ESTRO 2023 - Abstract Book

S146

Saturday 13 May

ESTRO 2023

collaboration with the national research institute for mathematics and computer science in the Netherlands (CWI) and the Amsterdam UMC.

SP-0209 Multi-criteria optimisation in brachytherapy: Generation and selection of optimal plans L. Beaulieu 1 , C. Bélanger 1 , P. Chatigny 1 1 Université Laval, Physics, Quebec, Canada

Abstract Text The current state-of-the-art multicriteria optimization (MCO) algorithms promise significantly better brachytherapy dosimetric treatment plans for complex multi-catheter configurations relative to either manual planning or commercially available inverse planning [1]. They do so by providing the end-users with hundreds if not thousands of Pareto optimal plans, exploring various compromises between all of the clinical objectives in seconds. This approach is highly efficient timewise and allows the brachytherapy team to concentrate on selecting the plan(s) that meet all the required quantitative (dose metrics) and more qualitative (isodose shapes, …) planning objectives of the treating physician. In this talk, we will review the strategies for plan optimization and extracting the Pareto front as implemented in brachytherapy. The change in planning paradigm that is enabled by MCO will be explored. Various implementation of MCO will be discussed and multi-catheter prostate HDR brachytherapy will served as a test case. Since a very large number of plans are generated, options pertaining to plan navigation and plan selection will be touch upon. A sneak peek into the latest application of this approach to more complex cases such a GYN interstitial brachytherapy with applicators offering numerous combinatorial options (namely parallel applicator needles, angulated applicator needles and template interstitial needles in addition to the standard applicator channels) will illustrate how the MCO approach could be integrated in the clinical setting as a fast pre-planning or inter-fraction planning tool. [1] Beaulieu L, Al-Hallaq H, Rosen BS, Carlson DJ. Multicriteria Optimization in Brachytherapy. Int J Radiat Oncol Biology Phys. 2022;114(2):177-180. SP-0210 Challenges and opportunities with the introduction of automated treatment planning D. Barten 1 1 Amsterdam University Medical Centers, University of Amsterdam, Department of Radiation Oncology, Amsterdam, The Netherlands Abstract Text Automated treatment planning is not a new phenomenon in brachytherapy. It helps to calculate individual patient plans in order to maximize tumor control and minimize toxicity. Recent publications show that automated planning is finally turning from a research niche to real clinical practice. Various research has shown that automated algorithms can calculated better plans, in terms of tumor coverage and sparing of healthy tissue, in a shorter time frame. Retrospective evaluation studies have shown their value for the acceptance of plans obtained by an automated algorithm, and the transition to clinical practise could be made. However, the idea prevails that automated planning, including artificial intelligence algorithms, are challenging to implement in clinical practice and might met resistance. In March 2020, we clinically introduced ‘BRachytherapy via artificially Intelligent GOMEA-Heuristic based Treatment planning’ (BRIGHT) for prostate cancer patients in our institution. Last two years we gained clinical experience and learned that when automated treatment planning is used in clinical practice new challenges arise. In example, the physician makes use of patient-specific information, experience and general knowledge that was not, or cannot be, captured by dose-volume criteria implemented in the new algorithm. The result was that the automated plans were manually fine-tuned when deemed necessary, which reduced the time savings. Furthermore, staffing, training and integration in an commercial treatment planning system appeared of greater influence on the performance than expected. Based on our experience, additional optimization aims need to be implemented to further improve direct clinical applicability of treatment plans and process efficiency. The evaluation of plan selection criteria and reasons for manual fine-tuning taught us which additional criteria are deemed of importance, such as dose-volume aims for gross-tumour volume, contiguous high-dose sub-volumes (“hotspots”), and high-dose regions in close proximity to organs at risk. One of the most important differences with respect to manual planning was that there is a shift in the use of time. With BRIGHT, or other types of automated treatment planning algorithms, time can be spent on carefully choosing the desired plan, instead of adjusting one plan iteratively without having any indication one has actually arrived at the best possible plan for that specific patient and what alternatives are. The main focus of this talk will be on the challenges of introducing automated planning and practical examples of our first experiences in the clinic. Additionally will be addressed how one can overcome these challenges and what role the RTT, doctors and medical physicists play in turning the challenges into opportunities.

Symposium: Patient preparation and positioning

SP-0211 Research on an upright positioning system for radiotherapy S. Boisbouvier 1 , A. Boucaud 1 , V. Grégoire 1 1 Léon Bérard Centre, Radiotherapy, Lyon, France

Abstract Text Although human beings spend most of their time sitting and standing, radiation therapy treatments are still delivered in supine position. Despite several publications that indicate patient set-up in upright position could be beneficial for their treatment. In this context, a research program on an upright positioning system (the so-called “Chair” developed by the Leo Cancer Care (figure 1)), was initiated. It included three steps: -patient workflow and immobilization devices development,