Multileaf collimation for electron intensity modulation

R. J. Kudchadker, K. R. Hogstrom, R. A. Boyd

Research output: Contribution to journalConference articlepeer-review

Abstract

Dynamic multileaf collimation (DMLC) could prove useful in electron conformal therapy, arc electron therapy, and electron field abutment. For these applications, it is first necessary to understand the ability of the DMLC to modulate electron fluence and its effect on the resulting dose distribution. The objectives of this work were to demonstrate the ability of the pencil-beam algorithm to fit the electron dose distribution created by the DMLC and to demonstrate for non-normal incidence on a flat phantom that the DMLC can restore dose uniformity. Measurements were performed using 12 and 20 MeV electrons with the 25 × 25 cm2 applicator. Dose was measured using film placed at a depth of 2 cm in a plastic phantom at 100 cm SSD. First, measurements were made with the MLC set to 10 × 10 cm2 and 20 × 20 cm2. Another irradiation simulated modulation by irradiating with square fields followed by the MLC blocking half the field. These results showed that the pencil beam algorithm can accurately predict the off-axis dose profiles. Second, the beam was angled at 30° from the normal incidence creating a gradient in dose uniformity. Then, the beam was modulated to achieve dose uniformity by gradually closing the leaves from the side closest to the phantom to the side furthest away. These results indicated that the DMLC can restore beam uniformity for cases where there is a low dose gradient.

Original languageEnglish (US)
Pages (from-to)210-213
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume1
StatePublished - 2000
Event22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Chicago, IL, United States
Duration: Jul 23 2000Jul 28 2000

Keywords

  • Electron
  • Intensity
  • Modulation
  • Multileaf collimation

ASJC Scopus subject areas

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

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