
  72. Munzenrider JE, Brown AP, Chu JC, et al. (1991) Numerical scoring of treatment plans. Int J Radiat Oncol Biol Phys 21: 147–163PubMedCrossRefGoogle Scholar
  73. Mustafa AA, Jackson DF (1983) Phys Med Biol 28(2): 169–176PubMedCrossRefGoogle Scholar
  74. NCI (1987) Evaluation of treatment planning for particle beam radiotherapy. Radiotherapy Development Branch, Radiation Research Program, Division of Cancer Treatment, National Cancer Institute, Bethesda, M.DGoogle Scholar
  75. NCI Photon Treatment Planning Working Group (1991) Three dimensional dose calculations for radiation therapy treatment planning. Int J Radiat Oncol Biol Phys 21: 25–36Google Scholar
  76. Niemierko A, Goitein M (1990) Random sampling for evaluating treatment plans. Med Phys 17: 753–762PubMedCrossRefGoogle Scholar
  77. Niemierko A, Goitein M (1991) Calculation of normal tissue complication probability and dose volume histogram reduction schemes for tissues with critical element architecture. Radiother Oncol 20: 166–176PubMedCrossRefGoogle Scholar
  78. Pelizzari CA, Chen GTY (1987) Registration of multiple diagnostic imaging scans using surface fitting. In: Bruinvis IAD, van der Giessen PH, van Kleffens H J, Wittkamper FW (eds) The use of computers in radiation therapy. Elsevier Science, North-Holland, pp 437–440Google Scholar
  79. Rabinowitz I, Broomberg J, Goitein M, McCarthy K, Leong J (1985) Accuracy of radiation field alignment in clinical practice. Int J Radiat Oncol Biol Phys 11: 1857–1867PubMedCrossRefGoogle Scholar
  80. Rice RK, Mijnheer BJ, Chin LM (1988) Benchmark Measurements for lung dose correction for x-ray beams. Int J Radiat Oncol Brol Phys 15: 399–409CrossRefGoogle Scholar
  81. Rosenow UF, Dannhausen H-W, Lubbert K, et al. (1987) Quality assurance in treatment planning. Report from the German Task Group. In: Bruinvis IAD, van der Giessen PH, van Kleffens HJ, Wittkamper FW, (eds) The use of computers in radiation therapy. Elsevier Science, North-Holland, pp 45–58Google Scholar
  82. Sauer O, Nowak G, Richter J (1987) Accuracy of dose calculations of the Philips treatment planning system OSS for blocked fields. In: Bruinvis IAD, van der Giessen PH, van Kleffens HJ, Wittkamper FW, (eds) The use of computers in radiation therapy. Elsevier Science, North-Holland, pp 57–60Google Scholar
  83. Schad LR, Boesecke R, Schlegel W, Hartmann GH, Sturm V, Strauss LG, Lorenz WJ (1987) 3-D image correlation of CT, MR and PET studies in radiotherapy treatment planning of brain tumors. J Comput Assis Tomogr 11: 948–954CrossRefGoogle Scholar
  84. Schwade JG, Houdek PV, Landy HJ (1990) Small-field stereotactic externalbeam radiation therapy of intracranial lesions: fractionated treatment with a fixedhalo immobilization device. Radiology 176: 563–565PubMedGoogle Scholar
  85. Sewchand W, Aygun C, Nicholson G, Salazar OM (1986) Patient immobilization during CT for treatment planning of head and neck cancer. Radiology 158: 251–252PubMedGoogle Scholar
  86. Sherouse GW, Mosher CE, Novins K, Rosenman J, Chaney EL (1987) Virtual simulation: concept and implementation. In: Bruinvis IAD, van der Giessen PH, van Kleffens HJ, Wittkamper FW (eds) The use of computers in radiation therapy. Elsevier Science, North-Holland, pp 433–436Google Scholar
  87. Sherouse GW, Bourland JD, Reynolds K, McMurry HL, Mitchell TP, Chaney EL (1990) Virtual simulation in the clinical setting: some practical considerations. Int J Radiat Oncol Biol Phys 19: 1059–1065PubMedCrossRefGoogle Scholar
  88. Sontag MR, Galvin JM, Axel L, Bloch P (1984) The use of NMR images for radiation therapy treatment planning. Proceedings of the Eighth International Conference on the Use of Computers in Radiation Therapy. IEEE Computer Society, Toronto, Canada, pp 168–172Google Scholar
  89. Sterling TD, Glicksman AS, Knowlton K, Weinkam J (1971) Three-dimensional treatment plan display on computer-produced films. In: Glicksman AS, Cohen M, Cunningham JR (eds) Computers in radiotherapy. (Proceedings of the 3rd International Conference on Computer in Radiotherapy, Glasgow, September 1970.) Br J Radiol (Special Report) 5Google Scholar
  90. Stern RL, Fraass BA, Gerhardsson A, McShan DL, Lam KL (1992) Generation and use of measurement-based 3-D dose distributions for 3-D dose calculation verification. Med Phys 19: 165–174PubMedCrossRefGoogle Scholar
