Mean glandular dose coefficients (DgN) for x-ray spectra used in contemporary breast imaging systems

Nosratieh, Anita; Hernandez, Andrew M.; Shen, Sam Z.; Yaffe, Martin J.; Seibert, J. Anthony; Boone, John M.

doi:10.1088/0031-9155/60/18/7179

Cited by 28 publications

(61 citation statements)

References 21 publications

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“…Making these fit equations available for mono-energetic data removed the need to keep generating tables of spectral DgN coefficients as new target/filter combinations or higher tube voltages, up to 50 kVp become available. It should be noted, however, that the fit equation provided by Boone for ϑ(E), the exposure per photon/mm 2 in Appendix D of his work, is incorrect and should not be used (Dance and Young, 2014, Nosratieh et al , 2015). …”

Section: Conversion Factors For Projection Mammography Using Simplementioning

confidence: 99%

“…In their 2015 paper (Nosratieh et al , 2015), Boone’s group present the calculation of DgN values for a very wide range of X-ray spectra, for breast thicknesses in the range 30–80 mm and for five different glandularities. Thus there appears to be no data published using this model for small or very large breasts.…”

Section: Conversion Factors For Projection Mammography Using Simplementioning

confidence: 99%

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Dosimetry in x-ray-based breast imaging

2016

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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.

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Section: Conversion Factors For Projection Mammography Using Simplementioning

confidence: 99%

Section: Conversion Factors For Projection Mammography Using Simplementioning

confidence: 99%

Dosimetry in x-ray-based breast imaging

2016

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“…Several authors have performed Monte Carlo (MC) simulations to compute the normalized glandular dose conversion coefficients (DgN) which are used to estimate mean dose to the glandular component of the breast tissue (mean glandular dose-MGD) during full field mammography from measurements of the incident air kerma or exposure. [1][2][3][4][5][6][7][8][9] In these studies, the breast has been modeled as a homogeneous mixture of adipose and glandular tissue surrounded by a shielding layer which simulates either a 0.4 cm thick layer of skin or a 0.5 cm thick layer of adipose tissue. It is fully irradiated, and the MGD is assumed independent of the source-to-breast distance and of the breast diameter.…”

Section: Introductionmentioning

confidence: 99%

A Monte Carlo model for mean glandular dose evaluation in spot compression mammography

et al. 2017

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Purpose To characterize the dependence of normalized glandular dose (DgN) on various breast model and image acquisition parameters during spot compression mammography and other partial breast irradiation conditions, and evaluate alternative previously-proposed dose-related metrics for this breast imaging modality. Methods Using Monte Carlo simulations with both simple homogeneous breast models and patient-specific breasts, three different dose related metrics for spot compression mammography were compared: the standard DgN, the normalized glandular dose to only the directly irradiated portion of the breast (DgNv), and the DgN obtained by the product of the DgN for full field irradiation and the ratio of the mid-height area of the irradiated breast to the entire breast area (DgNM). How these metrics vary with field-of-view size, spot area thickness, x-ray energy, spot area and position, breast shape and size, and system geometry was characterized for the simple breast model and a comparison of the simple model results to those with patient-specific breasts was also performed. Results DgN in spot compression mammography can vary considerably with breast area. However, the difference in breast thickness between the spot compressed area and the uncompressed area does not introduce a variation in DgN. As long as the spot compressed area is completely within the breast area and only the compressed breast portion is directly irradiated, its position and size does not introduce a variation in DgN for the homogeneous breast model. As expected, DgN is lower than DgNv for all partial breast irradiation areas, especially when considering spot compression areas within the clinically used range. DgNM underestimates DgN by 6.7% for a W/Rh spectrum at 28 kVp and for a 9×9 cm2 compression paddle. Conclusion As part of the development of a new breast dosimetry model, a task undertaken by the American Association of Physicists in Medicine and the European Federation of Organizations of Medical Physics, these results provide insight on how DgN and two alternative dose metrics behave with various image acquisition and model parameters.

