期刊论文详细信息
Radiation Oncology
Clinical implications in the use of the PBC algorithm versus the AAA by comparison of different NTCP models/parameters
Luisa Begnozzi3  Roberto Capparella3  Barbara Nardiello1  Antonella Bufacchi2 
[1] UPMC San Pietro FBF Advanced Radiotherapy Center, Rome, Italy;Medical Physics, PioXI Clinic and U.O.C. Medical Physics, S. Giovanni Calibita Fatebenefratelli Hospital, Rome, Italy;U.O.C. Medical Physics, S. Giovanni Calibita Fatebenefratelli Hospital, Rome, Italy
关键词: Anisotropic analytical algorithm;    Pencil beam convolution algorithm;    Normal tissue complication probability;    Dose volume histogram;   
Others  :  1153570
DOI  :  10.1186/1748-717X-8-164
 received in 2012-10-13, accepted in 2013-06-13,  发布年份 2013
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【 摘 要 】

Purpose

Retrospective analysis of 3D clinical treatment plans to investigate qualitative, possible, clinical consequences of the use of PBC versus AAA.

Methods

The 3D dose distributions of 80 treatment plans at four different tumour sites, produced using PBC algorithm, were recalculated using AAA and the same number of monitor units provided by PBC and clinically delivered to each patient; the consequences of the difference on the dose-effect relations for normal tissue injury were studied by comparing different NTCP model/parameters extracted from a review of published studies. In this study the AAA dose calculation is considered as benchmark data. The paired Student t-test was used for statistical comparison of all results obtained from the use of the two algorithms.

Results

In the prostate plans, the AAA predicted lower NTCP value (NTCPAAA) for the risk of late rectal bleeding for each of the seven combinations of NTCP parameters, the maximum mean decrease was 2.2%. In the head-and-neck treatments, each combination of parameters used for the risk of xerostemia from irradiation of the parotid glands involved lower NTCPAAA, that varied from 12.8% (sd=3.0%) to 57.5% (sd=4.0%), while when the PBC algorithm was used the NTCPPBC’s ranging was from 15.2% (sd=2.7%) to 63.8% (sd=3.8%), according the combination of parameters used; the differences were statistically significant. Also NTCPAAA regarding the risk of radiation pneumonitis in the lung treatments was found to be lower than NTCPPBC for each of the eight sets of NTCP parameters; the maximum mean decrease was 4.5%. A mean increase of 4.3% was found when the NTCPAAA was calculated by the parameters evaluated from dose distribution calculated by a convolution-superposition (CS) algorithm. A markedly different pattern was observed for the risk relating to the development of pneumonitis following breast treatments: the AAA predicted higher NTCP value. The mean NTCPAAA varied from 0.2% (sd = 0.1%) to 2.1% (sd = 0.3%), while the mean NTCPPBC varied from 0.1% (sd = 0.0%) to 1.8% (sd = 0.2%) depending on the chosen parameters set.

Conclusions

When the original PBC treatment plans were recalculated using AAA with the same number of monitor units provided by PBC, the NTCPAAA was lower than the NTCPPBC, except for the breast treatments. The NTCP is strongly affected by the wide-ranging values of radiobiological parameters.

