ESTRO 36 Abstract Book

S816 ESTRO 36 2017 _______________________________________________________________________________________________

2 Hospital Sant Joan de Reus, Medical Physics Department, Reus, Spain

maximum dose to OAR located inside the brain PTV were set to avoid hot spots. After that, the rest of the optimization was carried out using the automatic “Intermediate Dose Calculation” option. Various dosimetric parameters and indices were employed: PTV mean dose; D 1cc , D2% and D98%; mean and maximum doses for OAR; V5 and V20 for lungs; conformity (CI=Vol 95% /Vol PTV ) and homogeneity (HI=D 1cc /D prescr ) indices; Normal Tissue mean and V5 dose. Results We found avg. values for CI, 1.02 (0.98-1.09) and for HI, 1.08 (1.05-1.10) regardless of D prescr . OAR mean dose values along with average values reported by different authors are shown in Fig. 1. A great reduction is observed for almost all OAR for 23.4 Gy, while for 36 Gy our results are favorable for eyes and lenses and similar or slightly 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.

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. 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.

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

in

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