High density dental materials and radiotherapy planning

Comparison of the dose predictions using superposition algorithm and fluence map Monte Carlo method with radiochromic film measurements

Siarhei Spirydovich, Lech Papiez, Mark Langer, George Sandison, Van Thai

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

Background and purpose: During radiotherapy planning high density dental materials create a major challenge in determining correct dose distribution inside patients with head-and-neck tumors. Patients and methods: In this work we investigated the absorbed dose distribution inside a solid water® slab phantom with embedded high density material irradiated by a 6 MV photon beam of field size 10 × 10 cm. We evaluated the absorbed dose distribution with three different techniques: superposition algorithm, radiochromic film, and the fluence map Monte Carlo (FMMC) method. Results: The results obtained with radiochromic film and FMMC were in good agreement (within ±5% of the dose) with one another. The superposition algorithm, which is often considered superior to other commercially available dose calculation algorithms, produced appreciably less accurate results than FMMC. In particular, downstream from the high density cerrobend inhomogeneity the superposition algorithm predicts a higher dose than the measurement does by at least 10-16% depending upon the size of the inhomogeneity and the distance from it. Upstream of the high density inhomogeneities the superposition algorithm predicts a lower than measured dose due to its failure to predict the dose enhancement close to the inhomogeneity interface. Conclusions: The delivered dose downstream from a high density inhomogeneity would be significantly less than the prescribed dose calculated by the superposition algorithm. The FMMC method which is based on a hybrid of the superposition algorithm input fluence data and Monte Carlo can be a useful tool in predicting dose in the presence of high density (e.g. dental) materials.

Original languageEnglish
Pages (from-to)309-314
Number of pages6
JournalRadiotherapy and Oncology
Volume81
Issue number3
DOIs
StatePublished - Dec 2006

Fingerprint

Monte Carlo Method
Dental Materials
Radiotherapy
Photons
Neck
Head
Water

Keywords

  • Convolution
  • Dental
  • Fluence map
  • Head and neck
  • Monte Carlo
  • Superposition

ASJC Scopus subject areas

  • Oncology
  • Radiology Nuclear Medicine and imaging
  • Urology

Cite this

High density dental materials and radiotherapy planning : Comparison of the dose predictions using superposition algorithm and fluence map Monte Carlo method with radiochromic film measurements. / Spirydovich, Siarhei; Papiez, Lech; Langer, Mark; Sandison, George; Thai, Van.

In: Radiotherapy and Oncology, Vol. 81, No. 3, 12.2006, p. 309-314.

Research output: Contribution to journalArticle

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abstract = "Background and purpose: During radiotherapy planning high density dental materials create a major challenge in determining correct dose distribution inside patients with head-and-neck tumors. Patients and methods: In this work we investigated the absorbed dose distribution inside a solid water{\circledR} slab phantom with embedded high density material irradiated by a 6 MV photon beam of field size 10 × 10 cm. We evaluated the absorbed dose distribution with three different techniques: superposition algorithm, radiochromic film, and the fluence map Monte Carlo (FMMC) method. Results: The results obtained with radiochromic film and FMMC were in good agreement (within ±5{\%} of the dose) with one another. The superposition algorithm, which is often considered superior to other commercially available dose calculation algorithms, produced appreciably less accurate results than FMMC. In particular, downstream from the high density cerrobend inhomogeneity the superposition algorithm predicts a higher dose than the measurement does by at least 10-16{\%} depending upon the size of the inhomogeneity and the distance from it. Upstream of the high density inhomogeneities the superposition algorithm predicts a lower than measured dose due to its failure to predict the dose enhancement close to the inhomogeneity interface. Conclusions: The delivered dose downstream from a high density inhomogeneity would be significantly less than the prescribed dose calculated by the superposition algorithm. The FMMC method which is based on a hybrid of the superposition algorithm input fluence data and Monte Carlo can be a useful tool in predicting dose in the presence of high density (e.g. dental) materials.",
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