【 授权许可】

   
2013 Bufacchi et al.; licensee BioMed Central Ltd.

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【 参考文献 】
  • [1]Arnfield MR, Siantar CH, Siembers J, Garmon P, Cox L, Mohan R: The impact of electron transport on the accuracy of computed dose. Med Phys 2000, 27:1266-74.
  • [2]Carrasco P, Jornet N, Duch MA, Weber L, Ginjaume M, Eudaldo T, Jurado D, Ruiz A, Ribas M: Comparison of dose calculation algorithms in phantoms with lung equivalent heterogeneities under conditions of lateral electronic disequilibrium. Med Phys 2004, 31:2899-911.
  • [3]Shaine BH, Al-Ghazi MSAL, El-Khatib E: Experimental evaluation of interface doses in the presence of air cavities compared with treatment planning algorithms. Med Phys 1999, 26:350-5.
  • [4]Engelsman M, Damen EMF, Koken PW, Van’t Veld AA, Van Ingen KM, Mijnheer BJ: Impact of simple tissue inhomogneity correction algorithms on conformal radiotherapy of lung tumours. Radiother Oncol 2001, 60:299-09.
  • [5]AAPM: Tissue inhomogeneity corrections for megavoltage photon beams. New York: Report 85; 2004.
  • [6]Mackie TR, Scrimger JW, Battista JJ: A convolution method of calculating dose for 15 MV x rays. Med Phys 1985, 12:188-96.
  • [7]Boyer AL, Mok EC: A photon dose distribution model employing convolution calculations. Med Phys 1985, 12:169-77.
  • [8]Boyer AL, Mok EC: Calculation of photon dose distribution in an inhomogeneous medium using convolution. Med Phys 1986, 13:503-09.
  • [9]Mohan R, Chui C, Lidofsky L: Differential pencil beam dose computation model for photons. Med Phys 1986, 13:64-73.
  • [10]Woo MK, Cunningham JR: The validity of the density scaling method in primary electron transport for photon and electron beams. Med Phys 1990, 17:187-94.
  • [11]Aspradakis MM, Morrison RH, Richmond ND, Steele A: Experimental verification of convolution/superposition photon dose calculation for radiotherapy treatment planning. Phys Med Biol 2003, 48:2873-93.
  • [12]Ulmer W, Pyyry J, Kaissl W: 3D photon superposition/convolution algorithm and its foundation on results of Monte Carlo calculations. Phys Med Biol 2005, 50:1767-90.
  • [13]Bragg CM, Wingate K, Conway J: Clinical implications of the anisotropic analytical algorithm for IMRT treatment planning and verification. Radiother Oncol 2008, 86:276-84.
  • [14]Van Esch A, Tillikainen L, Pyykkonen J, Tenhunen M, Helminen H, Siljamäki S, Alakuijala J, Paiusco M, Lori M, Huyskens DP: Testing of the Analytical Anisotropic Algorithm for photon dose calculation. Med Phys 2006, 33:4130-48.
  • [15]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, 51:1421-38.
  • [16]Knöös T, Wieslander E, Cozzi L, Brink C, Fogliata A, Albers D, Nyström H, Lassen S: Comparison of dose calculation algorithms for treatment planning in external photon beam therapy for clinical situations. Phys Med Biol 2006, 51:5785-07.
  • [17]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 Electa Sl25 Linear Accelerator. Med Phys 2007, 34:1665-77.
  • [18]Fogliata A, Nicolini G, Vanetti E, Clivio A, Winkler P, Cozzi L: The impact of photon dose calculation algorithms on expected dose dostributions in lungs under different respiratory phases. Phys Med Biol 2008, 53:2375-90.
  • [19]Bragg CM, Conway J: Dosimetric verification of the Anisotropic Analytical Algorithm for radiotherapy treatment planning. Radiother Oncol 2006, 81:315-23.
  • [20]Nielsen TB, Wieslander E, Fogliata A, Nielsen M, Hansen O, Brink C: Influence of dose calculation algorithms on the predicted dose distributions and NTCP values for NSCLC patients. Med Phys 2011, 38:2412-18.
  • [21]Webb S, Nahum AE: A model for calculating tumor control probability in radiotherapy including the effects of inhomogeneous disributions of dose and clonogenic cell density. Phys Med Biol 1993, 39:653-66.
  • [22]Kutcher GJ, Burman C, Brewster L, Goitein M, Mohan R: Histogram reduction method for calculating complication probabilities for three-dimensional treatment planning evaluations. J Radiat Oncol Biol Phys 1991, 21:137-46.
  • [23]Burman C, Kutcher GJ, Emami B, Goiten M: Fitting of normal tissue tolerance data to an analytic function. Int J Radiat Oncol Biol Phys 1991, 21:123-35.
