Gamma Analysis Distance To Agreement

The distance between two dose distributions or dose surfaces is a direct, pixel-based measure of the difference between two dose surfaces, which does not require predefined parameters. Because this distance is a clearly defined physical quantity, it can be used as a metric to assess the performance of the γ index once the ratio of distance to the γ index and a basic assessment system is established. Conclusions: Surface distance is a direct measure of the difference between two dose distributions and can be used to assess or determine the parameters of the γ index. The dose gradient factor represents the weighting between spatial shift and dose shift and must be determined before defining the DTA/DD criteria. The authors also present a method for determining γ index parameters from measurements. We can continue to generalize the concept of distance to the distribution of the 3D dose, because the distribution of the dose can also be considered as a surface. For two distributions of 3D D1 and D2 doses (standardized doses are always used, unless otherwise stated), the difference between one point to D1 (dose of D1 (x1, y1, z1) is from one point to D2: there are three sources of uncertainty (difference) in the phantom structure when comparing the dose distribution between the treatment system and the actual measurements; (2) uncertainty (quantum noise) in the dosimetry system (for example. B film in our study); and (3) uncertainty due to discrepancies between the photon beam modeled in the processing system and the photon beam delivered. The uncertainty of adjustment at the x-y level results in spatial shift (global) and the uncertainty of adjustment in the Z direction results in a dose difference (global), the level provided by the treatment system being different from the measurement plan. The quantum noise of the dosimetria system can be considered a random shift of the dose axis and therefore has a global effect. As noted in Low and Dempsey3 and presented in table TABLEAU II, the measured amounts (z.B average marginal distance and D90) are changed at low noise levels (2%) this is not essential, but if the sound level is high enough, for example. B 5%, if only 68% of pixels should fall into the ±5%, even without spatial or dose displacement.

In the latter case, certain quantities (for example. B D99) are no longer suitable for evaluation. The uncertainty of primary interest in imRT quality assurance could be both global (changes in speed/symmetry/exit) and local (MLC/pin) and the change could be in both space (pines/MLC) and dose axles (flat/symmetry/output-change). The uncertainty of the installation and the noise of the dosimetrie system26 should, as far as possible, be inferred from the measured overall uncertainty and the inadequacy of the model could then be grouped with other delivery uncertainties. B for example configuration uncertainties, and the use of processing margins. Figure 44 shows the process of simulating patient plans. Space movements (d-0-10 mm in 0.5 mm increments) and dose movements (D – 0% to 10% in increments of 0.5%), as shown in Figure 3a3a (only 10 mm samples were shown) were applied to the 10 planar distributions provided in the TRT. The overall changes were applied because the layers were well controlled. Among errors of the same order of magnitude, global changes are the worst possible errors in terms of impact on dose distribution, but the simplest errors to detect.

This is why global changes are well suited to the most pessimistic/best-case scenario analysis. The surface distance distributions between the initial plan and the staggered planes were then calculated. For each initial dose distribution, 440 shifted dose distributions were generated and, for each staggered dose distribution, the average and median distances were calculated, as were the 85th (D85), 90(D90), 95 (D95) and 99th (D99) percentiles of the dose distribution.