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Evaluating the dosimetric consequences of MLC leaf positioning errors in dynamic IMRT treatments

Published online by Cambridge University Press:  12 February 2019

Arpita Agarwal ,
Nikhil Rastogi ,
KJ Maria Das ,
SA Yoganathan ,
D Udayakumar ,
R Naresh  and
Shaleen Kumar
Arpita Agarwal*
Affiliation:
Department of Physics, School of Sciences, IFTM University, Moradabad, Uttar Pradesh, India
Nikhil Rastogi
Affiliation:
Department of Physics, School of Sciences, IFTM University, Moradabad, Uttar Pradesh, India
KJ Maria Das
Affiliation:
Department of Radiotherapy, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
SA Yoganathan
Affiliation:
Department of Radiotherapy, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
D Udayakumar
Affiliation:
Department of Radiotherapy, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
R Naresh
Affiliation:
Department of Radiotherapy, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
Shaleen Kumar
Affiliation:
Department of Radiotherapy, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
*
Author for correspondence: Ms. Arpita Agarwal, Department of Physics, School of Sciences, IFTM University, Moradabad, Uttar Pradesh, India. Tel: 12253605730. E-mail: [email protected]
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Abstract

Purpose

The purpose of this study was to evaluate the dosimetric impact of multileaf collimator (MLC) positional errors on dynamic intensity-modulated radiotherapy (IMRT) treatments through planning simulation. Secondly the sensitivity of IMRT MatriXX device for detecting the MLC leaf positional errors was also evaluated.

Materials and methods

In this study five dynamic IMRT plans, each for brain and head–neck (HN), were retrospectively included. An in-house software was used to introduce random errors (uniform distribution between −2·0 and +2·0 mm) and systematic errors [±0·5, ±0·75, ±1·0 and ±2·0 mm (+: open MLC error and −: close MLC error)]. The error-introduced MLC files were imported into the treatment planning system and new dose distributions were calculated. Furthermore, the dose–volume histogram files of all plans were exported to in-house software for equivalent uniform dose (EUD), tumour control probability and normal tissue complication probability calculations. The error-introduced plans were also delivered on LINAC, and the planar fluences were measured by IMRT MatriXX. Further, 3%/3 mm and 2%/2 mm γ-criteria were used for analysis.

Results

In planning simulation study, the impact of random errors was negligible and ΔEUD was <0·5±0·7%, for both brain and HN. The impact of systematic errors was substantial, and on average, the maximum change in EUD for systematic errors (close 2 mm) was −10·7±3·1% for brain and −15·5±2·6% for HN.

Conclusions

It can be concluded that the acceptable systematic error was 0·4 mm for brain and 0·3 mm for HN. Furthermore, IMRT MatriXX device was able to detect the MLC errors ≥2 mm in HN and >3 mm errors in brain with 2%/2 mm γ-criteria.

Keywords

IMRTMLCrandomsystematicuncertainties
Type
Original Article
Information
Journal of Radiotherapy in Practice , Volume 18 , Issue 3 , September 2019 , pp. 225 - 231
Copyright
© Cambridge University Press 2019 

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Footnotes

Cite this article: Agarwal A, Rastogi N, Maria Das KJ, Yoganathan SA, Udayakumar D, Naresh R, Kumar S. (2019) Evaluating the dosimetric consequences of MLC leaf positioning errors in dynamic IMRT treatments. Journal of Radiotherapy in Practice18: 225–231. doi: 10.1017/S1460396918000705

