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Evaluation of plan optimisers in prostate VMAT using the dose distribution index

Published online by Cambridge University Press:  29 April 2019

James C. L. Chow Open the ORCID record for James C. L. Chow [Opens in a new window] ,
Runqing Jiang  and
Lu Xu
James C. L. Chow*
Affiliation:
Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Canada Department of Radiation Oncology, University of Toronto, Toronto, Canada
Runqing Jiang
Affiliation:
Medical Physics Department, Grand River Regional Cancer Centre, Kitchener, Canada Department of Physics, University of Waterloo, Waterloo, Canada
Lu Xu
Affiliation:
Medical Physics Department, Grand River Regional Cancer Centre, Kitchener, Canada Department of Physics, University of Waterloo, Waterloo, Canada
*
Author for correspondence: Dr James Chow, Department of Medical Physics, Princess Margaret Cancer Centre/UHN, 7/F, 700 University Avenue, Toronto, ON, Canada M5G 1X6. Tel: 416 946 4501. Fax: 416 946 6566. E-mail: james.chow@rmp.uhn.ca
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Abstract

Purpose:

Dose distribution index (DDI) is a treatment planning evaluation parameter, reflecting dosimetric information of target coverage that can help to spare organs at risk (OARs) and remaining volume at risk (RVR). The index has been used to evaluate and compare prostate volumetric modulated arc therapy (VMAT) plans using two different plan optimisers, namely photon optimisation (PO) and its predecessor, progressive resolution optimisation (PRO).

Materials and methods:

Twenty prostate VMAT treatment plans were created using the PO and PRO in this retrospective study. The 6 MV photon beams and a dose prescription of 78 Gy/39 fractions were used in plans with the same dose–volume criteria for plan optimisation. Dose–volume histograms (DVHs) of the planning target volume (PTV), as well as of OARs such as the rectum, bladder, left and right femur were determined in each plan. DDIs were calculated and compared for plans created by the PO and PRO based on DVHs of the PTV and all OARs.

Results:

The mean DDI values were 0·784 and 0·810 for prostate VMAT plans created by the PO and PRO, respectively. It was found that the DDI of the PRO plan was about 3·3% larger than the PO plan, which means that the dose distribution of the target coverage and sparing of OARs in the PRO plan was slightly better. Changing the weighting factors in different OARs would vary the DDI value by ∼7%. However, for plan comparison based on the same set of dose–volume criteria, the effect of weighting factor can be neglected because they were the same in the PO and PRO.

Conclusions:

Based on the very similar DDI values calculated from the PO and PRO plans, with the DDI value in the PRO plan slightly larger than that of the PO, it may be concluded that the PRO can create a prostate VMAT plan with slightly better dose distribution regarding the target coverage and sparing of OARs. Moreover, we found that the DDI is a simple and comprehensive dose–volume parameter for plan evaluation considering the target, OARs and RVR.

Keywords

dose distribution indexplan optimisationprostate radiotherapytreatment planning evaluationVMAT
Type
Original Article
Information
Journal of Radiotherapy in Practice , Volume 18 , Issue 4 , December 2019 , pp. 323 - 328
Copyright
© Cambridge University Press 2019 

