Evaluation of Tumor Control and Normal Tissue Complication Probability in Head and Neck Cancers with Different Sources of Radiation: A Comparative Study

Document Type: Original Paper

Authors

1 Department of Radiation Oncology, Dr. Ram Manohar Lohia Institute of Medical Sciences, Vibhuti Khand Gomti Nagar, Lucknow -226010 India

2 Department of Radiation Oncology, Dr. Ram Manohar Lohia Institute of Medical Sciences, Vibhuti Khand Gomti Nagar, Lucknow -226010

Abstract

Introduction: The ultimate goal of radiation treatment planning is to yield a high tumor control probability (TCP) with a low normal tissue complication probability (NTCP). Historically  dose volume histogram (DVH) with only volumetric dose distribution was utilized as a popular tool for plan evaluation  hence present study aimed to compare the radiobiological effectiveness of the cobalt-60 (Co-60) gamma photon and 6MV X-rays of linear accelerators (Linac) in the radiotherapy of head and neck tumors. 
Materials and Methods: TCP and NTCP were calculated using DVH through the BIOPLAN software developed by Sanchez-Nieto and Nahum . The treatment planning was performed for all the patients using both treatment modalities (i.e., Co-60 and 6 MV Linac). The TCP was also manually calculated using a mathematical formula proposed by Brenner’s et al.
Results: The average TCP calculated by the BIOPLAN for Co-60 and 6 MV X-rays were 44.6% and 60.8%, respectively. Furthermore, the average NTCPs obtained for the organ at risk, namely optic nerve, for Co-60 and 6 MV X-ray were 0.24 % and 0.03 %, respectively. Regarding the spinal cord, the average NTCPs for Co-60 gamma photon and 6 MV X-ray of Linac were 0.05 % and 0.002%, respectively.
Conclusion: As the findings of the present study indicated, Co-60 unit could provide comparable TCP along with minimal NTCP, compared to the high-cost technologies of Linac. The design of treatment plans based on the radiobiological parameters facilitated the judicious choice of physical parameters for the achievement of high TCP and low NTCP.

Keywords

Main Subjects


 

 

  1. Deasy JO, Mayo CS, Orton CG.. Treatment planning evaluation and optimization should be biologicaly and not dose /volume based. Med. Phys. 2015; 42(6):2753-6. DOI: 10.1118/1.4916670.
  2. Sanchez-Nieto B, Nahum AE.. Bioplan software for the biological evaluation of radiotherapy treatment plans. Medical Dosimetry. 2000; 25(2),:71-6. DOI: 10.1016/S0958-3947(00)00031-5.
  3. Brenner DJ. Dose, volume, and tumor-control predictions in radiotherapy. Int. J. Radiat Oncol Biol. Phys. 1993;  26, (1): 171-9. DOI: 10.1016/0360-3016(93)90189-3.
  4. Fletcher GH. Keynote address: the scientific basis of the present and future practice of clinical radiotherapy. Int J Radiat. Oncol. Biol. Phys 1983; 9:1073-82. DOI: 10.1016/0360-3016(83)90399-1.
  5. Niemierko A, Urie M, Goitein M. Optimization of 3D radiation therapy with both physical and biological end points and constraints. Int. J. Radiat. Oncol. Biol. Phys. 1992; 23:99-108. DOI: 10.1016/0360-3016(92)90548-V.
  6. Sanchez-Nieto B, Nahum AE. The delta-TCP concept: a clinically useful measure of tumor control probability. Int. J. Radiat. Oncol. Biol. Phys. 1999;  44(2), : 369-80. DOI: 10.1016/S0360-3016(99)00029-2.
  7. Withers HR. Biological basis of radiation therapy.; The Lancet. 1992 Jan 18;339(8786):156-9. DOI: 10.1016/0140-6736(92)90218-R.
  8. Niemierko A, Goitein M. Implementation of a model for estimating tumor control probability for an inhomogeneously irradiated tumor. Radiother. Oncol. 1993; 29:140-7. DOI: 10.1016/0167-8140(93)90239-5.
  9. Webb S, Nahum A.E. A model for calculating tumor control probability in radiotherapy including the effects of inhomogeneous distributions of dose and clonogenic cell density. Phys. Med. Biol. 1993; 38: 653-66. DOI: 10.1088/0031-9155/38/6/001.
  10. Fowler JF. Brief summary of radiobiological principles in fractionated radiotherapy. Semin. Radiat. Onco. 1992; 2:16–21. DOI: 10.1016/S1053-4296(05)80045-1
  11. Källman P, Ågren A, Brahme A. Tumour and normal tissue responses to fractionated non-uniform dose delivery. Int. J. Radiat. Biol. 1992; 62(2):249-62. PMID: 1355519.
  12. Brahme A. Individualizing cancer treatment: biological optimization models in treatment planning and delivery. International Journal of Radiation Oncology* Biology* Physics. 2001 Feb 1;49(2):327-37. DOI: 10.1016/S0360-3016(00)01501-7.

Volume 14, Issue 3
September and October 2017
Pages 167-172
  • Receive Date: 05 February 2017
  • Revise Date: 25 March 2017
  • Accept Date: 29 April 2017