  91. Ten Haken RK, Forman JD, Heimburger DK, et al. (1991a) Treatment planning issues related to prostate movement in response to differential filling of the rectum and bladder. Int J Radiat Oncol Biol Phys 20: 1317–1324PubMedCrossRefGoogle Scholar
  92. Ten Haken RK, Kessler ML, Stern RL, Ellis JH, Niklason LT (1991b) Quality assurance of CT and MRI for radiation therapy treatment planning. In: Starkschall G, Horton JL (eds) Quality assurance in radiotherapy physics. Med Phys Publishing, Madison, Wise, pp 73–103Google Scholar
  93. Ten Haken RK, Thornton AF, Sandler HM, et al. (1992) A quantitative assessment of the addition of MRI to CT-based, 3-D treatment planning of brain tumors. Radiother Oncol 25: 121–133PubMedCrossRefGoogle Scholar
  94. Thames HD, Schultheiss TE, Hendry JH, Tucker SL, Dubray BM, Brock W A (1991) Can modest escalations of dose be detected as increased tumor control? Int J Radiat Oncol Bio Phys 22: 241–246CrossRefGoogle Scholar
  95. Thomas SJ, Wilkinson ID, Dixon AK, Dendy PP(1992) Magnetic resonance imaging of Fricke-doped agarose gels for the visualization of radiotherapy dose distributions in a lung phantom. Br J Radiol 65: 167–169PubMedCrossRefGoogle Scholar
  96. Thornton AF Jr, Ten Haken RK, Weeks KJ, Gerhardsson A, Correll M, Lash KA (1991a) A head immobilization system for radiation simulation, CT, MRI, and PET imaging. Med Dosim 16: 51–56PubMedGoogle Scholar
  97. Thornton AF Jr, Ten Haken RK, Gerhardsson A, Correll M (1991b) Three-dimensional motion analysis of an improved head immobilization system for simulation, CT, MRI, and PET imaging.” Radiother Oncol 20: 224–228PubMedCrossRefGoogle Scholar
  98. Thornton AS Jr, Sandler HM, Ten Haken RK, et al. (1992) The clinical utility of MRI in 3-D treatment planning of brain neoplasms. Int J Radiat Oncol Biol Phys 24: 767–775PubMedCrossRefGoogle Scholar
  99. Tsien KC (1955) The application of automatic computing machines to radiation treatment planning. Br J Radiol 28: 432–439PubMedCrossRefGoogle Scholar
  100. Urie MM, Goitein M, Doppke K, et al. (1991) The role of uncertainty analysis in treatment planning. Int J Radiat Oncol Biol Phys 21:91–107PubMedCrossRefGoogle Scholar
  101. van de Geijn J (1965) The computation of two and three dimensional dose distributions in cobalt-60 teletherapy. Br J Radiol 38: 369–377CrossRefGoogle Scholar
  102. van de Geijn J, Harrington FS, Lichter AS, Glatstein E (1983) Simplified bite-block immobilization of the head. Radiology 149: 851PubMedGoogle Scholar
  103. van de Geijn J, Fraass BA (1984) The net fractional depth dose: a basis for a unified analytical description of FDD, TAR, TMR, and TPR. Med Phys 11: 784–793PubMedCrossRefGoogle Scholar
  104. Van Dyk J, Barnett RB, Cygler JE, Shragge PC (1993) Commissioning and quality assurance of treatment planning computers. Int J Rad Oncol Biol Phys 26: 261–273CrossRefGoogle Scholar
  105. Verhey LJ, Goitein M, McNulty P, Munzenrider JE, Suit HD (1982) Precise positioning of patients for radiation therapy. Int J Radiat Oncol Biol Phys 8: 289–294PubMedCrossRefGoogle Scholar
  106. Weeks KJ, Fraass BA, McShan DL, Hardybala SS, Hargreaves EA, Lichter AS (1989) Comparison of automated and manual shielding block fabrication. Int J Radiat Oncol Biol Phys 16: 501–504PubMedCrossRefGoogle Scholar
  107. Westmann CF, Mijnheer BJ, van Kleffens HJ (1984) Determination of the accuracy of different computer planning systems for treatment with external photon beams. Radiother Oncol 1: 339–347CrossRefGoogle Scholar
  108. Wittkamper FW, Mijnheer BJ, van Kleffens HJ (1988) Dose intercomparison at the radiotherapy centers in The Nether-lands. 2. Accuracy of locally applied computer planning systems for external photon beams. Radiother Oncol 11: 405–414PubMedCrossRefGoogle Scholar
  109. Wolbarst AB, Chin LM, Svensson GK (1982) Optimization of radiation therapy: integral-response of a model biological system. Int J Radiat Oncol Biol Phys 8: 1761–1769PubMedCrossRefGoogle Scholar
  110. Yanke BR, Ten Haken RK, Aisen A, Fraass BA, Thornton AF (1991) Design of MRI scan protocols for use in 3-D, CT-based treatment planning. Med Dosim 16: 205–211PubMedGoogle Scholar
  111. Zagars GK, Schultheiss TE, Peters LJ (1987) Inter-tumor heterogeneity and radiation dose-control curves. Radiol Oncol 8: 353–361CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Benedick A. Fraass
    • 1
  • Daniel L. McShan
    • 1
  1. 1.Radiation OncologyUniversity of Michigan Medical CenterAnn ArborUSA

Personalised recommendations