Dose-calculation algorithms in the context of inhomogeneity corrections for high energy photon beams

Niko Papanikolaou, Sotirios Stathakis

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

Radiation therapy has witnessed a plethora of innovations and developments in the past 15 years. Since the introduction of computed tomography for treatment planning there has been a steady introduction of new methods to refine treatment delivery. Imaging continues to be an integral part of the planning, but also the delivery, of modern radiotherapy. However, all the efforts of image guided radiotherapy, intensity-modulated planning and delivery, adaptive radiotherapy, and everything else that we pride ourselves in having in the armamentarium can fall short, unless there is an accurate dose-calculation algorithm. The agreement between the calculated and delivered doses is of great significance in radiation therapy since the accuracy of the absorbed dose as prescribed determines the clinical outcome. Dose-calculation algorithms have evolved greatly over the years in an effort to be more inclusive of the effects that govern the true radiation transport through the human body. In this Vision 20/20 paper, we look back to see how it all started and where things are now in terms of dose algorithms for photon beams and the inclusion of tissue heterogeneities. Convolution-superposition algorithms have dominated the treatment planning industry for the past few years. Monte Carlo techniques have an inherent accuracy that is superior to any other algorithm and as such will continue to be the gold standard, along with measurements, and maybe one day will be the algorithm of choice for all particle treatment planning in radiation therapy.

Original languageEnglish (US)
Pages (from-to)4765-4775
Number of pages11
JournalMedical physics
Volume36
Issue number10
DOIs
StatePublished - 2009

Keywords

  • Dose calculation
  • Inhomogeneity corrections
  • Photon beams

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

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