<p>The main focus of this work is to improve the existing clinical machine model within the Pinnacle software planning system (at Juravinski Cancer Center, Hamilton, CA). The incident energy fluence spectrum exiting from the accelerator head is considered an important element of the machine model. Relying on the Pinnacle auto modeling function to determine the relative photon fluence spectrum based on percent depth dose curves fitting for various filed sizes, led to different solutions when the process cycle were repeated. This work presents a new method for determining the Pinnacle photon energy fluence spectrum based on 6 MV Varian 21EX machine. A Monte Carlo simulation spectrum based on BEAMnrc code was attenuated to various depths of water. We determine that, the BEAMnrc spectrum attenuated by 15 cm of water gives the closest agreement between the computed and measured depth dose, similar to the clinical machine spectrum.</p> <p>Implementing the novel spectrum into a machine that retained the same modeling parameters as the clinical machine (21ex-JCC) shows a slight better calculation of the output factor. The MLC model parameters were also investigated, however, adjusting the MLC offset table was found to give significant improvements, especially for the small field geometries.</p> <p>The full impact of adjusting the photon energy spectrum, Off-Axis Softening Factor, MLC rounded leaf tip radius and MLC calibration offsets were investigated individually, resulting in a good model parameter fit. Several proposed supplementary setups were created to further assess our model. This include a geometry sensitive to MLC abutment leakage, the calculation of output factors for long and narrow MLC defined fields, and small square MLC and jaws defined fields. A Sun-Point diode detector was used in the measurement of the output factors for its accurate precision at small geometries. In addition, a GAFCHROMIC EBT2 film dosimetry was used in the measurement of the MLC abutment leakage.</p> <p>Our new model shows superior results in comparison to the clinical 21ex-JCC machine model, especially with MLC small field calculations. We conclude that relying on PDD curves and dose profiles validation method in assessing the model might not necessarily lead to the best machine parameters, since these are not sensitive to subtle changes in parameters that have important dosimetric consequences.</p> / Master of Science (MSc)