Abstract:
Objectives: The present study aimed to generate intensity-modulated beams with compensators for a conventional telecobalt machine, based on dose distributions generated with a treatment planning system (TPS) performing forward planning, and cannot directly simulate a compensator. Materials and Methods: The following materials were selected for compensator construction: Brass, Copper and Perspex (PMMA). Boluses with varying thicknesses across the surface of a tissue-equivalent phantom were used to achieve beam intensity modulations during treatment planning with the TPS. Beam data measured for specific treatment parameters in a full scatter water phantom with a 0.125 cc cylindrical ionization chamber, with a particular compensator material in the path of beams from the telecobalt machine, and that without the compensator but the heights of water above the detector adjusted to get the same detector readings as before, were used to develop and propose a semi-empirical equation for converting a bolus thickness to compensator material thickness, such that any point within the phantom would receive the planned dose. Once the dimensions of a compensator had been determined, the compensator was constructed using the cubic pile method. The treatment plans generated with the TPS were replicated on the telecobalt machine with a bolus within each beam represented with its corresponding compensator mounted on the accessory holder of the telecobalt machine. Results: Dose distributions measured in the tissue-equivalent phantom with calibrated Gafchromic EBT2 films for compensators constructed based on the proposed approach, were comparable to those of the TPS with deviation less than or equal to ± 3% (mean of 2.29 ± 0.61%) of the measured doses, with resultant confidence limit value of 3.21. Conclusion: The use of the proposed approach for clinical application is recommended, and could facilitate the generation of intensity-modulated beams with limited resources using the missing tissue approach rendering encouraging results. © 2018 Samuel N. A. Tagoe et al., published by Sciendo 2018.
