• An increase in CT imaging of pregnant patients is of concern. • Clinical indications were in line with good practice. • Estimated conceptus doses were lower or similar to published data. • Internal guidelines for appropriate use of imaging during pregnancy should be established.
A versatile EGSnrc Monte Carlo (MC) framework, initially designed to explicitly simulate X-ray tubes and record the output data into phase space data files, was modified towards dental cone-beam computed tomography (CBCT) dosimetric applications by introducing equivalent sources. Half value layer (HVL) measurements were conducted to specify protocol-specific energy spectra. Air kerma measurements were carried out with an ionisation chamber positioned against the X-ray tube to obtain the total filtration attenuation characteristics. The framework is applicable to bowtie and non-bowtie inherent filtrations, and it accounts for the anode heel effect and the total filtration of the tube housing. The code was adjusted to the Promax 3D Max (Planmeca, Helsinki, Finland) dental CBCT scanner. For each clinical protocol, calibration factors were produced to allow absolute MC dose calculations. The framework was validated by comparing MC calculated doses and measured doses in a cylindrical water phantom. Validation results demonstrate the reliability of the framework for dental CBCT dosimetry purposes.
• A patient's internal anatomy affects the dose to the conceptus. • Conceptus position has an influence on its dose estimation. • Patient anatomy and specific TCM must be considered for accurate conceptus dosimetry. • D to a standard-size phantom should not be used as D .
• The z-TCM information is sufficient for accurate dosimetry for standard protocols. • The z-TCM information is sufficient for accurate dosimetry for fast-speed scanning protocols. • For organ-based TCM schemes, the 3D-TCM information is necessary for accurate dosimetry. • At identical CTDI , the fast-speed scanning protocol delivered the highest doses. • Lung dose was higher in XCare than standard protocol at identical CTDI .
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.