  • [24]De Jaeger K, Hoogeman MS, Engelsman M, Seppenwoolde Y, Damen EM, Mijnheer BJ, Boersma LJ, Lebesque JV: Incorporating an improved dose-calculation algorithm in conformal radiotherapy of lung cancer: re-evaluation of dose in normal lung tissue. Radiother Oncol 2003, 69:1-10.
  • [25]Belderbos JS, De Jaeger K, Heemsbergen WD, Seppenwoolde Y, Baas P, Boersma LJ, Lebesque JV: First results of a phase I/II dose escalation trial in non-small cell lung cancer using three-dimensional conformal radiotherapy. Radiother Oncol 2003, 66:119-26.
  • [26]Martin E, Deville C, Bonnetain F, Bosset M, Créhange G, Truc G, Naudy S, Maingon P: Intensity-modulated radiation therapy in head and neck cancer : prescribed dose, clinical challenges and results. Radiother Oncol 2007, 85:392-08.
  • [27]ICRU report 62: Prescribing, recording and reporting photon beam therapy. 1999. Supplement to ICRU report 50
  • [28]AAPM Report 55: Radiation treatment planning dosimetry verification. New York; 1995.
  • [29]TRS-430: Commissioning and quality assurance of computerized planning systems for radiation treatment of cancer. Vienna: IAEA; 2004.
  • [30]Lyman JT, Wolbarst AB: Optimization of radiation therapy III: a method of assessing complication probabilities from dose volume histograms. Int J Radiat Oncol Biol Phys 1987, 13:103-9.
  • [31]Kallman P, Agren A, Brahme A: Tumor and normal tissue responses to fractionated non-uniform dose delivery. Int J Radiat Biol 1992, 62:249-62.
  • [32]Fowler JF, Chappel R, Ritter M: Is α/β for prostate tumors really low? Int J Radiat Oncol Biol Phys 2001, 50:1021-31.
  • [33]Kal HB, van Gellekom MPR: How low is the α/β ratio for prostate cancer? Int Radiat Oncol Biol Phys 2003, 57:1116-21.
  • [34]Nahum AE, Movsas B, Horwitz EM, Stobbe CC, Chapman JD: Incorporating clinical measurements of hypoxia into tumor local control modelling for prostate cancer: implications for the a/b ratio. Int Radiat Oncol Biol Phys 2003, 57:391-401.
  • [35]Valdagni R, Italia C, Montanaro P, Lanceni A, Lattuada P, Magnani T, Fiorino C, Nahum A: Is the alpha-beta ratio for prostate cancer really low? A prospective, non randomized trial comparing standard and hypofractionated conformal radiation therapy. Radiather Oncol 2005, 75:74-82.
  • [36]Fowler JF, Nahum AE, Orton CG: The best radiotherapy for the treatment of prostate cancer involves hypofractionation. Med Phys 2006, 33:3081-84.
  • [37]Nahum AE, Sanchez N: Tumor control probability modelling: basic principles and application in treatment planning. Phys Med 2001, 17:13-22.
  • [38]Seppenwoolde Y, Lebesque JV, de Jaeger K, Belderbos JS, Boersma LJ, Schilstra C, Henning GT, Hayman JA, Martel MK, Ten Haken RK: Comparing different NTCP models that predict the incidence of radiation pneumonitis. Int J Radiat Oncol Biol Phys 2003, 55:724-35.
  • [39]Emami B, Lyman J, Brown A, Coia L, Goitein M, Munzenrider JE, Shank B, Solin LJ, Wesson M: Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 1991, 21:109-12.
  • [40]Ågren Cronqvist A-K: Quantification of the response of heterogeneous tumors and organized normal tissue to fractionated radiotherapy. Thesis. Stockholm University: Departement of Medical radiation Physics; 1995.
  • [41]Eisbruch A, Ten Haken RK, Kim HM, Marsh LH, Ship JA: Dose, volume and function relationship in parotid salivary glands following conformal and intensity-modulated irradiation of head and neck cancer. Int J Radiat Oncol Biol Phys 1999, 45:577-87.
  • [42]Roesink JM, Moerland MA, Hoekstra A, Van Rijk PP, Terhaard CH: Scintigraphic assessment of early and late parotid gland function after radiotherapy for head and neck cancer: A prospective study of dose volume response relationship. Int J Radiat Oncol Biol Phys 2004, 58:1451-60.
  • [43]Lawrence BM, Ellen DY, Andrew J, Randall KTH, Louis SC, Avraham E, Søren MB, Jiho N, Joseph OD: Use of normal tissue complication probability models in the clinic. Int Radiat Oncol Biol Phys 2010, 76:S10-S19.
  • [44]Kong FM, Pan C, Eisbruch A, Haken RKT: Physical Models and simpler dosimetric descriptors of radiation late toxicity. Semin Radiat Oncol 2007, 17:108-120.
