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Updated: Dec 31, 2025

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
Published on: April 11, 2018
Inter-unit variability of multi-leaf collimator parameters for IMRT and VMAT treatment planning: a
Masaru Isono1, Yuichi Akino2, Hirokazu Mizuno3
1Department of Radiation Oncology, Osaka International Cancer Institute, 3-1-69 Otemae, Chuo-ku, Osaka-shi, Osaka 541-8567, Japan.
Abstract:
Modern treatment machines have shown small inter-unit variability regarding beam data. Recently, vendor-provided average beam data, such as the Representative Beam Data (RBD) of the TrueBeam (Varian Medical Systems, Palo Alto, CA, USA), has been used for modeling of the Eclipse (Varian Medical Systems) treatment planning system. However, RBD does not provide multi-leaf collimator (MLC) parameters, such as MLC leaf transmission factor (LTF) and dosimetric leaf gap (DLG). We performed a web-based multi-institutional survey to investigate these parameters as well as the measurement protocols and customization of the parameters for intensity-modulated radiotherapy (IMRT) and/or volumetric modulated radiotherapy (VMAT) commissioning. We collected 69 sets of linear accelerator (linac) data from 58 institutions. In order to measure MLC parameters, most institutions used farmer-type ionization chambers with a sensitive volume of 0.6 cm3, water phantoms, source surface distance of 90 cm with 10 cm depth, and a vendor-provided plan. The LTF showed small inter-unit variabilities, although the DLG showed large variations. For optimization of the parameters for IMRT/VMAT calculations, DLG values were upwardly adjusted at many institutions, whereas the LTF values were modestly changed. We clarified that MLC parameters were measured under the same conditions at more than half of the facilities. Most institutions customized parameters in a similar manner for IMRT/VMAT. The median measured and customized values obtained in our study will be valuable to verify MLC installation accuracy and to shorten the iterative processes of finding the optimal values.
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