Monte Carlo calculation of quality correction factors based on air kerma and absorbed dose to water in medium energy x-ray beams

Clinical dosimetry is typically performed using ion chambers calibrated in terms of absorbed dose to water. As primary measurement standards for this quantity for low and medium energy x-rays are available only since a few years, most dosimetry protocols for this photon energy range are still based on air kerma calibration. For that reason, data for beam quality correction factors kQ,Q0, necessary for the application of dose to water based protocols, are scarce in literature. Currently the international IAEA TRS-398 Code of Practice is under revision and new kQ,Q0 factors for a large number of ion chambers will be introduced in the update of this protocol. Several international groups provided the IAEA with experimental and Monte Carlo based data for this revision. Within the European Community the EURAMET 16NRM03 RTNORM project was initiated for that purpose. In the present study, Monte Carlo based results for the beam quality correction factors in medium energy x-ray beams for six ion chambers applying different Monte Carlo codes are presented. Additionally, the perturbation factor pQ, necessary for the calculation of dose to water from an air kerma calibration coefficient, was determined. The beam quality correction factor kQ,Q0 for the chambers varied in the investigated energy range by about 4%-5%, and for five out of six chambers the data could be fitted by a simple logarithmic function, if the half-value-layer was used as the beam quality specifier. Corresponding data using different Monte Carlo codes for the same ion chamber agreed within 0.5%. For the perturbation factor pQ, the data did not obey a comparable simple relationship with the beam quality specifier. The variation of pQ for all ion chambers was in the range of 3%-4%. Compared to recently published data, our pQ data is around 1% larger, although the same Monte Carlo code has been used. Compared to the latest experimental data, there are even deviations in the range of 2%.