Purpose: The aim of this study is to investigate the effect of changing phantom thickness on high dose region of interest (HD_ROI) and low dose ROI’s (LW_ROI’s) doses during helical radiotherapy (RT) by utilizing Adaptive RT (ART) technique.
Materials and Methods: The cylindrical phantom (CP) is wrapped with different thickness boluses and scanned in the kilovoltage computed tomography (KVCT). HD_ROI and LW_ROI’s were created in contouring system and nine same plans (1.8 Gy/Fr) were made with images of different thicknesses CP. The point dose measurements were performed using ionization chamber in Helical Tomotherapy (HT) treatment machine. For detecting thickness reduction effect, CP was irradiated using bolus-designed plans and it was irradiated using without bolus plan. The opposite of this scenario was applied to determine the thickness increase. KVCT and megavoltage CT (MVCT) images were used for dose comparison. The HT Planned Adaptive Software was used to see the differences in the planning and verification doses at dose volume histograms (DVH).
Results: Point dose measurements showed a 4.480% dose increase in 0.5 cm depth reduction for HD_ROI. These differences reached 8.508% in 2 cm depth and 15,279% in 5 cm depth. At the same time, a dose reduction of 0.665% was determined for a 0.5cm depth increase, a dose reduction of 1.771% was determined for a 2 cm depth increase, a dose reduction of 5.202% was determined for a 5 cm depth increase for the HD_ROI. The ART plan results show that the dose changes in the HD_ROI was greater than the LW_ROI’s.
Conclusion: Phantom thicknesses change can lead to a serious dose increase or decrease in the HD_ROI and LW_ROI’s.
If the inline PDF is not rendering correctly, you can download the PDF file here.
 Dubben HH Thames HD Beck-Bornholdt HP. Tumor volume: a basic and specific response predictor in radiotherapy. Radiother Oncol. 1998;47(2):167-74.
 Zhao L Wan Q Zhou Y et al. The role of replanning in fractionated intensity modulated radiotherapy for nasopharyngeal carcinoma. Radiother Oncol. 2011;98(1):23-7.
 Joon-Young J Dae Hyun K Cheon Woong C et al. Analysis of Changes in Skin Dose During Weight Loss when Tomotherapy of Nasopharynx Cancer. Journal of the Korean Magnetics Society. 2016;26(3):99-104.
 Yan D Lockman D Martinez A et al. Computed tomography guided management of interfractional patient variation. Semin Radiat Oncol. 2005;15(3):168-79.
 Piotrowski T Kazmierska J Sokołowski A et al. Impact of the spinal cord position uncertainty on the dose received during head and neck helical tomotherapy. J Med Imaging Radiat Oncol. 2013;57(4):503-511.
 Piotrowski T Ryczkowski A Adamczyk M Jodda A. Estimation of the planning organ at risk volume for the lenses during radiation therapy for nasal cavity and paranasal sinus cancer. J Med Imaging Radiat Oncol. 2015;59(6):743-750.
 Han C Chen YJ Liu A et al.. Actual dose variation of parotid glands and spinal cord for nasopharyngeal cancer patients during radiotherapy. Int J Radiat Oncol Biol Phys. 2008;70(4):1256-1262.
 Nishi T Nishimura Y Shibata T et al. Volume and dosimetric changes and initial clinical experience of a two-step adaptive intensity modulated radiation therapy (IMRT) scheme for head and neck cancer. Radiother Oncol. 2013;106(1):85-89.
 Woodford C Yartsev S Dar AR et al. Adaptive radiotherapy planning on decreasing gross tumor volumes as seen on megavoltage computed tomography images. Int J Radiat Oncol Biol Phys. 2007;69(4):1316-22.
 Chen C Fei Z Chen L et al. Will weight loss cause significant dosimetric changes of target volumes and organs at risk in nasopharyngeal carcinoma treated with Intensity-Modulated Radiation Therapy? Med Dosim. 2014;39(1):34-37.
 Beltran M Ramos M Rovira JJ et al. Dose variations in tumor volumes and organs at risk during IMRT for head and neck cancer. J Appl Clin Med Phys. 2012;13(6):3723.
 Bhide SA Davies M Burke K et al. Weekly volume and dosimetric changes during chemoradiotherapy with intensity-modulated radiation therapy for head and neck cancer: A prospective observational study. Int J Radiat Oncol Biol Phys. 2010;76(5):1360-8.
 Tariq I Chen T Kirkby NF Jena R. Modelling and Bayesian adaptive prediction of individual patients’ tumour volume change during radiotherapy. Phys Med Biol. 2016;61(5):2145-61.