  • [45]Tucker SL, Dong L, Bosch WR, Michalski J, Winter K, Lee AK, Cheung MR, Kuban DA, Cox JD, Mohan R: Fit of a generalized Lyman normal tissue complication probability (NTCP) model to grade ≥ 2 late rectal toxicity data from patients treated on protocol RTOG 94–06. Int J Radiat Oncol Biol Phys 2007, 69:S8-9.
  • [46]Rancati T, Fiorino C, Vavassori V, Baccolini M, Bianchi C, Foppiano F, Menegotti L, Monti A, Pasquino M, Stasi M, Fellin G, Valdagni R: Late rectal bleeding after conformal radiotherapy for prostate cancer: NTCP modeling. Radiother Oncol 2008, 88:S332-3.
  • [47]Söhn M, Yan D, Liang J, Meldolesi E, Vargas C, Alber M: Incidence of late rectal bleeding in high-dose conformal radiotherapy of prostate cancer using equivalent uniform dose-based and dose-volume-based normal tissue complication probability models. Int J Radiat Oncol Biol Phys 2007, 67:1066-73.
  • [48]Morgan AM, Knöös T, McNee SG, Evans CJ, Thwaites DI: Clinical implications of the implementation of advanced treatment planning algorithms for thoracic treatments. Radiother Oncol 2008, 86:48-54.
  • [49]Schilstra C, Meertens H: Calculation of the uncertainty in complication probability for various dose–response models, applied to the parotid gland. Int J Radiat Oncol Biol Phys 2001, 50:147-158.
  • [50]Brahme A: Optimized radiation therapy based on radiobiological objectives. Semin Radiat Oncol 1999, 9:35-47.
  • [51]Niemierko A, Urie M, Goiten M: Optimization of 3D radiation therapy with both physical and biological end points and constraints. Int J Radiat Oncol Biol Phys 1992, 23:99-107.
  • [52]Stewart RD, Li XA: BGRT: Biologically guided radiation therapy – The future is fast approaching! Med Phys 2007, 34:3739-51.
  • [53]Bentzen SM: Radiation therapy: Intensity modulated, image guided, biologically optimized and evidence based. Radiather Oncol 2005, 77:227-30.
  • [54]Begg A, van der Kogel A: Clinical radiobiology in 2008. Radiother Oncol 2008, 86:295-299.
  • [55]Chavaudra N, Bourhis J, Foray N: Quantified relationship between cellular radiosensitivity, DNA repair defects and chromatic relaxation: a study of 19 human tumor cell lines from different origin. Radiother Oncol 2004, 73:373-82.
  • [56]Hill RP, Kasper P, Griffin AM, O’Sullivan B, Catton C, Alasti H, Abbas A, Heydarian M, Ferguson P, Wunder JS, Bell RS: Studies of the in vivo radiosensitivity of human skin fibroblasts. Radiother Oncol 2007, 84:75-83.
  • [57]Martel MK, Sahijdak WM, Ten Haken RK, Kessler ML, Tumsi AT: Fraction size and dose parameters related to the incidence of pericardial effusions. Int J Radiat Oncol Biol Phys 1998, 40:155-61.
  • [58]Gagliardi G, Lax I, Ottolenghi A, Rutquist LE: Long-term cardiac mortality after radiotherapy of breast cancer–application of the relative seriality model. Br J Radiol 1996, 69:839-46.
  • [59]Eriksson F, Gagliardi G, Liedberg A, Lax I, Lee C, Levitt S, Lind B, Rutqvist LE: Long-term cardiac mortality following radiation therapy for Hodgkin’s disease: analysis with the relative seriality model. Radiother Oncol 2000, 55:153-62.
  • [60]Kwa SL, Lebesgue JV, Theuws JCM, Marks LB, Munley MT, Bentel G, Oetzel D, Spahn U, Graham MV, Drzymala RE, Purdy JA, Lichter AS, Martel MK, Ten Haken RK: Radiation pneumonitis as a function of mean dose: an analysis of pooled data of 540 patients. Int J Radiat Oncol Biol Phys 1998, 42:1-9.
  • [61]Gagliardi G, Bjöhle J, Lax I, Ottolenghi A, Eriksson F, Liedberg A, Lind P, Rutqvist LE: Radiation pneumonitis after breast cancer irradiation: Analysis of the complication probability using the relative seriality model. Int J Radiat Oncol Biol Phys 2000, 46:373-81.
  • [62]Rancati T, Fiorino C, Gagliardi G, Cattaneo GM, Sanguineti G: Casanova Borca V, Cozzarini C, Fellin G, Foppiano F, Girelli G, Menegotti L, Piazzolla A, Vavassori V, Valdagni R: Fitting late rectal bleeding data using different NTCP models: results from an Italian multi-centric study (AIROPROS0101). Radiother Oncol 2004, 73:21-32.
  • [63]Peeters ST, Hoogeman MS, Heemsbergen WD, Hart AA, Koper PC, Lebesque JV: Rectal bleeding, fecal incontinence and high stool frequency after conformal radiotherapy for prostate cancer: normal tissue complication probability modeling. Int J Radiat Oncol Biol Phys 2006, 66:11-19.
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