Browse > Article
http://dx.doi.org/10.14316/pmp.2020.31.3.54

History of the Photon Beam Dose Calculation Algorithm in Radiation Treatment Planning System  

Kim, Dong Wook (Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine)
Park, Kwangwoo (Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine)
Kim, Hojin (Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine)
Kim, Jinsung (Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine)
Publication Information
Progress in Medical Physics / v.31, no.3, 2020 , pp. 54-62 More about this Journal
Abstract
Dose calculation algorithms play an important role in radiation therapy and are even the basis for optimizing treatment plans, an important feature in the development of complex treatment technologies such as intensity-modulated radiation therapy. We reviewed the past and current status of dose calculation algorithms used in the treatment planning system for radiation therapy. The radiation-calculating dose calculation algorithm can be broadly classified into three main groups based on the mechanisms used: (1) factor-based, (2) model-based, and (3) principle-based. Factor-based algorithms are a type of empirical dose calculation that interpolates or extrapolates the dose in some basic measurements. Model-based algorithms, represented by the pencil beam convolution, analytical anisotropic, and collapse cone convolution algorithms, use a simplified physical process by using a convolution equation that convolutes the primary photon energy fluence with a kernel. Model-based algorithms allowing side scattering when beams are transmitted to the heterogeneous media provide more precise dose calculation results than correction-based algorithms. Principle-based algorithms, represented by Monte Carlo dose calculations, simulate all real physical processes involving beam particles during transportation; therefore, dose calculations are accurate but time consuming. For approximately 70 years, through the development of dose calculation algorithms and computing technology, the accuracy of dose calculation seems close to our clinical needs. Next-generation dose calculation algorithms are expected to include biologically equivalent doses or biologically effective doses, and doctors expect to be able to use them to improve the quality of treatment in the near future.
Keywords
Dose; Algorithm; Radiation; Oncology; Planning;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Johns HE, Bruce WR, Reid WB. The dependence of depth dose on focal skin distance. Br J Radiol. 1958;31:254-260.   DOI
2 Ahnesjo A, Andreo P, Brahme A. Calculation and application of point spread functions for treatment planning with high energy photon beams. Acta Oncol. 1987;26:49-56.   DOI
3 Tang WL, Khan FM, Gerbi BJ. Validity of lung correction algorithms. Med Phys. 1986;13:683-686.   DOI
4 Han T, Mikell JK, Salehpour M, Mourtada F. Dosimetric comparison of Acuros XB deterministic radiation transport method with Monte Carlo and model-based convolution methods in heterogeneous media. Med Phys. 2011;38: 2651-2664.   DOI
5 Aarup LR, Nahum AE, Zacharatou C, Juhler-Nottrup T, Knoos T, Nystrom H, et al. The effect of different lung densities on the accuracy of various radiotherapy dose calculation methods: implications for tumour coverage. Radiother Oncol. 2009;91:405-414.   DOI
6 Webb S, Parker RP. A Monte Carlo study of the interaction of external beam X-radiation with inhomogeneous media. Phys Med Biol. 1978;23:1043-1059.   DOI
7 Sterpin E, Tomsej M, De Smedt B, Reynaert N, Vynckier S. Monte carlo evaluation of the AAA treatment planning algorithm in a heterogeneous multilayer phantom and IMRT clinical treatments for an Elekta SL25 linear accelerator. Med Phys. 2007;34:1665-1677.   DOI
8 DeMarco JJ, Solberg TD, Smathers JB. A CT-based Monte Carlo simulation tool for dosimetry planning and analysis. Med Phys. 1998;25:1-11.   DOI
9 O'Connor JE. A transit dose technique for the determination of doses in inhomogeneous bodies. Br J Radiol. 1956; 29:663-667.   DOI
10 Gray A, Oliver LD, Johnston PN. The accuracy of the pencil beam convolution and anisotropic analytical algorithms in predicting the dose effects due to attenuation from immobilization devices and large air gaps. Med Phys. 2009; 36:3181-3191.   DOI
