Hostname: page-component-848d4c4894-75dct Total loading time: 0 Render date: 2024-05-10T23:39:48.524Z Has data issue: false hasContentIssue false
  • English
  • Français

Dosimetric study of the AAA algorithm for the VMAT technique using an anthropomorphic phantom in the pelvic region

Published online by Cambridge University Press:  12 January 2015

Vicente Puchades ,
Alfredo Serna ,
Fernando Mata-Colodro ,
Davis Ramos-Amores ,
Emilio Casal  and
Miguel Alcaraz
Vicente Puchades*
Affiliation:
Department of Medical Physics, Hospital Universitario Santa Lucia, Cartagena, España
Alfredo Serna
Affiliation:
Department of Medical Physics, Hospital Universitario Santa Lucia, Cartagena, España
Fernando Mata-Colodro
Affiliation:
Department of Medical Physics, Hospital Universitario Santa Lucia, Cartagena, España
Davis Ramos-Amores
Affiliation:
Department of Medical Physics, Hospital Universitario Santa Lucia, Cartagena, España
Emilio Casal
Affiliation:
Centro Nacional de Dosimetría (CND), Valencia, España
Miguel Alcaraz
Affiliation:
Departamento de Radiología y Medicina Física, Facultad de Medicina, Universidad de Murcia, Murcia, España
*
Correspondence to: Vicente Puchades Puchades, Mezquita s/n, 30202 Cartagena, Spain. Tel: +34 968 12 86 00; E-mail: Vicente.puchades2@carm.es
Get access Rights & Permissions [Opens in a new window]

Abstract

Purpose

The objective of this work was to investigate the accuracy of AAA dose calculation algorithm for RapidArc volumetric modulated technique (VMAT) in the presence of anatomical heterogeneities in the pelvic region.

Material and methods

An anthropomorphic phantom was used to simulate a prostate case, delineating planning target volumes (PTVs) and organs at risk. VMAT plans were optimised in eclipse (v10·0) treatment planning system (TPS). The dose distributions were calculated by the AAA dose calculation algorithm. A total of 49 thermoluminiscent dosimeters were inserted into the anthropomorphic phantom and dose measurements were compared with the predicted TPS doses.

Results

The average dose variation was −1·5% for planning target volume corresponding to the prostate and −0·3% for planning target volume corresponding to the pelvic nodes, −0·2% for the rectum, +2·4% for the bladder, −2·0% for the femoral heads and +1·0% for the intestinal package.

Conclusion

AAA is a reliable dose calculation for the treatment with VMAT in the anatomy of the pelvis.