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References

Fraass, B, Doppke, K, Hunt, M et al. American Association of Physicists in Medicine Radiation Therapy Committee Task Group 53: quality assurance for clinical radiotherapy treatment planning. Med Phys 1998; 25 (10): 1773–1829.10.1118/1.598373CrossRefGoogle Scholar
Malicki, J. The importance of accurate treatment planning, delivery, and dose verification. Rep Pract Oncol Radiother 2012; 17 (2): 63–65.10.1016/j.rpor.2012.02.001CrossRefGoogle ScholarPubMed
Smilowitz, J B, Das, I J, Feygelman, V et al. AAPM medical physics practice guideline 5. a.: commissioning and QA of treatment planning dose calculations—megavoltage photon and electron beams. J App Clin Med Phys 2015; 16 (5): 14–34.10.1120/jacmp.v16i5.5768CrossRefGoogle Scholar
Feuvret, L, Noël, G, Mazeron, J J, Bey, P. Conformity index: a review. Int J Radiat Oncol Biol Phys 2006; 64 (2): 333–342.10.1016/j.ijrobp.2005.09.028CrossRefGoogle ScholarPubMed
Yoon, M, Park, SY, Shin, D et al. A new homogeneity index based on statistical analysis of the dose–volume histogram. J App Clin Med Phys 2007; 8 (2): 9–17.10.1120/jacmp.v8i2.2390CrossRefGoogle ScholarPubMed
Wagner, T H, Bova, F J, Friedman, W A, Buatti, J M, Bouchet, L G, Meeks, S L. A simple and reliable index for scoring rival stereotactic radiosurgery plans. Int J Radiat Oncol Biol Phys 2003; 57 (4): 1141–1149.10.1016/S0360-3016(03)01563-3CrossRefGoogle ScholarPubMed
Chow, J C L, Jiang, R, Markel, D. Variation of PTV dose distribution on patient size in prostate VMAT and IMRT: a dosimetric evaluation using the PTV dose–volume factor. J Radiother Pract 2014; 13 (2): 189–194.10.1017/S1460396913000137CrossRefGoogle Scholar
Chow, J C L, Jiang, R, Kiciak, A, Markel, D. Dosimetric comparison between the prostate intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT) plans using the planning target volume (PTV) dose–volume factor. J Radiother Pract 2016; 15 (3): 263–268.10.1017/S1460396916000194CrossRefGoogle Scholar
Webb, S, Nahum, A E. A model for calculating tumour control probability in radiotherapy including the effects of inhomogeneous distributions of dose and clonogenic cell density. Phys Med Biol 1993; 38 (6): 653–666.10.1088/0031-9155/38/6/001CrossRefGoogle ScholarPubMed
Kutcher, G J, Burman, C. Calculation of complication probability factors for non-uniform normal tissue irradiation: the effective volume method gerald. Int J Radiat Oncol Biol Phys 1989; 16 (6): 1623–1630.10.1016/0360-3016(89)90972-3CrossRefGoogle Scholar
Niemierko, A. Reporting and analyzing dose distributions: a concept of equivalent uniform dose. Med Phys 1997; 24 (1): 103–110.10.1118/1.598063CrossRefGoogle ScholarPubMed
Warkentin, B, Stavrev, P, Stavreva, N, Field, C, Fallone, B G. A TCP-NTCP estimation module using DVHs and known radiobiological models and parameter sets. J App Clin Med Phys 2004; 5 (1): 50–63.10.1120/jacmp.v5i1.1970CrossRefGoogle ScholarPubMed
Paudel, N R, Narayanasamy, G, Han, E Y et al. Dosimetric and radiobiological comparison for quality assurance of IMRT and VMAT plans. J App Clin Med Phys 2017; 18 (5): 237–244.10.1002/acm2.12145CrossRefGoogle ScholarPubMed
Isa, M, Jiang, R, Kiciak, A, Rehman, J, Afzal, M, Chow J C L. Dosimetric and radiobiological characterizations of prostate IMRT and VMAT: a single-institution review of 90 cases. J Med Phys 2016; 41: 162–168.Google Scholar
Alfonso, J C, Herrero, M A, Nunez, L. A dose-volume histogram based decision-support system for dosimetric comparison of radiotherapy treatment plans. Radiat Oncol 2015; 10 (1): 263.10.1186/s13014-015-0569-3CrossRefGoogle ScholarPubMed
Chow, J C L, Jiang, R, Kiciak, A. Dose-volume consistency and radiobiological characterization between prostate IMRT and VMAT plans. Int J Cancer Ther Oncol 2016; 4: 447.Google Scholar
Quan, EM, Li, X, Li, Y et al. A comprehensive comparison of IMRT and VMAT plan quality for prostate cancer treatment. Int J Radiat Oncol Biol Phys 2012; 83 (4): 1169–1178.10.1016/j.ijrobp.2011.09.015CrossRefGoogle ScholarPubMed
Davidson, M T, Blake, S J, Batchelar, D L, Cheung, P, Mah, K. Assessing the role of volumetric modulated arc therapy (VMAT) relative to IMRT and helical tomotherapy in the management of localized, locally advanced, and post-operative prostate cancer. Int J Radiat Oncol Biol Phys 2011; 80 (5): 1550–1558.10.1016/j.ijrobp.2010.10.024CrossRefGoogle ScholarPubMed
EclipseTM Photon and Electron Reference Guide. Document ID P1015026-001-A ed. Palo Alto, CA, USA: Varian Medical Systems Inc.; 2015. p. 343.Google Scholar
Liu, H, Sintay, B, Pearman, K et al. Comparison of the progressive resolution optimizer and photon optimizer in VMAT optimization for stereotactic treatments. J Appl Clin Med Phys 2018; 19: 155–162.10.1002/acm2.12355CrossRefGoogle ScholarPubMed
Binny, D, Kairn, T, Lancaster, C M, Trapp, J V, Crowe, S B. Photon optimizer (PO) vs progressive resolution optimizer (PRO): a conformality-and complexity-based comparison for intensity-modulated arc therapy plans. Med Dosim 2018; 43 (3): 267–275.10.1016/j.meddos.2017.10.003CrossRefGoogle ScholarPubMed
Jiang, F, Wu, H, Yue, H, Jia, F, Zhang, Y. Photon Optimizer (PO) prevails over Progressive Resolution Optimizer (PRO) for VMAT planning with or without knowledge-based solution. J Appl Clin Med Phys 2017; 18 (2): 9–14.10.1002/acm2.12038CrossRefGoogle ScholarPubMed
Chow, J C L, Jiang, R. Prostate volumetric-modulated arc therapy: dosimetry and radiobiological model variation between the single-arc and double-arc technique. J Appl Clin Med Phys 2013; 14: 3–12.10.1120/jacmp.v14i3.4053CrossRefGoogle ScholarPubMed
Bentzen, S M, Constine, L S, Deasy, J O et al. Quantitative Analyses of Normal Tissue Effects in the Clinic (QUANTEC): an introduction to the scientific issues. Int J Radiat Oncol Biol Phys 2010; 76 (3): S3–S9.10.1016/j.ijrobp.2009.09.040CrossRefGoogle ScholarPubMed
Li, G, Zhang, Y, Jiang, X et al. Evaluation of the ArcCHECK QA system for IMRT and VMAT verification. Phys Med 2013; 29 (3): 295–303.10.1016/j.ejmp.2012.04.005CrossRefGoogle ScholarPubMed
Neilson, C, Klein, M, Barnett, R, Yartsev, S. Delivery quality assurance with ArcCHECK. Med Dosim 2013; 38 (1): 77–80.10.1016/j.meddos.2012.07.004CrossRefGoogle ScholarPubMed
Chow, J C L. Internet-based computer technology on radiotherapy. Rep Pract Oncol Radiother 2017; 22: 455–462.10.1016/j.rpor.2017.08.005CrossRefGoogle ScholarPubMed