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A hybrid approach for head and neck cancer using online image guidance and offline adaptive radiotherapy planning

Published online by Cambridge University Press:  18 February 2019

Roopam Srivastava*
Affiliation:
Department of Medical Physics and Radiation Safety, International Oncology Centre, Fortis Hospital, Noida, Uttar Pradesh, India
P.K. Sharma
Affiliation:
Department of Medical Physics and Radiation Safety, International Oncology Centre, Fortis Hospital, Noida, Uttar Pradesh, India
K.J. Maria Das
Affiliation:
Department of Radiotherapy, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
Jayanand Manjhi
Affiliation:
Department of BioMedical Science, Shobhit University, Meerut, Uttar Pradesh, India
*
Author for correspondence: Roopam Srivastava, Department of Medical Physics and Radiation Safety, International Oncology Centre, Fortis Hospital, Noida, Uttar Pradesh, India. E-mail: [email protected]

Abstract

Background

This is a prospective study to evaluate the dosimetric benefits of treatment plan adaptation for patients who had undergone repeat computed tomography (ReCT)and re-planning due to treatment-induced anatomical changes during radiotherapy.

Materials and Methods

This study involved five head and neck cancer patients who had their treatment plan modified, based on weekly thrice imaging protocol. Impact of mid-course imaging was assessed in patients using ReCT and cone beam computed tomography (CBCT)-based dose verification. Patients were imaged, apart from their initial CT, during the course of their radiation therapy with a ReCT and on board imager CBCT (Varian Medical Systems Inc., Palo Alto, CA, USA). Each CBCT/CT series was rigidly registered to the initial CT in the treatment planning system Eclipse (Varian Medical Systems Inc.) using bony landmarks. The structures were copied to the current CBCT/CT series and, where needed, manually edited slicewise. The dose distribution from the treatment plan was viewed as of the current anatomy by applying the treatment plan the CBCT/CT series, and studying the corresponding dose–volume histograms for organs at risk doses.

Results

The reduction of parotid volumes due to weight loss was observed in all patients, which means an increase in predicted mean doses of parotid when initial CT plan was re-calculated on ReCT and CBCT (Table 1). This explains the necessity of adaptive planning. The predicted mean dose of parotid glands was increased and constraints to spinal cord and skin were exceeded, so re-planning was performed.

Conclusions

The CBCT is a useful tool to view anatomic changes in patients and get an estimate of their impact on dose distribution. Re-planning based on imaging in head and neck patients during the course of radiotherapy is mandatory to reduce side effects.

Type
Original Article
Copyright
© Cambridge University Press 2019 

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Footnotes

Cite this article: Srivastava R, Sharma PK, Das KJM, Manjhi J. (2019) A hybrid approach for head and neck cancer using online image guidance and offline adaptive radiotherapy planning. Journal of Radiotherapy in Practice18: 271–275. doi: 10.1017/S146039691800078X

