ESTRO 36 Abstract Book

S806 ESTRO 36 2017 _______________________________________________________________________________________________

technique.

EP-1522 Quantifying the operator variability reduction driven by knowledge-based planning in VMAT treatments A. Scaggion 1 , M. Fusella 1 , S. Bacco 1 , N. Pivato 1 , A. Roggio 1 , M. Rossato 1 , R. Zandonà 1 , M. Paiusco 1 1 Istituto Oncologico Veneto IOV-IRCCS, Medical Physics, Padova, Italy Purpose or Objective The purpose of this study is to evaluate the potential of a commercial knowledge-based planning (KBP) algorithm to standardize and improve the quality of the radiotherapy treatment. This study evaluates if the predicted DVH constraints generated by the KBP algorithm can reduce the inter-operator variability thus providing a better standard of quality. Material and Methods Using Varian RapidPlan two models were created for oropharynx and prostate VMAT treatments with respectively 73 and 90 previously treated patients. Five oropharynx and six prostate test patients, not included in the training database, were anonymized and randomized. Four operators, with different planning expertise, were asked to manually obtain a clinical VMAT plan (mVMAT) for each test patient. Subsequently, each operator replied the planning procedure assisted by RapidPlan DVH predictions obtaining a second VMAT plan (rpVMAT). The potential of RapidPlan to reduce the inter-operator variability was evaluated comparing rpVMAT with mVMAT plans in terms of OAR sparing, target coverage and conformity. Results In the case of prostate treatments mVMAT and rpVMAT plans resulted in similar target coverage while a net reduction in OAR sparing variability was seen for rpVMAT plans (a visual example is given in Figure). For the case in figure, rectum V40Gy resulted 34.4±18.1% for mVMAT and 32.1±7.6% for rpVMAT. In general, a 40% reduction in inter- planner OAR sparing variability has been registered when planning was assisted by RapidPlan predictions.

Conclusion The novel target volume splitting technique offers an efficacious new approach to VMAT optimization, producing high dose gradients in the vicinity of the spinal cord and allowing prioritization of spinal cord sparing. EP-1521 Non-coplanar beam orientation and fluence map optimization based on group sparsity K. Sheng 1 1 David Geffen School of Medicine at UCLA, Radiation Oncology, Los Angeles- CA, USA Purpose or Objective With the increasing availability of non-coplanar radiotherapy systems in clinical set-tings, it is essential to develop effective and efficient algorithms for integrated non-coplanar beam orientation and fluence map optimization. To achieve this goal, we investigate the novel group sparsity approach for non-coplanar beam orientation optimization. Material and Methods The beam orientation and fluence map optimization problem is formulated as a large scale convex fluence map optimization problem with an additional group sparsity term that encourages most candidate beams to be inactive. The optimization problem is solved using an accelerated proximal gradient method, the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA).We derive a closed-form expression for a relevant proximal operator which enables the application of FISTA. The beam orientation and fluence map optimization algorithm is used to create non-coplanar treatment plans for six cases (including two head and neck, two lung, and two prostatecases) involving 500 - 800 candidate beams. The resulting treatment plans are compared with 4treatment plans created using a column generation algorithm, whose beam orientation and fluence map optimization steps are interleaved rather than integrated. Results In our experiments the treatment plans created using the group sparsity method meet or exceed the dosimetric quality of plans created using the column generation algorithm, which was shown superior to that of clinical plans (Figure shows a head and neck case). Moreover, the group sparsity approach converges in about 5 minutes in these cases, as compared with runtimes of more than an hour for the column generation method. Table shows the PTV dose statistics and runtime comparison. Conclusion This work demonstrates that the group sparsity approach to beam orientation optimization, when combined with an accelerated proximal gradient method such as FISTA, works effectively for non-coplanar cases with a large number of candidate beams.In this paper we obtain an orders of magnitude improvement in runtime for the \group sparsity"approach to beam orientation optimization by using an accelerated proximal gradient method to solve the ℓ2;1-norm penalized problem. Furthermore, the dosimetric quality of our group sparsity plans meets or exceeds the quality of treatment plans created using a column generation approach to beam angle selection, which has been demonstrated in recent literature to create high quality treatment plans.

For oropharynx treatments RapidPlan-assisted planning leads to more homogeneous target dose distributions, especially for the low-dose target. The low-dose PTV standard deviation obtained in rpVMAT plans was 2.6±0.6% while it resulted 3.2±1.5% for mVMAT ones. A variability reduction of the order of 10% was also seen in parotids, oral cavity and larynx sparing. For the less experienced planner RapidPlan assistance also induced an overall decrease of OAR mean doses by approximately 15%. Using RapidPlan assistance the overall inter-planner variability is reduced in every single patient and a general improvement of plans statistics is achieved. Conclusion The use of RapidPlan predictions in VMAT planning driven a homogenization of the planning outcome both in prostate and oropharynx treatment for a group of 4 planners. OAR sparing variability can be reduced as much as 40% maintaining similar target coverage when RapidPlan is employed. This study provide a quantitative measure of the RapidPlan potential as an instrument to improve plan quality. This findings states that the use of a knowledge based planning system allow for safer treatments.