Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-26T21:29:28.375Z Has data issue: false hasContentIssue false

Effect of translational couch shifts in volumetric modulated arc therapy (VMAT) plans and predicting its impact on daily dose delivery

Published online by Cambridge University Press:  10 November 2017

Noufal M. Padannayil*
Affiliation:
Department of Medical Physics and Radiotherapy, Baby Memorial Hospital, Calicut, India Department of Physics, Farook College, Calicut, India University of Calicut, Malapuram, Kerala, India
Kallikuzhiyil K. Abdullah
Affiliation:
Department of Physics, Farook College, Calicut, India University of Calicut, Malapuram, Kerala, India
Pallimanhayil A. R. Subha
Affiliation:
Department of Physics, Farook College, Calicut, India University of Calicut, Malapuram, Kerala, India
Sanudev Sadanadan
Affiliation:
Department of Medical Physics and Radiotherapy, Baby Memorial Hospital, Calicut, India
*
Correspondence to: Noufal M. Padannayil, Baby Memorial Hospital, Calicut, Kerala, India. Tel: +917358083838. E-mail: [email protected]

Abstract

Aim

To evaluate the impact of couch translational shifts on dose–volume histogram (DVH) and radiobiological parameters [tumour control probability (TCP), equivalent uniform dose (EUD) and normal tissue complication probability (NTCP)] of volumetric modulated arc therapy (VMAT) plans and to develop a simple and swift method to predict the same online, on a daily basis.

Methods

In total, ten prostate patients treated with VMAT technology were selected for this study. The plans were generated using Eclipse TPS and delivered using Clinac ix LINAC equipped with a Millennium 120 multileaf collimator. In order to find the effect of systematic translational couch shifts on the DVH and radiobiological parameters, errors were introduced in the clinically accepted base plan with an increment of 1 mm and up to 5 mm from the iso-centre in both positive and negative directions of each of the three axis, x [right–left (R-L)], y [superior–inferior (S-I)] and z [anterior–posterior (A-P)]. The percentages of difference in these parameters (∆D, ∆TCP, ∆EUD and ∆NTCP) were analyzed between the base plan and the error introduced plans. DVHs of the base plan and the error plans were imported into the MATLAB software (R2013a) and an in-house MATLAB code was generated to find the best curve fitted polynomial functions for each point on the DVH, there by generating predicted DVH for planning target volume (PTV), clinical target volume (CTV) and organs at risks (OARs). Functions f(x, vj), f(y, vj) and f(z, vj) were found to represent the variation in the dose when there are couch translation shifts in R-L, S-I and A-P directions, respectively. The validation of this method was done by introducing daily couch shifts and comparing the treatment planning system (TPS) generated DVHs and radiobiological parameters with MATLAB code predicted parameters.

Results

It was noted that the variations in the dose to the CTV, due to both systematic and random shifts, were very small. For CTV and PTV, the maximum variations in both DVH and radiobiological parameters were observed in the S-I direction than in the A-P or R-L directions. ∆V70 Gy and ∆V60 Gy of the bladder varied more due to S-I shift whereas, ∆V40 Gy, ∆EUD and ∆NTCP varied due to A-P shifts. All the parameters in rectum were most affected by the A-P shifts than the shifts in other two directions. The maximum percentage of deviation between the TPS calculated and MATLAB predicted DVHs of plans were calculated for targets and OARs and were found to be less than 0·5%.

Conclusion

The variations in the parameters depend upon the direction and magnitude of the shift. The DVH curves generated by the TPS and predicted by the MATLAB showed good correlation.

