ESTRO 36 Abstract Book

S827 ESTRO 36 _______________________________________________________________________________________________

Material and Methods A total of 276 RapidArc plans optimized with Eclipse v13 were exported in DICOM format for this study comprising all locations (HN, prostate, gyne, brain, other). The cumulative histogram of leaf gaps for all plans is shown in figure 1. A set of MATLAB routines was developed to perform the analysis. The following parameters were computed: Total Modulation Index (MIt) (Park et, al), Modulation Complexity Score (MCS) (McNiven et. al), Beam Irregularity (BI) (Du et. al), mean gap, median gap and MU/Gy. All these parameters were evaluated as predictors of the fraction of small gaps, in particular fraction of gaps smaller than 20, 10 and 5 mm.

poorer to published ones for the rest of OAR, this may be due to the fact that the majority of our cases with 36 Gy were children which are precisely the more complex cases to optimize.

Results There was a very large variability in the distribution of MLC gaps involved in VMAT plans. A strong exponential relationship between the median gap and the fraction of gaps smaller than 5, 10 and 20 mm was observed (r 2 =0.8, 0.92 and 0.95) (see figure 2). A similar but weaker relationship was observed for the mean gap (r 2 =0.74, 0.87 and 0.94), the MCS (r 2 =0.55, 0.58 and 0.54) and MU/Gy (r 2 =0.21, 0.26 and 0.25). Neither the MIt nor the BI presented a relationship with any of the gap fractions studied. For median gaps > 30mm, the fraction of gaps lower than 5, 10 and 20 mm was estimated as 0.13 ± 0.07, 0.20 ± 0.06 and 0.36 ± 0.07, respectively. On the contrary, for median gaps ~10mm, the fraction of gaps lower than 5, 10 and 20 mm was estimated as high as 0.33 ± 0.07, 0.50 ± 0.06 and 0.72 ± 0.07, respectively.

Dosimetric parameters dependent on D prescr

are presented

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Table 1.

Conclusion A RapidArc planning process for craniospinal axis irradiation has been implemented with significant improvement on conformity, homogeneity, feasibility and efficiency. EP-1539 Parameters for estimating and controlling small gaps in VMAT treatments J. Saez Beltran 1 , V. Hernandez Masgrau 2 1 Hospital Clinic i Provincial, Radiation Oncology Department, Barcelona, Spain 2 Hospital Sant Joan de Reus, Medical Physics Department, Reus, Spain Purpose or Objective It is well established that dose modelling and calculation of small fields and small MLC gaps is challenging. Indeed, VMAT plans with a large fraction of small MLC gaps are prone to present dosimetric discrepancies due to limitation of the TPS and uncertainties in treatment delivery. On the other hand, there is a growing interest in developing tools to characterize robust class solutions for plans. Our goal was to study leaf gap distributions in terms of descriptive variables and complexity indices.

Conclusion In general, plan complexity indices exhibit a weak correlation with the fraction of small gaps in VMAT plans. Similarly, setting limits on the number of MUs, or MU/Gy has no clear impact on the fraction of small gaps generated during the optimization process. A good prediction of the fraction of small gaps can be obtained from the median gap of the plan. Thus, tolerance levels for the fraction of small gaps can be defined in terms of the median gap of the plan, which can be useful to generate more robust VMAT plans.