ESTRO 37 Abstract book

S1030

ESTRO 37

EP-1898 Smooth animations of the probabilistic analog to worst-case dose distributions N. Wahl 1,2,3 , H.P. Wieser 1,2,4 , L.R. Müller 1,2,3 , P. Hennig 5 , M. Bangert 1,2 1 German Cancer Research Center DKFZ, Medical Physics in Radiation Oncology, Heidelberg, Germany 2 Heidelberg Institute of Radiation Oncology, HIRO, Heidelberg, Germany 3 University of Heidelberg, Department of physics and astronomy, Heidelberg, Germany 4 University of Heidelberg, Medical Faculty, Heidelberg, Germany Purpose or Objective Clinical robustness analysis is rare and usually limited to the re-computation of the treatment plan considering discrete worst case scenarios. To stay within feasible computation times, this analysis has to be based on comparably few random or importance samples, which might not reveal the true variability in dose within a continuous space of possible treatment scenarios. Here, we present an approximate method to generate continuous animations of a dose distribution confidence boundary based on few samples. The resulting visualizations can be interpreted as smooth probabilistic analog to discrete worst case dose distributions. Material and Methods We suggest to approximate the probability distribution over dose by a multivariate Normal distribution whose mean and covariance can be estimated by sampling or analytical methods. Modelling uncertainties in this context with Gaussian densities may not be fully accurate but it is a widely accepted and mathematically convenient practice in radiation therapy. First, it allows that a subset of voxels, i.e. a dose slice or a volume of interest, can be represented by a computationally tractable marginal multivariate Normal distribution. Second, samples can be drawn from this multivariate Normal via a linear transformation of a standard multivariate Normal sample using the mean dose and the Cholesky-decomposition of the covariance matrix. This sampling process can be adapted to explore a continuous subspace of the sample space. To do so, we extend an existing method developed for Gaussian process animations. This method parametrizes a hyper- sphere on the standard multivariate Normal by a randomly chosen radius r , and then "walks" on an orthodrome on this hyper-sphere to generate a set of equiprobable coordinates that can be back-projected, evaluated and displayed one after each other to obtain consecutive and "smooth" samples of the original multivariate Normal. The radius r may also be chosen according to a distinct meaning, e.g. from the quantile function of the χ²-distribution yielding confidence surfaces or by a selected start coordinate. Results We generated a set of visualizations for a carbon plan on the liver case and a proton plan on the prostate case from the open source CORT dataset. 54 importance samples based on combinations of a 2% and 3% range error and 2mm and 3mm setup error where used for the liver and the prostate case, respectively. Since the additional dimension time is needed to present the results, i.e. smooth animations, two animated GIFs showing samples on the 50% confidence ellipsoid (corresponding to ±0.68σ sigma in a single dimension) are provided at https://github.com/becker89/ESTRO2018. Conclusion We present a method that allows to illustrate the structure of the uncertainties present in a treatment plan based on a continuous animation of equiprobable scenarios. Our technique provides a probabilistic analog 5 Max Planck Institute for Intelligent Systems, Probabilistic Numerics, Tübingen, Germany

to worst case dose distributions and may inform practical robustness analysis.

Electronic Poster: Physics track: Treatment planning: applications

EP-1899 HyperArc^TM: a new mono-isocenter VMAT technique for SRS of multiple brain lesions. R. Ruggieri 1 , S. Naccarato 1 , A. Fiorentino 1 , F. Ricchetti 1 , R. Mazzola 1 , F. Alongi 1 1 Sacro Cuore Don Calabria Hospital, Radiation Oncology, Negrar, Italy Purpose or Objective Linac based VMAT-SRS of multiple brain lesions is typically performed by a multiple-isocenters approach, i.e. one isocenter per lesion, which is time-demanding for the need of independent setup verifications of each isocenter. Here we present the first worldwide experience with a new mono-isocenter technique with multiple non-coplanar arcs (HyperArc TM , Varian Inc.) in terms of a plan comparison with our previous multiple- isocenters VMAT approach. Material and Methods From August 2017, 13 patients have been treated by HyperArc TM for multiple (mean 5, range 2-21) brain lesions (PTV(cc): mean 10.8, range 0.5-42.2) in 1-3 fractions: the prescribed doses (D p ) were 18-25 Gy for single-fraction, and 21-27 Gy for three-fractions SRS, respectively. By HyperArc TM , an add-on of Eclipse TM (v.15.5, Varian Inc.), we generated mono-isocenter VMAT plans (HA) with 5 non-coplanar 180°-arcs (couch at 0°, ±45°, ±90°). Multiple-isocenters VMAT plans (RA) with 2 coplanar 360°-arcs per isocenter were also planned by Eclipse TM (v.15.5, Varian Inc.). A dose normalization of 100%D p at 98%PTV was adopted, where a 2 mm isotropic margin from the union of all lesions gave PTV, while D 2% (PTV)<150%D p was accepted. All plans respected the constraints on maximum dose, D(0.5cc), to the brainstem (18 Gy), and to chiasm, optical nerves, eyes and lens (15 Gy). By hypothesis testing, HA and RA plans were then compared in terms of dose-volume metrics, by Paddick conformity (CI) and gradient (GI) index and by V 12 and mean dose to the brain-minus-PTV, and in terms of MU (MU/fr.) and total treatment time (T) per fraction. Whereas measured for HA treatments, for RA plans T(min.) was estimated by assuming 3 min. for initial patient setup plus 5 min. per each CBCT-guided setup correction per isocenter. Results As detailed in Table 1, significant variations in favour of HA plans were computed for both target dose indexes, CI and GI. The lower GI in HA plans was the likely cause of the significant reduction in V 12 to the brain-minus-PTV. At low doses, below 2-3 Gy, the sparing of the brain-minus- PTV was instead in favour of RA plans: on the whole, no significant difference between the mean doses to the brain-minus-PTV of the two groups of plans resulted. Finally, both MU and T were significantly reduced by HyperArc TM plans. Conclusion HyperArc TM plans assured a higher CI together with a lower GI than the RA plans. This is consistent with the computed reduction in V 12 to the brain-minus-PTV, i.e. the shell of surrounding healthy-brain exposed to medium-to-high doses which is typically correlated with the incidence of side effects. Finally, for all our patients HyperArc TM treatments were completed within a typical 20 min. time slot, even for a case with 21 lesions.