References

1. Rangel, A, Dunscombe, P. Tolerances on MLC leaf position accuracy for IMRT delivery with a dynamic MLC. Med Phys 2009; 36 (7): 3304–3309.10.1118/1.3134244Google Scholar
2. Woo, M K, Nico, A. Impact of multileaf collimator leaf positioning accuracy on intensity modulation radiation therapy quality assurance ion chamber measurements. Med Phys 2005; 32 (5): 1440–1445.10.1118/1.1901843Google Scholar
3. Luo, W, Li, J, Price, R A et al. Monte Carlo based IMRT dose verification using MLC log files and R/V outputs. Med Phys 2006; 33 (7): 2557–2564.10.1118/1.2208916Google Scholar
4. Zygmanski, P, Kung, J H, Jiang, S B, Chin, L. Dependence of fluence errors in dynamic IMRT on leaf‐positional errors varying with time and leaf number. Med Phys 2003; 30 (10): 2736–2749.10.1118/1.1598674Google Scholar
5. Mu, G, Ludlum, E, Xia, P. Impact of MLC leaf position errors on simple and complex IMRT plans for head and neck cancer. Phys Med Biol 2008; 53 (1): 77–88.10.1088/0031-9155/53/1/005Google Scholar
6. Sastre-Padro, M, Welleweerd, J, Malinen, E, Eilertsen, K, Olsen, D R, van der Heide, U A. Consequences of leaf calibration errors on IMRT delivery. Phys Med Biol 2007; 52 (4): 1147–1156.10.1088/0031-9155/52/4/019Google Scholar
7. Yan, G, Liu, C, Simon, T A, Peng, L C, Fox, C, Li, J G. On the sensitivity of patient‐specific IMRT QA to MLC positioning errors. J Appl Clin Med Phys 2009; 10 (1): 120–128.10.1120/jacmp.v10i1.2915Google Scholar
8. Carver, A, Gilmore, M, Riley, S, Uzan, J, Mayles, P. An analytical approach to acceptance criteria for quality assurance of intensity modulated radiotherapy. Radiother Oncol 2011; 100 (3): 453–455.10.1016/j.radonc.2011.08.045Google Scholar
9. Niemierko, A. Reporting and analyzing dose distributions: a concept of equivalent uniform dose. Med Phys 1997; 24: 103–110.Google Scholar
10. Gay, H A, Niemierko, A. A free program for calculating EUD-based NTCP and TCP in external beam radiotherapy. Physica Medica. 2007; 23 (3): 115–125.10.1016/j.ejmp.2007.07.001Google Scholar
11. Rangel, A, Ploquin, N, Kay, I, Dunscombe, P. Evaluation of linear accelerator performance standards using an outcome oriented approach. Med Phys 2008; 35 (6): 2513–2518.10.1118/1.2921833Google Scholar
12. Tatsumi, D, Hosono, M N, Nakada, R et al. Direct impact analysis of multi-leaf collimator leaf position errors on dose distributions in volumetric modulated arc therapy: a pass rate calculation between measured planar doses with and without the position errors. Phys Med Biol 2011; 56 (20): N237–N246.10.1088/0031-9155/56/20/N03Google Scholar
13. Budgell, G J, Mott, J H, Williams, P C, Brown, K J. Requirements for leaf position accuracy for dynamic multileaf collimation. Phys Med Biol 2000; 45 (5): 1211–1227.10.1088/0031-9155/45/5/310Google Scholar
14. Litzenberg, D W, Moran, J M, Fraass, B A. Verification of dynamic and segmental IMRT delivery by dynamic log file analysis. J Appl Clin Med Phys 2002; 3 (2): 63–72.10.1120/1.1449362Google Scholar
15. Oliver, M, Gagne, I, Bush, K, Zavgorodni, S, Ansbacher, W, Beckham, W. Clinical significance of multi-leaf collimator positional errors for volumetric modulated arc therapy. Radiother Oncol 2010; 97 (3): 554–560.10.1016/j.radonc.2010.06.013Google Scholar
16. Oliver, M, Bush, K, Zavgorodni, S, Ansbacher, W, Beckham, W A. Understanding the impact of RapidArc therapy delivery errors for prostate cancer. J Appl Clin Med Phys 2011; 12 (3): 32–43.10.1120/jacmp.v12i3.3409Google Scholar
17. Coleman, L, Skourou, C. Sensitivity of volumetric modulated arc therapy patient specific QA results to multileaf collimator errors and correlation to dose volume histogram based metrics. Med Phys 2013; 40 (11): 111715.10.1118/1.4824433Google Scholar