References

1. Eisbruch, A, Foote, R L, O’Sullivan, B et al. Intensity-modulated radiation therapy for head and neck cancer: emphasis on the selection and delineation of the targets. Semin Radiat Oncol 2002; 12: 238249.10.1053/srao.2002.32435Google Scholar
2. Clark, C H, Bidmead, A M, Nutting, C M et al. Intensity-modulated radiotherapy improves target coverage, spinal cord sparing and allows dose escalation in patients with locally advanced cancer of the larynx. Radiother Oncol 2004; 70: 189198.10.1016/j.radonc.2003.10.012Google Scholar
3. Barker J L, Garden A S, Ang K K et al. Quantification of volumetric and geometric changes occurring during fractionated radiotherapy for head-and-neck cancer using an integrated CT/linear accelerator system. Int J Radiat Oncol Biol Phys 2004; 59: 960–970.10.1016/j.ijrobp.2003.12.024Google Scholar
4. Ho, K F, Marchant, T, Moore, C et al. Monitoring dosimetric impact of weight loss with kilovoltage (kV) cone beam CT (CBCT) during parotid-sparing IMRT and concurrent chemotherapy. Int J Radiat Oncol Biol Phys 2012; 82 (3): e375e382.10.1016/j.ijrobp.2011.07.004Google Scholar
5. Ahn, P H, Chen, C C, Ahn, A I et al. Adaptive planning in intensity-modulated radiation therapy for head and neck cancers: single-institution experience and clinical implications. Int J Radiat Oncol Biol Phys 2011; 80 (3): 677685.10.1016/j.ijrobp.2010.03.014Google Scholar
6. Elstroem, U V, Grau, C. Adaptive image-guided radiotherapy for head and neck cancer. Functional Preservation and Quality of Life in Head and Neck Radiotherapy 2009; 183–190.10.1007/978-3-540-73232-7_16Google Scholar
7. Schwartz, D L, Garden, A S, Thomas, J et al. Adaptive radiotherapy for head-and-neck cancer: initial clinical outcomes from a prospective trial. Int J Radiat Oncol Biol Phys 2012; 83 (3): 986993.10.1016/j.ijrobp.2011.08.017Google Scholar
8. Wang, W, Yang, H, Hu, W et al. Clinical study of the necessity of replanning before the 25th fraction during the course of intensity-modulated radiotherapy for patients with nasopharyngeal carcinoma. Int J Radiat Oncol Biol Phys 2010; 77 (2): 617621.10.1016/j.ijrobp.2009.08.036Google Scholar
9. The Phantom Laboratory. CatPhan 503 Manual. Handbook, 2012.Google Scholar
10. Dunlop, A, McQuaid, D, Nill, S et al. Comparison of CT number calibration techniques for CBCT-based dose calculation. Strahlenther Onkol 2015; 191 (12): 970978.10.1007/s00066-015-0890-7Google Scholar
11. Franzen, L, Funegard, U, Ericson, T, Henriksson, R. Parotid gland function during and following radiotherapy of malignancies in the head and neck. A consecutive study of salivary flow and patient discomfort. Eur J Cancer 1992; 28 (2-3): 457462.10.1016/S0959-8049(05)80076-0Google Scholar
12. Wang, Z H, Yan, C, Zhang, Z Y et al. Radiation-induced volume changes in parotid and submandibular glands in patients with head and neck cancer receiving postoperative radiotherapy: a longitudinal study. Laryngoscope 2009; 119 (10): 19661974.10.1002/lary.20601Google Scholar
13. Hansen, E K, Bucci, M K, Quivey, J M, Weinberg, V, Xia, P. Repeat CT imaging and replanning during the course of IMRT for head-and-neck cancer. Int J Radiat Oncol Biol Phys 2006; 64 (2): 355362.10.1016/j.ijrobp.2005.07.957Google Scholar
14. Barker, J L Jr., Garden, A S, Ang, K K et al. Quantification of volumetric and geometric changes occurring during fractionated radiotherapy for head-and-neck cancer using an integrated CT/linear accelerator system. Int J Radiat Oncol Biol Phys 2004; 59 (4): 960970.10.1016/j.ijrobp.2003.12.024Google Scholar
15. Robar, J L, Day, A, Clancey, J et al. Spatial and dosimetric variability of organs at risk in head-and-neck intensity-modulated radiotherapy. Int J Radiat Oncol Biol Phys 2007; 68 (4): 11211130.10.1016/j.ijrobp.2007.01.030Google Scholar
16. Woodford, C, Yartsev, S, Dar, A R, Bauman, G, Dyk, J. Van. Adaptive radiotherapy planning on decreasing gross tumor volumes as seen on megavoltage computed tomography images. Int J Radiat Oncol Biol Phys 2007; 69 (4): 13161322.10.1016/j.ijrobp.2007.07.2369Google Scholar
17. Yan, D, Lockman, D, Brabbins, D, Tyburski, L, Martinez, A. An off-line strategy for constructing a patient-specific planning target volume in adaptive treatment process for prostate cancer. Int J Radiat Oncol Biol Phys 2000; 48: 289302.10.1016/S0360-3016(00)00608-8Google Scholar