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Accurate surface dose measurements in CT examinations using high sensitivity MOSFET dosimeters calibrated by Monte Carlo simulations

The objective of this work is to use MOSFET dosimeters to accurately measure surface dose delivered during CT examinations in various scanning conditions. To achieve this, the behaviour of MOSFETs under kilovoltage x-ray irradiation first needed to be investigated. A dose-to-dose reproducibility of 4.5%, and a mean change in sensitivity response of 10.4% with accumulated dose were measured. A Monte Carlo model of the x-ray source of a PQ5000 CT simulator was built and validated in order to investigate the MOSFET response characteristics and perform dose calculations. An over-response of 10% was observed when the beam energy was decreased from 140 to 80 kVp, and a slight anisotropy of 8.5% from the mean value over 360º was observed. The dosimeters were calibrated on a solid water phantom using a method involving MC surface dose calculations. Good agreement was found between measurements and simulations of surface dose on a cylindrical PMMA phantom for a stationary tube technique, single axial scan and multiple contiguous axial scans, with generally less than 7.5% discrepancies. Film and MOSFET measurements were then performed for helical adult brain scan parameters using different pitch and collimator settings. The use of five MOSFETs combined in a linear array was found to be suitable to accurately measure surface dose in helical scans for almost all pitch and collimation combinations.

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.98747
Date January 2006
CreatorsLemire, Matthieu.
PublisherMcGill University
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
LanguageEnglish
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Formatapplication/pdf
CoverageMaster of Science (Department of Medical Radiation Physics.)
Rights© Matthieu Lemire, 2006
Relationalephsysno: 002333250, proquestno: AAIMR24717, Theses scanned by UMI/ProQuest.

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