Dosimetric implication of multileaf collimator leaves for abutting, half beam blocking and intensity modulation

Indra J. Das, Alireza Kassaee, Raj K. Mitra, David I. Rosenthal

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Dosimetry related to inter and intra-leaf leakage has been reported for every type of multileaf collimator (MLC), however, dosimetry at the abutting MLC leaves that are frequent in intensity modulated radiation therapy (IMRT) as well as for half beam blocked fields in conjunction with dynamic and virtual wedges has not been reported. In this study, dosimetric significance of MLC leaves for abutting and half beam blocked field is evaluated for the curved and focused MLCs (Varian and Siemens) at leaves position of 0, ±0.1, ±0.2, ±0.3, ±0.5, ±1.0, ±5 and ±10 cm in 0° and 90° gantry angle using CEA film. Films were exposed by blocking one side of the MLC leaves and second exposure with blocking the other half. Films were scanned using laser film densitometer. Results show that Varian MLC produces significant hot spot (40%) in a star pattern due to curved leaves design and depends strongly on the gantry position. The 90° gantry position provides relatively uniform dose probably due to sagging of the leaves. The Siemens MLC provides random cold and hot spots in the range of ±20% independent of the gantry angle. The width of the abutting hot and cold spots is <2 mm for both MLCs. It is concluded that the dosimetric differences between rounded and focus beam edge is significant and of clinical importance in IMRT. The MLC leaves position should be precise and calibrated redundantly to minimize the cold and hot spots in an abutting and half beam blocked fields.

Original languageEnglish (US)
Pages (from-to)2202-2204
Number of pages3
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume3
DOIs
StatePublished - Jan 1 2000

Keywords

  • Abutting fields
  • IMRT
  • MLC

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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