Improvement of target and critical structure doses in Corvus IMRT treatment plans

Anil Sethi, Leonid Leybovich, Nesrin Dogan, Matthew Krasin, Bahman Emami

Research output: Contribution to journalArticle

Abstract

The NOMOS MIMIC unit delivers radiation in a tomographic fashion, one arc at a time. Each arc radiates two slices. The slice thickness is determined by the beamlet width: 0.85 cm in the 1cm MIMIC mode and 1.7 cm in the 2 cm mode. The resolution of beam intensity modulation in the direction of couch motion is defined by the beamlet width. A systematic study of targets of various lengths showed that the dose coverage is a cyclical function of target length. The target dose heterogeneity index (h=Dmax./Dmin.) periodically varied from 1.1 to 1.3 as target length was increased. The period of this function was approximately equal to the beamlet width. Corvus positions treatment arcs symmetrically with respect to the target length. Thus for certain length targets, the ends of target may fall in the beamlet penumbra region thereby reducing target minimum dose. In addition, when a critical structure is located adjacent to a target, the same beamlet bank may irradiate both target and critical structure. This leads to an overdosing of the critical structure and an underdosing of the target. However, small modifications in the target representation (a slight increase in PTV or the addition of a distant pseudo target) can be made to cause a shift in arc positions. When the treatment arcs are shifted such that the target is positioned outside the penumbra region and no beamlet bank radiates both target and critical structure, a better target dose distribution and sparing of critical structure is achieved.

Original languageEnglish (US)
Pages (from-to)1549-1552
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume2
DOIs
StatePublished - Jan 1 2000
Externally publishedYes

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Keywords

  • Dose optimization
  • IMRT
  • Tomotherapy

ASJC Scopus subject areas

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

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