Type
Original Article
Copyright
© Cambridge University Press 2017 

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. Otto, K. Volumetric modulated arc therapy: IMRT in a single gantry arc. Med Phys 2008; 35: 310317.Google Scholar
2. Zhang, P, Happersett, L, Hunt, M, Jackson, A, Zelefsky, M, Mageras, G. Volumetric modulated arc therapy: planning and evaluation for prostate cancer cases. Int J Radiat Oncol Biol Phys 2010; 76: 14561462.Google Scholar
3. Vanetti, E, Clivio, A, Nicolini, G et al. Volumetric modulated arc radiotherapy for carcinomas of the oro-pharynx, hypo-pharynx and larynx: a treatment planning comparison with fixed field IMRT. Radiother Oncol 2009; 92: 111117.Google Scholar
4. Cozzi, L, Dinshaw, K A, Shrivastava, S K et al. A treatment planning study comparing volumetric arc modulation with RapidArc and fixed field IMRT for cervix uteri radiotherapy. Radiother Oncol 2008; 89: 180191.Google Scholar
5. Fogliata, A, Clivio, A, Nicolini, G, Vanetti, E, Cozzi, L. Intensity modulation with photons for benign intracranial tumours: a planning comparison of volumetric single arc, helical arc and fixed gantry techniques. Radiother Oncol 2008; 89: 254262.Google Scholar
6. Fu, W, Yang, Y, Yue, N J, Heron, D E, Saiful Huq, M. Dosimetric influences of rotational setup errors on head and neck carcinoma intensity-modulated radiation therapy treatments. Med Dosim 2013; 38 (2): 125132.Google Scholar
7. Wertz, H, Lohr, F, Dobler, B et al. Dosimetric consequences of a translational isocenter correction based on image guidance for intensity modulated radiotherapy (IMRT) of the prostate. Phys Med Biol 2007; 52 (18): 56555665.Google Scholar
8. Fu, W, Yang, Y, Li, X, Heron, D E, Huq, M S, Yue, N J. Dosimetric effects of patient rotational setup errors on prostate IMRT treatments. Phys Med Biol 2006; 51 (20): 53215331.Google Scholar
9. Oliver, M, Gagne, I, Bush, K, Zavgorodni, S, Ansbacher, W, Beck-ham, W. Clinical significance of multi-leaf collimator positional errors for volumetric modulated arc therapy. Radiother Oncol 2010; 97: 554560.Google Scholar
10. 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: 3243.Google Scholar
11. Noufal, M P, Abdullah, K K, Niyas, P, Nambiar, V R. Analysis of influence of errors in angular settings of couch and collimator on the dosimetric and radiobiological parameters in VMAT plans. J Med Imaging Radiat Sci 2017; 48 (2): 166177.Google Scholar
12. Becker-Schiebe, M, Abaci, A, Ahmad, T et al. Reducing radiation-associated toxicity using online image guidance (IGRT) in prostate cancer patients undergoing dose-escalated radiation therapy. Rep Pract Oncol Radiother 2016; 21 (3): 188194.Google Scholar
13. Park, S S, Yan, D, McGrath, S et al. Adaptive image-guided radiotherapy (IGRT) eliminates the risk of biochemical failure caused by the bias of rectal distension in prostate cancer treatment planning: clinical evidence. Int J Radiat Oncol Biol Phys 2012; 83 (3): 947952.Google Scholar
14. ICRU. Prescribing, recording and reporting photon beam therapy. ICRU Report No 50. ICRU; Bethesda, MD, USA, 1993.Google Scholar
15. van Herk, M, Remeijer, P, Rasch, C, Lebesque, J V. The probability of correct target dosage: dose-population histograms for deriving treatment margins in radiotherapy. Int J Radiat Oncol Biol Phys 2000; 47: 11211135.Google Scholar
16. Wen, N, Kumarasiri, A, Nurushev, T et al. An assessment of PTV margin based on actual accumulated dose for prostate cancer radiotherapy. Phys Med Biol 2013; 58 (21): 77337744.Google Scholar
17. Gill, S K, Reddy, K, Campbell, N, Chen, C. Determination of optimal PTV margin for patients receiving CBCT-guided prostate IMRT: comparative analysis based on CBCT dose calculation with four different margins. J Appl Clin Med Phys 2015; 16 (6): 252262.Google Scholar
18. Gay, H A, Niemierko, A. A free program for calculating EUD-based NTCP and TCP in external beam radiotherapy. Phys Med 2007; 23: 115125.Google Scholar
19. Semenenko, V A, Li, X A. Lyman-Kutcher-Burman NTCP model parameters for radiation pneumonitis and xerostomia based on combined analysis of published clinical data. Phys Med Biol 2008; 53: 737755.Google Scholar
20. Levegrun, S, Jackson, A, Zelefsky, M J et al. Risk group dependence of dose-response for biopsy outcome after three-dimensional conformal radiation therapy of prostate cancer. Radiother Oncol 2002; 63: 1126.Google Scholar
21. Sovik, A, Ovrum, J, Olsen, DR, Malinen, E. On the parameter describing the generalised equivalent uniform dose (gEUD) for tumours. Phys Med 2007; 23: 100106.Google Scholar
22. Cheung, M R, Tucker, S L, Dong, L et al. Investigation of bladder dose and volume factors influencing late urinary toxicity after external beam radiotherapy for prostate cancer. Int J Radiat Oncol Biol Phys 2007; 67: 10591065.Google Scholar
23. Michalski, J M, Gay, H, Jackson, A, Tucker, S L, Deasy, J O. Radiation dose-volume effects in radiation-induced rectal injury. Int J Radiat Oncol Biol Phys 2010; 76: S123S129.Google Scholar
24. Lo, C, Huang, D, Hong, J. The dose-volume differences by set-up error for prostate. Med Phys 2007; 34: 24942494.Google Scholar
25. Algan, O, Jamgade, A, Ali, I et al. The dosimetric impact of daily setup error on target volumes and surrounding normal tissue in the treatment of prostate cancer with intensity-modulated radiation therapy. Med Dosim 2012; 37 (4): 406411.Google Scholar
26. Arumugam, S, Xing, A, Holloway, L, Goozee, G. A study on the sensitivity of VMAT and IMRT prostate plans considering uncertainties in treatment delivery and patient positioning. Med Phys 2011; 38: 36723672.Google Scholar