Comparison between margin-growing algorithms in radiotherapy software environments

Abstract

Margin-growing algorithms are commonly used tools that are available within virtual simulation and treatment planning software. We report on the accuracy of the margin-growing algorithms available in six commercially available radiotherapy software environments. A phantom containing two differently sized spheres and two rods (one level and one inclined) was constructed and scanned by CT with 1.25 mm, 2.5 mm, 3.75 mm and 5 mm slice thicknesses. The objects were outlined on a GE Advantage Simulator, and the outlined volumes recorded. Images and structures were transferred to MasterPlan, Xio, Pinnacle, Eclipse and Prosoma, where imported volumes were recorded. The contours on each system were grown isotropically by 10 mm, 20 mm and 30 mm, and volumes for each grown contour were recorded. Transfer of structure sets created in GE Advantage Simulator to the other software environments showed that the reported volumes of the four structures differ on each system. Results showed no correlation between volume accuracy and slice thickness. In general, margin growth of up to 30 mm for the rods and spheres is shown to be consistent between systems to within 1.33 mm for all slice thicknesses. Slice thickness did not appear to influence the accuracy of margin growth. Although this work highlights apparent differences in the reported volumes grown from the same original structure sets, the significance of this aspect of the planning process needs to weighed against reported intra- and inter-clinician variability in contour definition. It is not unreasonable, however, to expect that software packages should at least be consistent in volume information provided to the user.

Dependence of volume calculation and margin growth accuracy on treatment planning systems for stereotactic radiosurgery

“…The difference was then compared to the stated margin applied. This is similar to the method used by Smith et al 3 and Wang et al 8 for spherical phantom structures.…”

“…Variation in mean volumes calculated for each TPS is shown in Figure 1 and Table 3. For volumes < 1 cm 3 agreement was within 0.04 cm 3 , and for volumes > 1 cm 3 agreement was within 5%. Average differences were most positive for Pinnacle and VODCA and most negative for GammaPlan and Eclipse, compared to the mean of all TPS.…”

“…Variation in volumes calculated between different centres with the same TPS is shown in Figure 2. For volumes < 1 cm 3 agreement was within 0.05 cm 3 , and for volumes > 1 cm 3 agreement was within 5%.…”

“…1 One factor affecting this is the user's ability to accurately and precisely delineate structures using limited image information; another is the accurate calculation of volumes in 3D based on series of points defined on pixelated 2D image slices. Methods for such calculations differ between treatment planning systems (TPS), with variation of 5-10% reported for both regular geometric shapes [2][3][4] and actual clinical targets. [4][5][6] For the majority of external beam treatments, uniform margins are added to the delineated (gross) target volume (GTV) to account for sub-clinical spread and for uncertainties in delivery, leading to the formation of the planning target volume (PTV).…”

“…Methods for applying these margins also differ between TPS, with variations of about 1 mm compared to expected growth being reported. 3,[6][7][8] Accuracy of volume calculation can in turn affect plan parameters such as dose-volume histograms. 9 For clinical trials' quality assurance, benchmark cases are routinely used to assess variation from protocol in recruiting centres, and ensure consistency of contouring, planning and delivery.…”