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Dosimetric variations in calculation grid size in prostate VMAT: a dose-volume histogram analysis using the Gaussian error function

Published online by Cambridge University Press:  23 November 2017

James C. L. Chow ,
Runqing Jiang  and
Daniel Markel
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
Daniel Markel
Affiliation:
Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
*
Correspondence to: Dr James Chow, Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Canada ON M5G 2M9. Tel: 416 946 4501. Fax: 416 946 6566. E-mail: james.chow@rmp.uhn.ca
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Abstract

Background

Varying the calculation grid size can change the results of dose-volume and radiobiological parameters in a treatment plan, and therefore has an impact on the treatment planning quality assurance.

Purpose

This study investigated the dosimetric influence of the calculation grid size variation in the prostate volumetric modulated arc therapy (VMAT) plan.

Methods and materials

Dose distributions of 10 prostate VMAT plans were acquired using calculation grid sizes of 1–5 mm. Dose-volume histogram (DVH) analysis was carried out to determine the dose-volume variation corresponding to the grid size change using the Gaussian error function (GEF). At the same time, dose-volume points, dose-volume parameters and radiobiological parameters were calculated based on DVHs of targets and organs at risk (OARs) for each grid size.

Results

Comparing percentage variations of GEF parameters between the planning target volume (PTV) and clinical target volume (CTV), GEF parameters of the PTV were found varied more significantly than the CTV. This resulted in larger variations of dose-volume (%ΔCI=40·02 versus 13·55%, %ΔHI=12·45 versus 2·93% and %ΔGI=0·22 versus 0·06%) and radiobiological parameters (%ΔTCP=0·61 versus 0·25% and %ΔEUD=2·11 versus 0·26%) of the PTV compared with CTV. For OARs, the rectal wall showed a larger dose-volume variation than the rectum. However, similar dose-volume variation due to grid size change was not found in the bladder, bladder wall and femur.

Conclusions

Knowing the dosimetric variation in this study is important to the radiotherapy staff in the quality assurance for the prostate VMAT planning.

Keywords

calculation grid sizedose-volume histogramGaussian error functionprostate VMATtreatment planning
Type
Original Article
Information
Journal of Radiotherapy in Practice , Volume 17 , Issue 2 , June 2018 , pp. 162 - 170
Copyright
© Cambridge University Press 2017 

