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Using a Monte Carlo model to predict dosimetric properties of small radiotherapy photon fields.

Accurate characterization of small-field dosimetry requires measurements to be made with precisely aligned specialized detectors and is thus time consuming and error prone. This work explores measurement differences between detectors by using a Monte Carlo model matched to large-field data to predict properties of smaller fields. Measurements made with a variety of detectors have been compared with calculated results to assess their validity and explore reasons for differences. Unshielded diodes are expected to produce some of the most useful data, as their small sensitive cross sections give good resolution whilst their energy dependence is shown to vary little with depth in a 15MV linac beam. Their response is shown to be constant with field size over the range 1-10cm, with a correction of 3% needed for a field size of 0.5cm. BEAMnrc has been used to create a 15MV beam model, matched to dosimetric data for square fields larger than 3cm, and producing small-field profiles and percentage depth doses (PDDs) that agree well with unshielded diode data for field sizes down to 0.5cm. For fields sizes of 1.5cm and above, little detector-to-detector variation exists in measured output factors, however for a 0.5cm field a relative spread of 18% is seen between output factors measured with different detectors-values measured with the diamond and pinpoint detectors lying below that of the unshielded diode, with the shielded diode value being higher. Relative to the corrected unshielded diode measurement, the Monte Carlo modeled output factor is 4.5% low, a discrepancy that is probably due to the focal spot fluence profile and source occlusion modeling. The large-field Monte Carlo model can, therefore, currently be used to predict small-field profiles and PDDs measured with an unshielded diode. However, determination of output factors for the smallest fields requires a more detailed model of focal spot fluence and source occlusion.