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“…For verifying the Monte Carlo modelling, THOPs with 25%, 50%, and 75% MGF were employed to attain the DgN coefficients at the W/Ag target-filter combination for breast thicknesses of 3, 5, and 7 cm and tube voltages of 26, 28, 30, 32, and 34 kVp. The results were compared with those obtained by Nosratieh et al 23 . Subsequently, THEPs were used to obtain the heterogeneous DgN coefficients for concentrated, inferior, and superior glandular distributions.…”

Section: Mammography Modellingmentioning

confidence: 82%

“…Compared with the result of TG-195, the error is less than 0.2%, indicating the credibility of the Monte Carlo code. Figure 2 compares the DgN coefficients of THOPs and those obtained by Nosratieh et al 23 . The linear regression result revealed a favorable linearity (y = 0.9812x − 0.0013, R 2 = 0.9866) with no significant differences between the two sets of DgN values (p = 0.727).…”

mentioning

confidence: 81%

Three-layer heterogeneous mammographic phantoms for Monte Carlo simulation of normalized glandular dose coefficients in mammography

Chang

Lai

et al. 2020

Sci Rep

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Normalized glandular dose (DgN) coefficients obtained using homogeneous breast phantoms are commonly used in breast dosimetry for mammography. However, glandular tissue is heterogeneously distributed in the breast. This study aimed to construct three-layer heterogeneous mammographic phantoms (THEPs) to examine the effect of glandular distribution on DgN coefficient. Each layer of THEPs was set to 25%, 50%, or 75% glandular fraction to emulate heterogeneous glandular distribution. Monte Carlo simulation was performed to attain mean glandular dose (MGD) and air kerma at 22-36 kVp and W/Al, W/Rh, and W/Ag target-filter combinations. The heterogeneous DgN coefficient was calculated as functions of the mean glandular fraction (MGF), breast thickness, tube voltage, and half-value layer. At 50% MGF, the heterogeneous DgN coefficients for W/Al, W/Rh, and W/Ag differed by 40.3%, 36.7%, and 31.2%. At 9-cm breast thickness, the DgN values of superior and inferior glandular distributions were 25.4% higher and 29.2% lower than those of uniform distribution. The proposed THEPs can be integrated with conventional breast dosimetry to consider the heterogeneous glandular distribution in clinical practice.Breast cancer is the second most common cause of cancer deaths among women 1 , and its incidence increases annually. X-ray mammography has become a primary tool for breast cancer screening because of the high sensitivity and specificity for microcalcification and mass detection 2 . Mammography is also adopted for the high effectiveness/cost ratio. However, the glandular tissue in the breast is sensitive to radiation. The radiation exposure during mammography may increase the risk of radiation-induced secondary breast malignancy 3 . Therefore, assessment of glandular dose in the breast is crucial.In modern breast dosimetry, one of the most critical parameters is the normalized glandular dose (DgN) coefficient, which is obtained using Monte Carlo simulation of mean glandular dose (MGD) in a breast phantom 4 . Boone used simple homogeneous breast phantoms to simulate the breast absorbed dose and applied a G factor to calculate MGD 5 . He further proposed monoenergetic DgN coefficients to facilitate rapid calculation of the DgN coefficient for arbitrary X-ray energy spectra 6 . Dance et al. 7 employed homogeneous semicylindrical phantoms to assess MGD conversion factor g, breast composition factor c, and X-ray spectrum factor s. The authors further supplemented the conversion factors for the high-energy spectra used for contrast enhanced digital mammography by using the same homogeneous breast model 8 . The above method is now the standard breast dosimetry protocols for mammography in the United Kingdom, European Union, and IAEA and is also adopted in the quality assurance protocols in USA. Sarno et al. 9 used homogeneous semi-cylinder and ad hoc shaped phantoms to exam MGD in mammography and calculate the t-factor (relative glandular dose, RGD) and T-factor in digital breast tomosynthesis (DBT).Three-dimensional (3D) imaging modalit...

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Mean glandular dose coefficients (D_gN) for x-ray spectra used in contemporary breast imaging systems

Cited by 28 publications

References 21 publications

Dosimetry in x-ray-based breast imaging

Dosimetry in x-ray-based breast imaging

A Monte Carlo model for mean glandular dose evaluation in spot compression mammography

Three-layer heterogeneous mammographic phantoms for Monte Carlo simulation of normalized glandular dose coefficients in mammography

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