11 Young MEJ. Radiological physics. London: Lewis; 1967.
12 Batho HF. Lung corrections in cobalt 60 beam therapy. J Can Assoc Radiol. 1964;15:79-83.
13 Van Dyk J, Keane TJ, Kan S, Rider WD, Fryer CJ. Radiation pneumonitis following large single dose irradiation: a reevaluation based on absolute dose to lung. Int J Radiat Oncol Biol Phys. 1981;7:461-467.   DOI
14 Chopra KL, Leo P, Kabat C, Rai DV, Avadham JS, Kehwar TS, et al. Evaluation of dose calculation accuracy of treatment planning systems in the presence of tissue heterogeneities. Ther Radiol Oncol. 2018;2:28.   DOI
15 Huang JY, Dunkerley D, Smilowitz JB. Evaluation of a commercial Monte Carlo dose calculation algorithm for electron treatment planning. J Appl Clin Med Phys. 2019;20: 184-193.
16 Kroon PS, Hol S, Essers M. Dosimetric accuracy and clinical quality of Acuros XB and AAA dose calculation algorithm for stereotactic and conventional lung volumetric modulated arc therapy plans. Radiat Oncol. 2013;8:149.   DOI
17 Fogliata A, Nicolini G, Clivio A, Vanetti E, Cozzi L. Critical appraisal of Acuros XB and Anisotropic Analytic Algorithm dose calculation in advanced non-small-cell lung cancer treatments. Int J Radiat Oncol Biol Phys. 2012;83: 1587-1595.   DOI
18 Kappas K, Rosenwald JC. A 3-D beam subtraction method for inhomogeneity correction in high energy X-ray radiotherapy. Radiother Oncol. 1986;5:223-233.   DOI
19 Shimm DS, Doppke KP, Leong JC, Gregory E, Dosoretz DE. Variation in the lung inhomogeneity correction factor with beam energy. Clinical implications. Acta Radiol Oncol. 1985;24:407-410.   DOI
20 Sontag MR, Cunningham JR. The equivalent tissue-air ratio method for making absorbed dose calculations in a heterogeneous medium. Radiology. 1978;129:787-794.   DOI
21 Mohan R, Chui C, Lidofsky L. Differential pencil beam dose computation model for photons. Med Phys. 1986;13: 64-73.   DOI
22 Ahnesjo A, Saxner M, Trepp A. A pencil beam model for photon dose calculation. Med Phys. 1992;19:263-273.   DOI
23 Khan FM, Levitt SH, Moore VC, Jones TK Jr. Computer and approximation methods of calculating depth dose in irregularly shaped fields. Radiology. 1973;106:433-436.   DOI
24 Ma CM, Li JS, Pawlicki T, Jiang SB, Deng J, Lee MC, et al. A Monte Carlo dose calculation tool for radiotherapy treatment planning. Phys Med Biol. 2002;47:1671-1689.   DOI
25 Rogers DW, Faddegon BA, Ding GX, Ma CM, We J, Mackie TR. BEAM: a Monte Carlo code to simulate radiotherapy treatment units. Med Phys. 1995;22:503-524.   DOI
26 Jeraj R, Keall P. The effect of statistical uncertainty on inverse treatment planning based on Monte Carlo dose calculation. Phys Med Biol. 2000;45:3601-3613.   DOI
27 Vassiliev ON, Wareing TA, McGhee J, Failla G, Salehpour MR, Mourtada F. Validation of a new grid-based Boltzmann equation solver for dose calculation in radiotherapy with photon beams. Phys Med Biol. 2010;55:581-598.   DOI
28 Holt JG, Laughlin JS, Moroney JP. The extension of the concept of tissue-air ratios (TAR) to high-energy x-ray beams. Radiology. 1970;96:437-446.   DOI
29 Lovelock DM, Chui CS, Mohan R. A Monte Carlo model of photon beams used in radiation therapy. Med Phys. 1995; 22:1387-1394.   DOI
30 Weinkam J, Sterling T. A versatile system for three-dimensional radiation dose computation and display, RTP. Comput Programs Biomed. 1972;2:178-191.   DOI
31 Young ME, Gaylord JD. Experimental tests of corrections for tissue inhomogeneities in radiotherapy. Br J Radiol. 1970;43:349-355.   DOI
32 Van Dyk J, Battista JJ, Rider WD. Half body radiotherapy: the use of computed tomography to determine the dose to lung. Int J Radiat Oncol Biol Phys. 1980;6:463-470.   DOI
