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Multileaf collimator characterization and modeling for a 1.5 T MR-linac using static synchronous and asynchronous sweeping gaps.

Roel G J KierkelsVictor HernandezJordi SaezAgnes AngerudGuido C HilgersKathrin SurmannDanny SchuringAndré W H Minken
Published in: Physics in medicine and biology (2024)
Objective. The Elekta unity MR-linac delivers step-and-shoot intensity modulated radiotherapy plans using a multileaf collimator (MLC) based on the Agility MLC used on conventional Elekta linacs. Currently, details of the physical Unity MLC and the computational model within its treatment planning system (TPS)Monacoare lacking in published literature. Recently, a novel approach to characterize the physical properties of MLCs was introduced using dynamic synchronous and asynchronous sweeping gap (aSG) tests. Our objective was to develop a step-and-shoot version of the dynamic aSG test to characterize the Unity MLC and the computational MLC models in theMonacoandRayStationTPSs. Approach. Dynamic aSG were discretized into a step-and-shoot aSG by investigating the number of segments/sweep and the minimal number of monitor units (MU) per segment. The step-and-shoot aSG tests were compared to the dynamic aSG tests on a conventional linac at a source-to-detector distance of 143.5 cm, mimicking the Unity configuration. the step-and-shoot aSG tests were used to characterize the Unity MLC through measurements and dose calculations in both TPSs. Main results. The step-and-shoot aSGs tests with 100 segments and 5 MU/segment gave results very similar to the dynamic aSG experiments. The effective tongue-and-groove width of the Unity gradually increased up to 1.4 cm from the leaf tip end. The MLC models inRayStationandMonacoagreed with experimental data within 2.0% and 10%, respectively. The largest discrepancies inMonacowere found for aSG tests with >10 mm leaf interdigitation, which are non-typical for clinical plans. Significance. The step-and-shoot aSG tests accurately characterize the MLC in step-and-shoot delivery mode. The MLC model inRayStation2023B accurately describes the tongue-and-groove and leaf tip effects whereasMonacooverestimates the tongue-and-groove shadowing further away from the leaf tip end.
Keyphrases
  • physical activity
  • systematic review
  • mental health
  • randomized controlled trial
  • early stage
  • magnetic resonance imaging
  • artificial intelligence
  • deep learning