Mean glandular dose in digital mammography: a dose calculation method comparison

Moayyad E. Suleiman; Patrick C. Brennan; Mark F. McEntee

doi:10.1117/1.JMI.4.1.013502

24 January 2017 Mean glandular dose in digital mammography: a dose calculation method comparison

Moayyad E. Suleiman, Patrick C. Brennan, Mark F. McEntee

Author Affiliations +

Journal of Medical Imaging, Vol. 4, Issue 1, 013502 (January 2017). https://doi.org/10.1117/1.JMI.4.1.013502

Abstract

Our objective was to analyze the agreement between organ dose estimated by different digital mammography units and calculated dose for clinical data. Digital Imaging and Communication in Medicine header information was extracted from 52,405 anonymized mammograms. Data were filtered to include images with no breast implants, breast thicknesses 20 to 110 mm, and complete exposure and quality assurance data. Mean glandular dose was calculated using methods by Dance et al., Wu et al., and Boone et al. Bland–Altman analysis and regression were used to study the agreement and correlation between organ and calculated doses. Bland–Altman showed statistically significant bias between organ and calculated doses. The bias differed for different unit makes and models; Philips had the lowest bias, overestimating Dance method by 0.03 mGy, while general electric had the highest bias, overestimating Wu method by 0.20 mGy, the Hologic organ dose underestimated Boone method by 0.07 mGy, and the Fujifilm organ dose underestimated Dance method by 0.09 mGy. Organ dose was found to disagree with our calculated dose, yet organ dose is potentially beneficial for rapid dose audits. Conclusions drawn based on the organ dose alone come with a risk of over or underestimating the calculated dose to the patient and this error should be considered in any reported results.

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Moayyad E. Suleiman, Patrick C. Brennan, and Mark F. McEntee "Mean glandular dose in digital mammography: a dose calculation method comparison," Journal of Medical Imaging 4(1), 013502 (24 January 2017). https://doi.org/10.1117/1.JMI.4.1.013502

Received: 17 July 2016; Accepted: 27 December 2016; Published: 24 January 2017

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