OBJECTIVE: To investigate the statistical distribution of the gamma value under error-free conditions, in order to study the relation between the gamma evaluation failure rate and statistically significant deviations in the general situation.
METHODS: The 2D absorbed dose distribution for 30 clinical head-and-neck IMRT fields were calculated in a QC phantom. For the same fields, dose measurements were simulated by assuming that the calculated value represented the expectation value, and by adding a random spatial uncertainty of 1-9 mm (1SD) and a random dose uncertainty of 1%-3% (1SD). The simulated measurements were then compared to the calculated dose using the gamma evaluation, and the distribution of the failure rate (i.e. the probability of gamma values above unity) was analysed.
RESULTS: For a wide range of the random measurement uncertainty, a distinct peak in the failure rate distribution was observed. The presence of higher failure rates was associated with large values of the second order derivative of the dose distribution. For spatial uncertainties larger than or equal to the resolution of the dose matrix, and for reasonable dose uncertainties, the median value of the failure rate distribution was fairly constant.
CONCLUSIONS: Simulations showed, in the general case, that the probability of having a gamma value above unity under error-free conditions was not spatially uniform. We believe that this shortcoming may be partly responsible for the limited ability of the gamma evaluation method to detect errors in clinically relevant situations.

Quality assurance (QA) for clinical trials is important. Lack of compliance can affect trial outcome. Clinical trial QA groups have different methods of dose distribution verification and analysis, all with the ultimate aim of ensuring trial compliance. The aim of this study was to gain a better understanding of different processes to inform future dosimetry audit reciprocity.
Six clinical trial QA groups participated. Intensity modulated treatment plans were generated for three different cases. A range of 17 virtual \'measurements\' were generated by introducing a variety of simulated perturbations (such as MLC position deviations, dose differences, gantry rotation errors, Gaussian noise) to three different treatment plan cases. Participants were blinded to the \'measured\' data details. Each group analysed the datasets using their own gamma index (γ) technique and using standardised parameters for passing criteria, lower dose threshold, γ normalisation and global γ.
For the same virtual \'measured\' datasets, different results were observed using local techniques. For the standardised γ, differences in the percentage of points passing with γ < 1 were also found, however these differences were less pronounced than for each clinical trial QA group\'s analysis. These variations may be due to different software implementations of γ.
This virtual dosimetry audit has been an informative step in understanding differences in the verification of measured dose distributions between different clinical trial QA groups. This work lays the foundations for audit reciprocity between groups, particularly with more clinical trials being open to international recruitment.