Keywords

AAA algorithmanthropomorphic phantomheterogeneities calculationvolumetric arc therapy (VMAT)
Type
Original Articles
Information
Journal of Radiotherapy in Practice , Volume 14 , Issue 2 , June 2015 , pp. 162 - 170
Check for updates
Copyright
© Cambridge University Press 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Mundt, J, Roeske, J C. Can intensity-modulated radiotherapy replace brachytherapy in the management of cervical cancer? counter-point. Brachytherapy 2002; 1: 192–194.CrossRefGoogle Scholar
2.Otto, K. Volumetric modulated arc therapy: IMRT in a single gantry arc. Med Phys 2008; 35: 310–317.Google Scholar
3.Palma, D, Emily, V, James, Ket al. Volumetric modulated arc therapy for delivery of prostate radiotherapy: comparison with intensity-modulated radiotherapy and three-dimensional conformal radiotherapy. Int J Radiat Oncol Biol Phys 2008; 72 (4): 996–1001.Google Scholar
4.Popescu, C C, Olivotto, I A, Beckham, W Aet al. Volumetric modulated arc therapy improves dosimetry and reduces treatment time compared to conventional intensity-modulated radiotherapy for locoregional radiotherapy of left-sided breast cancer and internal mammary nodes. Int J Radiat Oncol Biol Phys 2010; 76: 287–295.Google Scholar
5.Johnston, M, Clifford, S, Bromley, R, Back, M, Oliver, L, Eade, T. Volumetric-modulated arc therapy in head and neck radiotherapy: a planning comparison using simultaneous integrated boost for nasopharynx and oropharynx carcinoma. Clin Oncol 2011; 23: 8503–8511.Google Scholar
6.Oliver, M, Gagne, I, Bush, K, Zavgorodni, S, Ansbacher, W, Beckham, W. Clinical significance of multi-leaf collimator positional error for volumetric modulates arc therapy. Radiother Oncol 2010; 97: 554–560.Google Scholar
7.Davidson, S E, Ibbott, G S, Prado, K L, Dong, L, Liao, Z, Followill, D S. Accuracy of two heterogeneity dose calculation algorithms for IMRT in treatment plans designed using an anthropomorphic thorax phantom. Med Phys 2007; 34: 1850–1857.Google Scholar
8.Létourneau, D, Keller, H, Michael, B S, Jaffray, D A. Integral test phantom for dosimetric quality assurance of image guided and intensity modulated stereotactic radiotherapy. Med Phys 2007; 34: 1850–1857.Google Scholar
9.Davidson, S E, Ibbott, G S, Followill, D S, Popple, R A. Heterogeneity dose calculation accuracy in IMRT: study of five commercial treatment planning systems using an anthropomorphic thorax phantom. Med Phys 2008; 35: 5434–5439.Google Scholar
10.Laub, W U, Bakai, A, Nüsslin, F. Intensity modulated irradiation of a thorax phantom: comparisons between measurements, Monte Carlo calculations and pencil beam calculations. Phys Med Biol 2001; 46: 1695–1706.Google Scholar
11.Low, D A, Gerber, R L, Mutic, S, Purdy, J A. Phantoms for IMRT dose distribution measurement and treatment verification. Int J Radiat Oncol Biol Phys 1998; 40: 1231–1235.Google Scholar
12.Schiefera, H, Fogliata, A, Nicolini, Get al. The Swiss IMRT dosimetry intercomparison using a thorax phantom. Med Phys 2010; 37: 4424–4431.CrossRefGoogle Scholar
13.Ma, C-M, Pawlicki, T, Jiang, S Bet al. Monte Carlo verification of IMRT dose distributions from a commercial treatment planning optimization system. Phys Med Biol 2000; 45: 2483–2496.CrossRefGoogle ScholarPubMed
14.Sterpin, E, Tomsej, M, Vynckie, S, De Smedt, B, Reynaert, N. 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: 1665–1678.Google Scholar
15.Jones, A O, Das, I J, Jones, F L Jr, Monte, A. Carlo study of IMRT beamlets in inhomogeneous media. Med Phys 2003; 30: 296–301.Google Scholar
16.Ulmer, W, Harder, D. A triple gaussian pencil beam model for photon beam treatment planning. Med Phys 1995; 5: 25–30.Google Scholar
17.Ulmer, W, Harder, D. Applications of a triple Gaussian pencil beam model for photon beam treatment planning. Med Phys 1996; 6: 68–74.Google Scholar
18.Ahnesjö, A, Saxner, M, Trepp, A. A pencil beam model photon dose calculation. Med Phys 1992; 19: 263–273.Google Scholar
19.Yoon, M, Lee, D H, Shin, D, Lee, S B, Park, S Y, Cho, K H. Accuracy of inhomogeneity correction algorithm in intensity-modulated radiotherapy of head-and-neck tumors. Med Dosim 2007; 32: 44–51.Google Scholar
20.Martin, J B, Rebecca, E, Tsang, Cet al. Verification of lung dose in an anthropomorphic phantom calculated by the collapsed cone convolution method. Phys Med Biol 2010; 45: N143–N150.Google Scholar