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References

1. Otto, K. Volumetric modulated arc therapy: IMRT in a single gantry arc. Med Phys. 2008; 35: 310–317.Google Scholar
2. Palma, D A, Verbakel, W F, Otto, K, Senan, S. New developments in arc radiation therapy: a review. Can Treat Rev 2012; 36: 393–399.Google Scholar
3. Hardcastle, N, Tomé, W A, Foo, K, Miller, A, Carolan, M, Metcalfe, P. Comparison of prostate IMRT and VMAT biologically optimised treatment plans. Med Dosim. 2011; 36: 292–298.Google Scholar
4. Quan, E M, Li, X, Li, Y et al. A comprehensive comparison of IMRT and VMAT plan quality for prostate cancer treatment. Int J Radiat Oncol Bio Phys 2012; 83: 1169–1178.Google Scholar
5. Khan, M I, Jiang, R, Kiciak, A, Ur Rehman, J, Afzal, M, Chow, J C L. Dosimetric and radiobiological characterizations of prostate intensity modulated radiotherapy and volumetric modulated arc therapy: a single institution review of ninety cases. J Med Phys 2016; 41: 162–168.Google Scholar
6. Chow, J C L, Jiang, R. Comparison of dosimetric variation between prostate IMRT and VMAT due to patient’s weight loss: patient and phantom study. Rep Pract Oncol Radiother 2013; 18: 272–278.Google Scholar
7. 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.Google Scholar
8. Letourneau, D, Publicover, J, Kozelka, J, Moseley, D J, Jaffray, D A. Novel dosimetric phantom for quality assurance of volumetric modulated arc therapy. Med Phys 2009; 36: 1813–1821.Google Scholar
9. Liang, B, Liu, B, Zhou, F, Yin, F, Wu, Q. Comparisons of volumetric modulated arc therapy (VMAT) quality assurance (QA) systems: sensitivity analysis to machine errors. Radiat Oncol 2016; 11: 146–156.Google Scholar
10. Earl, M A, Shepard, D M, Naqvi, S, Li, X A, Yu, C X. Inverse planning for intensity-modulated arc therapy using direct aperture optimization. Phys Med Biol 2003; 48: 1075–1089.Google Scholar
11. Chow, J C L, Grigorov, G N, Nuri, Y. SWIMRT: a graphical user interface using sliding window algorithm to construct fluence map machine file. J Appl Clin Med Phys 2006; 7: 69–85.Google Scholar
12. Dempsey, J F, Romeijn, J E, Li, J G, Low, D A, Palta, J R. A Fourier analysis of the dose grid resolution required for accurate IMRT fluence map optimization. Med Phys. 2005; 32: 380–388.Google Scholar
13. Chung, H, Jin, H, Palta, J, Suh, T S, Kim, S. Dose variations with varying calculation grid size in head and neck IMRT. Phys Med Biol 2006; 51: 4841–4856.Google Scholar
14. Srivastava, S P, Cheng, C, Das, I J. The dosimetric and radiobiological impact of calculation grid size on head and neck IMRT. Pract Radiat Oncol 2017; 7: 209–217.Google Scholar
15. Chow, J C L, Markel, D, Jiang, R. Dose-volume histogram analysis in radiotherapy using the Gaussian error function. Med Phys 2008; 35: 1398–1402.Google Scholar
16. Chow, J C L, Jiang, R, Markel, D. The effect of interfraction prostate motion on IMRT plans: a dose-volume histogram analysis using a Gaussian error function model. J Appl Clin Med Phys 2009; 10: 79–95.Google Scholar
17. Chow, J C L, Markel, D, Jiang, R. Calculation of normal tissue complication probability using Gaussian error function model. Med Phys. 2010; 37: 4924–4929.Google Scholar
18. Chow, J C L, Jiang, R, Daniel, M. 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; 12: 189–194.Google Scholar
19. Chow, J C L, Jiang, R, Kiciak, A, Daniel, M. 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: 263–268.Google Scholar
20. 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
21. Chow, J C L, Jiang, R. Dosimetry estimation on variations of patient size in prostate volumetric-modulated arc therapy. Med Dosim. 2013; 38: 42–47.Google Scholar
22. Okunieff, P, Morgan, D, Niemierko, A, Suit, H D. Radiation dose-response of human tumours. Int J Radiat Oncol Bio Phys 1995; 32: 1227–1237.Google Scholar
23. Lyman, J T. Complication probability as assessed from dose-volume histograms. Radiat Res Suppl 1985; 8: S13–9.Google Scholar
24. Burman, C, Kutcher, G J, Emami, B, Goitein, M. Fitting of normal tissue tolerance data to an analytic function. Int J Radiat Oncol Biol Phys 1991; 21: 123–135.Google Scholar
25. Kutcher, G J, Burman, C, Brewster, L, Goitein, M, Mohan, R. Histogram reduction method for calculating complication probabilities for three-dimensional treatment planning evaluations. Int J Radiat Oncol Biol Phys 1991; 21: 137–146.Google Scholar
26. Jiang, R, Barnett, R B, Chow, J C L, Chen, J. The use of spatial dose gradients and probability density function to evaluate the effect of internal organ motion for prostate IMRT treatment planning. Phys Med Biol 2007; 52: 1469–1484.Google Scholar
27. Henriquez, F C, Castrillon, S V. A quality index for equivalent uniform dose. J Med Phys 2011; 36: 126–132.Google Scholar
28. Kataria, T, Sharma, K, Subramani, V, Karrthick, K P, Bisht, S S. Homogeneity index: An objective tool for assessment of conformal radiation treatments. J Med Phys 2012; 37: 207–213.Google Scholar
29. ICRU Report 62: Prescribing, Recording, and Reporting Photon Beam Therapy (Supplement to ICRU Report 50) (International Commission on Radiation Units and Measurements). Bethesda, Maryland: ICRU, 1999.Google Scholar
30. Feuvret, L, Noël, G, Mazeron, J J, Bey, P. Conformity index: a review. Int J Radiat Oncol Biol Phys 2006; 64: 333–342.Google Scholar
31. Paddick, I, Lippitz, B. A simple dose gradient measurement tool to complement the conformity index. J Neurosurg. 2006; 105: 194–201.Google Scholar
32. Grigor, G N, Koster, K, Chow, J C L, Osei, E K. Prostate IMRT: two-dimensional model of rectal NTCP employing the variability of rectal motion and rectum wall thickness. Int J Radiat Res 2014; 12: 283–293.Google Scholar
33. Chow, J C L. Internet-based computer technology on radiotherapy. Rep Pract Oncol Radiother 2017; 22: 455–462.Google Scholar