 Fenwick JD Tomé WA Kissick MW Mackie TR. Modelling simple helically delivered dose distributions. Phys Med Biol. 2005; 50(7):1505-17.
 Schirm M Yartsev S Bauman G et al. Consistency check of planned adaptive option on helical tomotherapy. Technol Cancer Res Treat. 2008;7(6):425-32.
 Sen A West MK. Commissioning experience and quality assurance of helical tomotherapy machines. J Med Phys. 2009;34(4):194-9.
 Olivera GH Shepard DM Ruchala K et al.Tomotherapy. Van Dyk J ed. The Modern Technology of Radiation Oncology. Madison WI: Medical Physics Publishing 1999:521-87.
 Mackie TR. History of tomotherapy. Phys Med Biol. 2006;51(13):R427-53.
 Welsh JS Lock M Harari PM et al. Clinical implementation of adaptive helical tomotherapy: a unique approach to image-guided intensity modulated radiotherapy. Tech Cancer Res Treat. 2006;5:465-479.
 Piotrowski T Kaczmarek K Bajon T et al. Evaluation of Image-Guidance Strategies for Prostate Cancer. Technol Cancer Res Treat. 2014;13(6):583-591.
 Yan D. Adaptive radiotherapy: merging principle into clinical practice. Semin Radiat Oncol. 2010;20(2):79-83.
 Thörnqvist S Hysing LB Tuomikoski L et al. Adaptive radiotherapy strategies for pelvic tumors a systematic review ofclinical implementations. Acta Oncol.2016 Aug;55(8):943-58.
 Surucu M Shah KK Roeske JC et al. Adaptive radiotherapy for head and neck cancer implications for clinical and dosimetry outcomes. Technol Cancer Res Treat. 2017;16(2):218-223.
 Yadav P Tolakanahalli R Rong Y Paliwal BR. The effect and stability of MVCT images on adaptive TomoTherapy. J Appl Clin Med Phys. 2010;11(4):3229.
 Meeks SL Harmon JF Jr Langen KM et al. Performance characterization of megavoltage computed tomography imaging on a helical tomotherapy unit. Med Phys. 2005;32(8):2673-81.
 Welsh JS Lock M Harari PM et al. Clinical Implementation of Adaptive Helical Tomotherapy: A Unique Approach to Image-Guided Intensity Modulated Radiotherapy Technology in Cancer Research and Treatment. Technol Cancer ResTreat. 2006;5(5):465-79.
 Yan D Liang J. Expected treatment dose construction and adaptive inverseplanning optimization: implementation for offline head and neck cancer adaptive radiotherapy. Med Phys. 2013;40(2):021719.
 Schwartz DL. Current progress in adaptive radiation therapy for head and neckcancer. Curr Oncol Rep. 2012;14(2):139-47.
 van der Horst A Houweling AC van Tienhoven G et al. Dosimetric effects of anatomical changes during fractionated photon radiation therapy in pancreatic cancer patients. J Appl Clin Med Phys. 2017;18(6):142-151.
 Ren G Xu S-P Du L et al. Actual Anatomical and Dosimetric Changes of Parotid Glands in Nasopharyngeal Carcinoma Patients during Intensity Modulated Radiation Therapy. BioMed Res Int. 2015;2015:670327.
 Duma MN Kampfer S Schuster T et al. Adaptive radiotherapy for soft tissue changes during helical tomotherapy for head and neck cancer. Strahlenther Onkol. 2012;188(3):243-7.
 Ashburner MJ Tudor S. The optimization of superficial planning target volumes (PTVs) with helical tomotherapy. J Appl Clin Med Phys. 2014;15(6):4560.
 Chow JCL 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(5):272-278.
 Piotrowski T Gintowt K Jodda A et al. Impact of the intra- and inter-observer variability in the delineation of parotid glands on the dose calculation during head and neck helical tomotherapy. Technol Cancer Res Treat. 2015;14(4):467-474.
 Jang S Watchman C. SU-FF-T-596: Dosimetric Impact of Anatomic Changes Due to Patient Weight Loss On TomoTherapy Plan. Med Phys. 2009;36:2661–2662.
 Pair ML Du W Rojas HD et al.. Dosimetric effects of weight loss or gain during volumetric modulated arc therapy and intensity-modulated radiation therapy for prostate cancer. Med Dosim. 2013;38(3):251-4.
 Choi HS Jo GS Chae JP et al. Defining the Optimal Time of Adaptive Replanning in Prostate Cancer Patients with Weight Change during Volumetric Arc Radiotherapy: A Dosimetric and Mathematical Analysis Using the Gamma Index. Computational and Mathematical Methods in Medicine. 2017;2017.