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

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.

Improving the modelling of a multi-leaf collimator with tilted leaf sides used in radiotherapy.

Background And Purpose: Multi-leaf collimators (MLCs) with tilted leaf sides have a complex transmission behaviour that is not easily matched by radiotherapy treatment planning systems (TPSs). We sought to develop an MLC model that can accurately match test fields and clinically relevant plans at different centres.

Materials And Methods: Two new MLC models were developed and evaluated within a research version of a commercial TPS.

Challenges in modeling the Agility multileaf collimator in treatment planning systems and current needs for improvement.

Background: The Agility multileaf collimator (MLC) mounted in Elekta linear accelerators features some unique design characteristics, such as large leaf thickness, eccentric curvature at the leaf tip, and defocused leaf sides ('tilting'). These characteristics offer several advantages but modeling them in treatment planning systems (TPSs) is challenging.

Purpose: The goals of this study were to investigate the challenges faced when modeling the Agility in two commercial TPSs (Monaco and RayStation) and to explore how the implemented MLC models could be improved in the future.

Maintaining dosimetric quality when switching to a Monte Carlo dose engine for head and neck volumetric-modulated arc therapy planning.

Head and neck cancers present challenges in radiation treatment planning due to the large number of critical structures near the target(s) and highly heterogeneous tissue composition. While Monte Carlo (MC) dose calculations currently offer the most accurate approximation of dose deposition in tissue, the switch to MC presents challenges in preserving the parameters of care. The differences in dose-to-tissue were widely discussed in the literature, but mostly in the context of recalculating the existing plans rather than reoptimizing with the MC dose engine.

Dosimetric leaf gap and leaf trailing effect in a double-stacked multileaf collimator.

Purpose: To investigate (i) the dosimetric leaf gap (DLG) and the effect of the "trailing distance" between leaves from different multileaf collimator (MLC) layers in Halcyon systems and (ii) the ability of the currently available treatment planning systems (TPSs) to approximate this effect.

Methods: DICOM plans with transmission beams and sweeping gap tests were created in Python for measuring the DLG for each MLC layer independently and for both layers combined. In clinical Halcyon plans both MLC layers are interchangeably used and leaves from different layers are offset, thus forming a trailing pattern.