Investigating the dose distribution in the uncompressed breast with a dedicated CT mammotomography system

Crotty, Dominic J.; Brady, Samuel L.; Jackson, Dvone; Toncheva, Greta; Anderson, Colin E.; Yoshizumi, Terry T.; Tornai, Martin P.

doi:10.1117/12.845433

Cited by 5 publications

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“…The case shown here is one for which the normalized glandular dose ratio between the two breast tissue definitions is similar to the mean of the ratios for all three modalities, so it was selected as representative of an average case. As expected, 17,51,55 these dose maps clearly show, especially for mammography and the lower energy BCT acquisition, the preferential dose deposition in the tissue closer to the x-ray source position of the breast. Therefore, since the glandular tissue tends to be centrally located in the breast, the homogeneous tissue mixture approximation results in an overestimation of the glandular dose compared to when using the true heterogeneous distribution.…”

Section: Iiid Heterogeneous Vs Homogeneous Mean Normalized Glandulasupporting

confidence: 79%

“…34,49,50 These two spectra were chosen since these encompass the extremes of the x-ray beam quality of the three spectra currently being used (third spectrum: 60 kVp, 0.51 mm Ce filter, first HVL = 2.95 mm Al). 51 For each breast, 36 BCT projection acquisitions were simulated, each varying the position of the x-ray source and detector to simulate different projection angles, ranging from 0 • to 350 • , in 10 • steps. The normalized dose results from the 36 projections were averaged to estimate the normalized dose for a complete BCT acquisition.…”

Section: Iid Monte Carlo Simulationsmentioning

confidence: 99%

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Characterization of the homogeneous tissue mixture approximation in breast imaging dosimetry

et al. 2012

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Purpose: To compare the estimate of normalized glandular dose in mammography and breast CT imaging obtained using the actual glandular tissue distribution in the breast to that obtained using the homogeneous tissue mixture approximation. Methods: Twenty volumetric images of patient breasts were acquired with a dedicated breast CT prototype system and the voxels in the breast CT images were automatically classified into skin, adipose, and glandular tissue. The breasts in the classified images underwent simulated mechanical compression to mimic the conditions present during mammographic acquisition. The compressed thickness for each breast was set to that achieved during each patient's last screening cranio‐caudal (CC) acquisition. The volumetric glandular density of each breast was computed using both the compressed and uncompressed classified images, and additional images were created in which all voxels representing adipose and glandular tissue were replaced by a homogeneous mixture of these two tissues in a proportion corresponding to each breast's volumetric glandular density. All four breast images (compressed and uncompressed; heterogeneous and homogeneous tissue) were input into Monte Carlo simulations to estimate the normalized glandular dose during mammography (compressed breasts) and dedicated breast CT (uncompressed breasts). For the mammography simulations the x‐ray spectra used was that used during each patient's last screening CC acquisition. For the breast CT simulations, two x‐ray spectra were used, corresponding to the x‐ray spectra with the lowest and highest energies currently being used in dedicated breast CT prototype systems under clinical investigation. The resulting normalized glandular dose for the heterogeneous and homogeneous versions of each breast for each modality was compared. Results: For mammography, the normalized glandular dose based on the homogeneous tissue approximation was, on average, 27% higher than that estimated using the true heterogeneous glandular tissue distribution (Wilcoxon Signed Rank Testp = 0.00046). For dedicated breast CT, the overestimation of normalized glandular dose was, on average, 8% (49 kVp spectrum, p = 0.00045) and 4% (80 kVp spectrum, p = 0.000089). Only two cases in mammography and two cases in dedicated breast CT with a tube voltage of 49 kVp resulted in lower dose estimates for the homogeneous tissue approximation compared to the heterogeneous tissue distribution. Conclusions: The normalized glandular dose based on the homogeneous tissue mixture approximation results in a significant overestimation of dose to the imaged breast. This overestimation impacts the use of dose estimates in absolute terms, such as for risk estimates, and may impact some comparative studies, such as when modalities or techniques with different x‐ray energies are used. The error introduced by the homogeneous tissue mixture approximation in higher energy x‐ray modalities, such as dedicated breast CT, although statistically significant, may not be of clinical concern. Further...

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Section: Iiid Heterogeneous Vs Homogeneous Mean Normalized Glandulasupporting

confidence: 79%

Section: Iid Monte Carlo Simulationsmentioning

confidence: 99%

Characterization of the homogeneous tissue mixture approximation in breast imaging dosimetry

et al. 2012

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“…Soliman and Bakkari (2015) found that radiochromic film was not sensitive enough to measure entrance skin dose in mammography. However, radiochromic film has been used to characterize the dose distribution inside phantoms in contrast enhanced digital mammography (Hwang et al , 2014) and in DBCT (Russo et al , 2010; Crotty et al , 2010; Crotty et al , 2011). …”

Section: Alternative Methods Of Dose Measurementmentioning

confidence: 99%

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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“…For example, to increase contrast, the x-ray spectra used in BCT (49-80 kVp) have lower energy than those used in whole-body CT (80-140 kVp). 1 To the best of our knowledge, three types of BCT systems that can image patients have been developed; one system was designed by Boone et al, 3 one other prototype system developed by a commercial company (Koning Corporation, West Henrietta, NY), as previously described, 4, 5 and a third system developed by Tornai et al 6,7 Breast tissue classification can provide quantitative measurements regarding breast composition, density, and tissue distribution change with age. It could also aid in breast cancer detection and identification of women at high-risk.…”

Section: Introductionmentioning

confidence: 99%

Cupping artifact correction and automated classification for high‐resolution dedicated breast CT images

Yang

Sechopoulos

et al. 2012

Medical Physics

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Investigating the dose distribution in the uncompressed breast with a dedicated CT mammotomography system

Cited by 5 publications

References 0 publications

Characterization of the homogeneous tissue mixture approximation in breast imaging dosimetry

Characterization of the homogeneous tissue mixture approximation in breast imaging dosimetry

Dosimetry in x-ray-based breast imaging

Cupping artifact correction and automated classification for high‐resolution dedicated breast CT images

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