33 Yuen K, Kornelsen RO. Practical application of the differential Batho method for inhomogeneity correction on kerma in a photon beam. Med Phys. 1988;15:74-77.   DOI
34 Iwasaki A. A method of taking into account the inhomogeneity backscatter contribution to the Batho correction factor. Phys Med Biol. 1986;31:923-926.   DOI
35 Sontag MR, Cunningham JR. Clinical application of a CT based treatment planning system. Comput Tomogr. 1978; 2:117-130.   DOI
36 Kappas K, Rosenwald JC. Theoretical and experimental analysis of scatter from inhomogeneous slabs in a 60Co beam: the differential tissue-air ratio method (DTAR). Phys Med Biol. 1986;31:1211-1228.   DOI
37 Cunningham JR. Scatter-air ratios. Phys Med Biol. 1972;17: 42-51.   DOI
38 Panettieri V, Barsoum P, Westermark M, Brualla L, Lax I. AAA and PBC calculation accuracy in the surface buildup region in tangential beam treatments. Phantom and breast case study with the Monte Carlo code PENELOPE. Radiother Oncol. 2009;93:94-101.   DOI
39 Adam DP, Liu T, Caracappa PF, Bednarz BP, Xu XG. New capabilities of the Monte Carlo dose engine ARCHER-RT: clinical validation of the Varian TrueBeam machine for VMAT external beam radiotherapy. Med Phys. 2020;47: 2537-2549.   DOI
40 Mackie TR, Scrimger JW, Battista JJ. A convolution method of calculating dose for 15-MV x rays. Med Phys. 1985;12: 188-196.   DOI
41 Clarkson JR. A note on depth doses in fields of irregular shape. Br Inst Radiol. 1941;14:4.
42 Johns HE. The physics of radiation therapy. Almancil: Springfield; 1953.
43 Ahnesjo A. Collapsed cone convolution of radiant energy for photon dose calculation in heterogeneous media. Med Phys. 1989;16:577-592.   DOI
44 Ma CMC, Chetty IJ, Deng J, Faddegon B, Jiang SB, Li J, et al. Beam modeling and beam model commissioning for Monte Carlo dose calculation-based radiation therapy treatment planning: report of AAPM Task Group 157. Med Phys. 2020;47:e1-e18.
45 Kappas K. Les heterogeneites dans les faisceaux de photons de haute energie employes en radiotherapie: recherches experimentales et theoriques [Inhomogeneities in high energy photon beams used in radiotherapy. Experimental and theoretical studies]. Toulouse: Univ Paul Sabatier de Toulouse, 1986. Portuguese.
46 Hogstrom KR, Mills MD, Almond PR. Electron beam dose calculations. Phys Med Biol. 1981;26:445-459.   DOI
47 Schoknecht G, Khatib M. [Model calculations of the Energy distribution of scattered radiation in a patient (author's transl)]. Rontgenblatter. 1982;35:303-306. German.
48 Scholz C, Schulze C, Oelfke U, Bortfeld T. Development and clinical application of a fast superposition algorithm in radiation therapy. Radiother Oncol. 2003;69:79-90.   DOI
49 Patents in the Field of Medicine. Can J Comp Med Vet Sci. 1941;5:246.
50 Mackie TR, Bielajew AF, Rogers DW, Battista JJ. Generation of photon energy deposition kernels using the EGS Monte Carlo code. Phys Med Biol. 1988;33:1-20.   DOI
51 Bortfeld T, Schlegel W, Rhein B. Decomposition of pencil beam kernels for fast dose calculations in three-dimensional treatment planning. Med Phys. 1993;20(2 Pt 1):311-318.   DOI
52 Bourland JD, Chaney EL. A finite-size pencil beam model for photon dose calculations in three dimensions. Med Phys. 1992;19:1401-1412.   DOI
53 Sievinen J, Ulmer W, Kaissl W. AAA Photon dose calculation model in eclipseTM. Palo Alto: Varian Medical System; 2005.
54 Fogliata A, Nicolini G, Vanetti E, Clivio A, Cozzi L. Dosimetric validation of the anisotropic analytical algorithm for photon dose calculation: fundamental characterization in water. Phys Med Biol. 2006;51:1421-1438.   DOI