Estimation of the risk for the second cancers induction in healthy tissues during the radiation therapy of liver’s tumor

Authors

10.22052/6.5.23

Abstract

The aim of this study was to estimate the delivered doses to tissues and organs around the liver tumor during radiotherapy and to determine organs with a high probability of secondary induction cancers. This study was carried out using Monte Carlo method.
The used Phantom, the ORNL phantom is for an adult female. The volume of the tumor is as much as 30% of the liver tissue.In the initial step of this study, we will focus on simulating the linear accelerator of Varian 2100 6MV and by comparing the output results with the calculated values;​​ we will make sure that the results of MCNPX code are sufficiently accurate. In the next step, the corrections are considered in phantom and Monte Carlo technique was used for radiotherapy. The dose calculations was done for 38 organs. According to the obtained results in this simulation, the reached doses to other tissues surrounding tumor was in the range of 0.01-13.07%. Among the examined organs, the healthy tissue of the liver, kidney, the left part of bone_rib cage, the right part of bone_rib cage, adrenals pancreas and lung have received 88, 24.5, 24.2, 18.8, 15.9, 7, 5 cGy, respectively. Due to the linear relationship between the dose received in each organ and the risk of cancer of the organ in subsequent years, in the BERT model, the kidneys have a higher risk of secondary cancers than other organs. In calculating of the risk by Monte Carlo method at a given time, the healthy part of the liver has the highest risk of inducing secondary cancers, and the risk of inducing secondary cancers for kidney, the right part of cage, the left part of cage and adrenal glands were 81, 48, 36 and 18 percent, respectively. Secondary cancer induction is more likely for patients who require more therapy for effective radiotherapy than other patients.

 
 

Keywords


[1] V. Gregoire, T.R. Mackie. State of the art on dose prescription, reporting and recording in Intensity-Modulated Radiation Therapy (ICRU report No. 83), Cancer Radiother, 15 (2011) 555–559. [2] R. Siegel, D. Naishadham and A. Jemal. Cancer statistics, CACancer J Clin, 62 (2012) 10–29. [3] D. Sardari, H. Samavat, A. Esmaeeli and R. Maleki. Measurement of depth-dose oflinear accelerator and simulation by use of Geant4 computer code, Rep PractOncol Radiother, 15 (2010) 64–68. [4] S.B. Scarboro, D.S. Followill, R.M. Howell and S.F. Kry. Variations in photon energyspectra of a 6 MV beam and their impact on TLD response, Med Phys, 38 (2011) 2619–2628. [5] F.El. Moussaoui, T.E1. Bardouni, M. Azahra, A. Kamili and H. Boukhal. Monte Carlo calculation for the development of a BNCT neutron source (1eV-10 KeV) using MCNP code, Cancer Radiother, 12 (2008) 360–364. [6] J.L. Thalhofer, W.F. Rebello, S.A. Correa, A.X. Silva, E.M. Souza and D.V. Batista. Calculation of Dose in Healthy Organs, during Radiotherapy 4-Field Box 3D Conformal for Prostate Cancer, Simulation of the Linac 2300, Radiotherapy Room and MAX Phantom, International Journal of Medical Physics, Clinical Engineering and Radiation Oncology, 2 (2013) 61–68. [7] R. Garcia, S.O. Iciar, J.L.L. Guerra, S. sanches and I. Azinovic. Robotic radiosurgery for the treatment of liver metastases. Reports of practical oncology and radiotherapy, 554 (2017) 1–7. [8] A.G. Rijkee, J. Zoetelief and C.P.J. Raaijmakers. Assessment of Induction of Secondary Tumours Due To Various Radiotherapy Modalities, Radiation Protection Dosimetry, 118 (2006) 219–226. [9] S. Yonai, N. Matsufuji and M. Namba. Calculation of out-of-field dose distribution in carbon-ion radiotherapy by Monte Carlo simulation. Med. Phys, 39 (2012) 5028–5039. [10] M. Mazonakis and J. Damilakis. Cancer risk after radiotherapy for benign diseases, Physica Medica, 42 (2017) 1–7. [11] W.A.J. Vandaal, B.M. Goslings, J. Hermans, D.J. Ruiter, C.F. Sepmeyer, M. Vink, W.A. Van Vloten and P. Thomas. Radiation-induced Head and Neck Tumours: Is the Skin as Sensitive as the Thyroid Gland?, Eur j Cancer C/m Oncol, 19 (1983) 1081–1086. [12] G.X. Ding. Energy spectra, angular spread fluence profile and dose distribution of 6 and 18 MV photon beams: results of Monte Carlo simulations for a Varian 2100EX accelerator, Phys Med Biol, 47 (2002) 1025–1046. [13] D. Sheikh-Bagheri and D.W.O. Rogers. Monte Carlo calculation of nine megavoltage photon beam spectra using the BEAM code, Med Phys, 29 (2002) 391–402. [14] A. Mesbahi, P. Mehnati and A. Keshtkar. A comparative Monte Carlo study on 6MV photon beam characteristics of Varian 21EX and Electa SL-25 linacs, Radiat Med, 5 (2007) 23–30. [15] BEIR, Health Risks from Exposure to Low Levels of Ionizing Radiation: BEIR VII, Phase 2 _National Academy of Science, Washington, DC, (2006). [16] A. Mesbahi, P. Mehnati, A. Keshtkar and A. Farajollahi. Dosimetric properties of a flattening filter-free 6-MV photon beam: A Monte Carlo study, Radiat Med, 25 (2007) 315–324. [17] P.J. Keal, J.V. Siebers, B. Libby and R. Mohan. Determining the incident electron fluence for Monte Carlo-based photon treatment planning using a standard measured data set, Medical physics, 30 (2003) 574–579. [18] K.M. Kourinou, M. Mazonakis, E. Lyraraki, J. Stratakis and J. Damilakis. Scattered dose to radiosensitive organs and associated risk for cancer development from head and neck radiotherapy in pediatric patients, Physica Medica, 29 (2013) 650–655. [19] M.J. Berger, J.H. Hubbell, S.M. Seltzer, J. Chang, J.S. Coursey, R. Sukumar, D.S. Zucker and K. Olsen, NIST, PML, Radiation Physics Division, (2010). [20] B. Emami, Tolerance of Normal Tissue to Therapeutic Radiation, Department of Radiation Oncology, Loyola University Medical Center, Maywood, Illinois, USA, (2013).