Dosimetry in x-ray-based breast imaging

Abstract

The estimation of the mean glandular dose to the breast (MGD) for x-ray based imaging modalities forms an essential part of quality control and is needed for risk estimation and for system design and optimisation. This review considers the development of methods for estimating the MGD for mammography, digital breast tomosynthesis (DBT) and dedicated breast CT (DBCT). Almost all of the methodology used employs Monte Carlo calculated conversion factors to relate the measurable quantity, generally the incident air kerma, to the MGD. After a review of the size and composition of the female breast, the various mathematical models used are discussed, with particular emphasis on models for mammography. These range from simple geometrical shapes, to the more recent complex models based on patient DBCT examinations. The possibility of patient-specific dose estimates is considered as well as special diagnostic views and the effect of breast implants. Calculations using the complex models show that the MGD for mammography is overestimated by about 30% when the simple models are used. The design and uses of breast-simulating test phantoms for measuring incident air kerma are outlined and comparisons made between patient and phantom-based dose estimates. The most widely used national and international dosimetry protocols for mammography are based on different simple geometrical models of the breast, and harmonisation of these protocols using more complex breast models is desirable.

Figure 1

Typical distributions of compressed breast thickness for CC and MLO views. The data are for women attending for a diagnostic examination. Figure from Kelaranta et al (2015) and reproduced by permission of Oxford University Press.

Figure 2

Estimates of average breast composition for different compressed breast thickness from two United Kingdom centres for women in the age range 50 to 64. The error bars correspond to ±1 standard error on the mean. In some cases the error bars are too small to show. Figure from (Dance et al, 2000).

Figure 3

Linear attenuation coefficients for adipose (closed circles) and glandular breast tissues (open circles) at 20 keV. Data compiled from H Hammerstein et al (1979), J Johns and Yaffe (1987), C Chen et al (2010) and T Tomal et al (2010).

Figure 4

Simple geometrical models used by Dance (1990) (a,b), Wu et al (1991) (a,b) and Boone (1999) (a,c) to model the breast in the CC projection. All three models have a central region which is a homogeneous mixture of adipose and glandular tissues surrounded by an outer layer. In the Dance model this layer is adipose tissue whereas in the other two models it is skin. In the Dance model the breast is a cylinder of semi-circular cross section, whereas in the Wu model it has semi-elliptical cross section. The Boone model (a, c) uses a phantom of circular cross section, only half of which is irradiated (the thick line shows the position of the radiation field.

Figure 5

(left) The g factor for varying breast thickness and 1^st HVL. (right) c factors for a 5 cm compressed breast thickness for varying breast glandularity and 1^st HVL. Data taken from Dance et al (2000).

Figure 6

Variation of the DgN with tube voltage and 1^st half value layer as determined by Wu et al (1991).

Figure 7

Variation of RGD(α) with DBT projection angle for various simulation factors, showing its independence with glandularity and x-ray spectrum. Figure from Sechopoulos et al (2007a). Copyright (c) 2007, American Association of Physicists in Medicine (AAPM).

Figure 8

Model of the MLO view breast as developed by Sechopoulos et al. Figure from Sechopoulos et al (2007a). Copyright (c) 2007, American Association of Physicists in Medicine (AAPM).

Figure 9

Comparison of Dance et al’s t factors with Sechopoulos et al’s RGD(α), showing the expected similarity given their equivalent definition. Figure from Dance et al (2011).

Figure 10

(top) Monoenergetic Monte Carlo results of MGD per million photons simulated for DBCT acquisitions for breasts of two sizes (defined as the diameter at the chest wall), three glandularities and a range of x-ray energies. (bottom) Result of combining the monoenergetic results to obtain spectral DgNCT coefficients for the same breasts for a range of tube voltages. Figures from Boone et al (2004). Copyright (c) 2004, American Association of Physicists in Medicine (AAPM).

Figure 11

Distribution of breast diameters at the chest wall over 200 patients, measured for the modelling of the uncompressed breast during DBCT acquisition. Figure from Boone et al (2004). Copyright (c) 2004, American Association of Physicists in Medicine (AAPM).

Figure 12

Sagittal slice of one of the DBCT patient images that was classified and compressed to represent a breast with its real patient tissue structure undergoing mammography in the study by Sechopoulos et al (2012). Figure from Sechopoulos et al (2012). Copyright (c) 2012, American Association of Physicists in Medicine (AAPM).

Figure 13

Scatter plot of the normalized glandular dose coefficients for the actual patient breast glandular tissue structure compared to that resulting when assuming a homogeneous tissue mixture. Figure from Sechopoulos et al (2012). Copyright (c) 2012, American Association of Physicists in Medicine (AAPM).

Figure 14

Model of the glandular tissue distribution inside a new model of the breast compressed for mammography developed by Hernandez et al (2015) based on analysis of DBCT patient data. This model was used to compare the resulting MGD to that of the homogeneous model estimates. Figure from Hernandez et al (2015). Copyright (c) 2015, American Association of Physicists in Medicine (AAPM). Part (a) of the figure shows at the top the radial glandular fraction (RGF) and at the bottom in shaded form the regional volumetric glandular fraction (rVGF) in a coronal plane through the breast. Part (b) (top) shows in shaded form the rVGF in a transverse section through the breast. The scale used for shading is shown at the bottom of part (b). The reader is referred to the original paper for a detailed explanation of these quantities and how they have been used.

Figure 15

Screen capture of mammographic patient dose monitoring using TQM software (Qaelum NV, Leuven, Belgium) at the University of Leuven. Image courtesy of Hilde Bosmans.

Figure 16

Diagrams of the (top) standard PMMA phantom and the (bottom) PMMA/PE phantom proposed by Bouwman et al to represent patient breasts. Tables 1 and 2 list the values of their equivalent thickness and glandularity. Figure from Bouwman et al (2015a).

Figure 17

MGD variation with breast thickness for (left) CR, screen-film and DR systems and (right) five different DR systems. Republished by permission of British Institute of Radiology, from Young and Oduko (2016).

Figure 18

Patient MGD as function of compressed breast thickness for a particular mammography system operating in mammography and DBT modes. Figure based on Bouwman et al (2015a).