Dosimetric evaluation of UMW electron wedges

X. Wu, Z. P. Chen, C. Luo, M. L. Watzich, R. Larsen, H. Shao, A. H. Wolfson, A. M. Markoe

Research output: Contribution to journalConference article

Abstract

A dosimetric evaluation was performed for a set of UMW electron wedges, developed at the University of Miami and manufactured by MED-TEC, Inc., on a Varian CL-2100 CD accelerator. These electron wedges were designed to generate wedged electron beam profiles with virtually no degradation of beam energy. For electron beams ranging from 6 to 18 MeV, depth doses and beam profiles were acquired at various depths including the photon contamination region using a Wellhofer water tank with a 0.14 cc ion chamber. The analysis showed that the changes in beam energy in the wedge filtering process were insignificant (on the order of 0.1 MeV). A maximum of 1.5% increase in x-ray dose was found. Based on the fact that the wedge effect does not introduce significant energy variations across the wedged direction, the Hogstrom electron pencil beam algorithm was used for dose computation with the electron fluence tuned in both wedged and un-wedged directions using scanned profiles at the depth of 0.5R90. Examples of improved dose distribution in oblique beam setup applying these electron wedges are demonstrated. The results show the abilities of these UMW electron wedges in achieving better dose distributions when curved surfaces, oblique beam entries and variable target depths are encountered in electron beam radiotherapy.

Original languageEnglish (US)
Pages (from-to)2924-2927
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume4
StatePublished - Dec 1 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 beams
  • Electron wedge
  • Radiotherapy

ASJC Scopus subject areas

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

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