ESTRO 2022 - Abstract Book

S828

Abstract book

ESTRO 2022

Materials and Methods We have developed a mathematical model using MATLAB which enables the formulation of tissue-equivalent materials considering physical properties, photon interactions but also proton stopping power, absorption, and scattering interactions. Using a non-linear optimisation algorithm, this work has formulated new bone- and muscle-equivalent epoxy resin-based materials in terms of their photon and proton interaction parameters. However, perfectly matching all interactions is challenging, therefore, a weighted cost function was defined according to the relative importance of each photon and proton interaction. Mass density, mass attenuation and relative stopping power (RSP) were assigned the highest weightings due to their impact on the materials ability to be correctly characterised during the imaging and treatment planning process (TPS) as well as providing accurate proton dosimetry measurements. The formulated materials have been manufactured and characterised via the use of single-and dual-energy CT as well as proton water-equivalent thickness measurements at The National Physical Laboratory (UK) and University College London Hospital. Monte Carlo simulations (FLUKA) were completed to calculate the fluence correction factors of the materials, which provides a more detailed understanding of nuclear interaction equivalence of the material. Each material’s RSP was also compared to the clinical TPS assigned RSP using the HU-RSP calibration curve to check their use for end-to-end audit purposes. Results Table 1 show that the new optimised materials score better than current commercial phantom materials when considering all-important physical properties, photon interactions, proton stopping power, absorption, and scattering interactions.

Experimental results suggest the new bone and muscle formulations adequately mimic target tissue parameters such as the mass density and RSP with acceptable differences of 1-3%. Conclusion Results suggest that the proposed bone and muscle formulations can be used for the development of future photon and proton-optimised dosimetric phantoms. This work highlights the potential of this new mathematical model as a tool in the creation of phantoms with optimised tissue materials for photon and proton beams.

OC-0938 MLC complexity metrics in clinical online adapted IMRT plans delivered with a double-stacked MLC

P. Sibolt 1 , N.C. Momsen 1 , L.M. Åström 1,2 , U. Bjelkengren 1 , D. Sjöström 1 , C.P. Behrens 1

1 Copenhagen University Hospital - Herlev and Gentofte, Dept of Oncology, Copenhagen, Denmark; 2 Technical University of Denmark, Dept of Health Technology, Roskilde, Denmark Purpose or Objective Complexity of intensity-modulated radiotherapy (IMRT) plans depends on e.g. the applied optimization procedure, and a high degree of multi-leaf collimator (MLC) modulation is known to challenge the accuracy in both dose calculation and treatment delivery. In automated treatment planning for online adaptive radiotherapy (oART) plan quality evaluation relies on calculation-based approaches, and the use of MLC complexity metrics could act as a valuable supplement to independent dose calculations. This study aimed at evaluating two different MLC complexity metrics in comparison with the more commonly used MU/Gy for clinically generated oART plans on a linear accelerator with a double-stacked MLC. Materials and Methods A total of 57 clinical IMRT plans for seven patients treated for urinary bladder cancer were exported from Ethos (Varian Medical Systems); a CBCT-based and artificial intelligence-driven oART platform with a double-stacked MLC. The MLC complexity metrics, edge penalty [1] and one minus the modulation complexity score (1-MCS) [2], were calculated from the control points in the DICOM files, and information on the MU/Gy was collected for each plan. Phantom-based measurements were carried out using the Delta4+ phantom (Scandidos) on the corresponding plans and the resulting gamma passing rates (3%/2mm, local, 20% cut-off) were compared to the complexity scores. The correlations between the gamma passing rates and the various metrics were evaluated.