Literature DB >> 18068841

Tissue segmentation in Monte Carlo treatment planning: a simulation study using dual-energy CT images.

Magdalena Bazalova1, Jean-François Carrier, Luc Beaulieu, Frank Verhaegen.   

Abstract

PURPOSE: Tissue segmentation is an important step in Monte Carlo (MC) dose calculation and is often done uncritically. A new approach to tissue segmentation using dual-energy CT images is studied in this work.
MATERIALS AND METHODS: A simple MC model of a CT scanner was built and CT images of phantoms with ten tissue-equivalent cylinders were simulated using soft and hard X-ray spectra. The Z and rho(e) of the cylinders were extracted using a formalism based on a parameterization of the linear attenuation coefficient.
RESULTS: It was shown that in order to extract Z and rho(e) with a reasonable accuracy, hard X-ray beams have to be used for scanning. When an additional filtration of 9 mm of aluminium in the CT X-ray beam is used, beam hardening in high density materials is suppressed and the mean errors of the extraction of Z and rho(e) for 10 tissue-equivalent materials in a small tissue-equivalent phantom are 3.7% and 3.1%, respectively.
CONCLUSIONS: MC simulations were used to show that the extraction of Z and rho(e) for a number of tissue-equivalent materials using dual-energy CT images is possible which improves tissue segmentation for Monte Carlo dose calculations, as demonstrated with a 250 kVp photon beam dose calculation.

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Year:  2008        PMID: 18068841     DOI: 10.1016/j.radonc.2007.11.008

Source DB:  PubMed          Journal:  Radiother Oncol        ISSN: 0167-8140            Impact factor:   6.280


  9 in total

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  9 in total

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