CT Radiation Dosimetry Study using Monte Carlo Simulation and Computational Anthropomorphic Phantoms

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Date

2012

Authors

Zhang, Yakun

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Samei, Ehsan

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Abstract

There are three main x-ray based modalities for imaging the thorax: radiography, tomosynthesis, and computed tomography (CT). CT perhaps provides the highest level of feature resolution but at notably higher radiation dose, which has increased the concern among radiation protection professionals. Being able to accurately assess the radiation dose patients receive during CT procedures is a crucial step in the management of CT dose. To identify the best imaging modality for patients, the American College of Radiology published the guiding principle of "The right exam, for the right reason, at the right time". To implement this principle in making an appropriate choice between standard chest projection imaging, tomosynthesis, and CT, the organ and effective dose for each modality should be accurately known. This thesis work attempted to explain the effect on dose results when choosing different types of computational phantoms used in CT dosimetry; this work also compared radiation dose across three main x-ray based modalities on one common platform for different body shape adults.

The first part of this thesis compared organ doses, effective doses, and risk indices from 13 representative adult CT protocols using four types of reference phantoms (XCAT, ICRP 110, ImPACT, and CT-Expo). Despite closely-matched organ mass, total body weight, and height, large differences in organ dose exist due to variation in organ location, spatial distribution, and dose approximation method. Dose differences for fully irradiated radiosensitive organs were much smaller than those for partially irradiated organs. Weighted dosimetry quantities including effective dose, male risk indices, k factors, and male q factors agreed well across phantoms. The female risk indices and q factors varied considerably across phantoms.

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Zhang, Yakun (2012). CT Radiation Dosimetry Study using Monte Carlo Simulation and Computational Anthropomorphic Phantoms. Master's thesis, Duke University. Retrieved from https://hdl.handle.net/10161/6199.

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