21.Dunscombe, P, McGhee, P, Lederer, E. Anthropomorphic phantom measurements for the validation of a treatment planning system. Phys Med Biol 1996; 41: 399–412.Google Scholar
22.Ibbott, G S, Molineu, A, Followill, D S. Independent evaluations of IMRT through the use of an anthropomorphic phantom. Technol Cancer Res Treat 2006; 5: 481–487.CrossRefGoogle ScholarPubMed
23.Ann Van, E, Laura, T, Jukka, Pet al. Testing of the analytical anisotropic algorithm for photon dose calculation. Med Phys 2006; 33 (11): 4130–4148.Google Scholar
24.Oliver, M, Isabelle, G, Karl, B, Sergie, Z, Will, A, Wayne, B. Clinical significance of multi-leaf collimator positional errors for volumetric modulated arc therapy. Rad Oncol 2010; 97: 554–560.Google Scholar
25.Fraass, B, Doppke, K, Hunt, Met al. American Association of Physicists in Medicine Radiation Therapy Committee Task Group 53: quality assurance for clinical radiotherapy treatment planning. Med Phys 1998; 25: 1773–1829.Google Scholar
26.Kinhikar, R A, Upreti, R, Tambe, C M, Despande, D D. Intensity modulated radiotherapy dosimetry with ion chambers, TLD, MOSFET and EDR2 film. Australas Phys Eng Sci Med 2007; 30: 25–32.Google Scholar
27.Han, T, Mourtada, F, Kisling, K, Mikell, J, Followill, D, Howell, R. Experimental validation of deterministic Acuros XB algorithm for IMRT and VMAT dose calculations with the Radiological Physics Center’s head and neck phantom. Med Phys 2012; 39: 2193–2202.Google Scholar
28.Salinas, J, Serna, A, Iglesias, Aet al. Early results of hypofractionated VMAT IGRT in prostate cancer. Int J Rad Oncol Biol Phys 2012; 84(3S), S375.Google Scholar
29.Clivio, A, Fogliata, A, Franzetti-Pellanda, Aet al. Volumetric-modulated arc radiotherapy for carcinomas of the anal canal: a treatment planning comparison with fixed field IMRT. Rad Oncol 2009; 92: 118–124.Google Scholar
30.Serna, A, Puchades, V, Mata, F. Acceptance for clinical use of a treatment planning system with IMRT and VMAT techniques. Revista de Física Médica 2011; 12: 187–196.Google Scholar
31.Mata Colodro, F, Serna Berná, A, Puchades Puchades, V. Dosimetric validation of a redundant independent calculation software for VMAT fields. Phys Med 2013; 29: 341–349.CrossRefGoogle ScholarPubMed
32.Mijnheer, B, Olszewska, A, Fiorino, Cet al. Quality assurance of treatment planning systems. Practical Examples For Non-IMRT Photon Beams. ESTRO Booklet 7; 2004 ESTRO.Google Scholar
33.Ezzell, G A, Burmeister, J W, Dogan, Net al. IMRT commissioning: multiple institution planning and dosimetry comparisons, a report from AAPM task group 119. Med Phys 2009; 36: 5359–5373.CrossRefGoogle ScholarPubMed
34.Al-Hallaq, H A, Reft, C S, Roeske, J C. The dosimetric effects of tissue heterogeneities in intensity-modulated radiation therapy (IMRT) of the head and neck. Phys Med Biol 2006; 51: 1145–1156.Google Scholar
35.Fogliata, A, Nicollini, 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.Google Scholar
36.Fogliata, A, Nicollini, G, Clivio, A, Vanetti, E, Cozzi, L. Dosimetric evaluation of Acuros XB advanced dose calculation algorithm in heterogeneous media. Radiat Oncol 2011; 6: 82.Google Scholar
37.Rana, S, Rogers, K, Pokharel, S, Cheng, C. Evaluation of Acuros XB algorithm based on RTOG 0813 dosimetric criteria for SBRT lung treatment with RapidArc. J Appl Clin Med Phys 2014; 15: 4474.Google Scholar
38.Liu, H W, Nugent, Z, Clayton, R, Dunscombe, P, Lau, H, Khan, R. Clinical impact of using the deterministic patient dose calculation algortithm Acuros XB for lung stereotactic body radiation therapy. Acta Oncol 2014; 53 (3): 324–329.Google Scholar
39.Rana, S. Clinical dosimetry impact of Acuros XB and analytical anisotropic algorithm (AAA) on real lung cancer treatment plans: review. Int J Cancer Ther Oncol 2014; 2 (1): 02019.CrossRefGoogle Scholar
40.Kan, M W, Leung, L H, So, R W, Yu, P K. Experimental verification of the Acuros XB and AAA dose calculation adjacent to heterogeneous media for IMRT and RapidArc of nasopharyngeal carcinoma. Med Phys 2013; 40: 031714.Google Scholar
41.Kathirvel, M, Subramanian, S, Clivio, Aet al. Critical appraisal of the accuracy of Auros-XB and anisotropic analytical algorithm compared to measurement and calculations with the compass system in the delivery of RapidArc clinical plans. Radiat Oncol 2013; 8: 140.Google Scholar