Voxelized Breast Phantoms for Dosimetry in Mammography

Tucciariello, Raffaele M.; Barca, Patrizio; Sarto, D. Del; Lamastra, Rocco; Mettivier, Giovanni; Retico, Alessandra; Russo, Paolo; Sarno, Antonio; Traino, Antonio Claudio; Fantacci, Maria Evelina

doi:10.5220/0010322901540161

Cited by 5 publications

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“…The multiscale simulations for breast dosimetry could be employed along with other breast models with complex glandular tissue distributions. [26][27][28][29] In this case, the differences between realistic (heterogeneous) and simplified (homogeneous) models could be extended beyond the MGD to encompass also the GDD and the specific energy distribution. The methodology that was used in this work (Equation 3) can, in theory, be adapted for any breast model with the advantage that, while the macroscopic simulations are necessary to map the h(D g ) distributions, the distributions of f (z, D g ) can be reused from previous microscopic simulations.…”

Section: Discussionmentioning

confidence: 99%

Multiscale Monte Carlo simulations for dosimetry in x‐ray breast imaging: Part II ‐ Microscopic scales

Massera,

Tomal,

Thomson

2023

Medical Physics

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BackgroundAlthough the benefits of breast screening and early diagnosis are known for reducing breast cancer mortality rates, the effects and risks of low radiation doses to the cells in the breast are still ongoing topics of study.PurposeTo study specific energy distributions () in cytoplasm and nuclei of cells corresponding to glandular tissue for different x‐ray breast imaging modalities.MethodsA cubic lattice (500 μm length side) containing 4064 spherical cells was irradiated with photons loaded from phase space files with varying glandular voxel doses (). Specific energy distributions were scored for nucleus and cytoplasm compartments using the PENELOPE (v. 2018) + penEasy (v. 2020) Monte Carlo (MC) code. The phase space files, generated in part I of this work, were obtained from MC simulations in a voxelized anthropomorphic phantom corresponding to glandular voxels for different breast imaging modalities, including digital mammography (DM), digital breast tomosynthesis (DBT), contrast enhanced digital mammography (CEDM) and breast CT (BCT).ResultsIn general, the average specific energy in nuclei is higher than the respective glandular dose scored in the same region, by up to 10%. The specific energy distributions for nucleus and cytoplasm are directly related to the magnitude of the glandular dose in the voxel (), with little dependence on the spatial location. For similar values, for nuclei is different between DM/DBT and CEDM/BCT, indicating that distinct x‐ray spectra play significant roles in . In addition, this behavior is also present when the specific energy distribution () is considered taking into account the GDD in the breast.ConclusionsMicrodosimetry studies are complementary to the traditional macroscopic breast dosimetry based on the mean glandular dose (MGD). For the same MGD, the specific energy distribution in glandular tissue varies between breast imaging modalities, indicating that this effect could be considered for studying the risks of exposing the breast to ionizing radiation.

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Section: Discussionmentioning

confidence: 99%

Multiscale Monte Carlo simulations for dosimetry in x‐ray breast imaging: Part II ‐ Microscopic scales

Massera,

Tomal,

Thomson

2023

Medical Physics

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“…The random sampling started with the nominal glandular volume percentage, then the central breast region was divided into semi-cylindrical slices (Z direction), one for each voxel layer in depth. Afterwards, the number of glandular voxels for each slice was determined, based on the nominal glandular content, by random sampling from a normal distribution with mean C and standard deviation SD (Tucciariello et al 2021). With the number of glandular voxels in a specific layer, their location was sampled from a uniform distribution (X and Y coordinates).…”

Section: Simplified Heterogeneous Modelsmentioning

confidence: 99%

Impact of photoelectric cross section data on systematic uncertainties for Monte Carlo breast dosimetry in mammography

Massera

Fernández-Varea

2021

Phys. Med. Biol.

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Monte Carlo (MC) simulations are employed extensively in breast dosimetry studies. In the energy interval of interest in mammography energy deposition is predominantly caused by the photoelectric effect, and the corresponding cross sections used by the MC codes to model this interaction process have a direct influence on the simulation results. The present work compares two photoelectric cross section databases in order to estimate the systematic uncertainty, related to breast dosimetry, introduced by the choice of cross sections for photoabsorption. The databases with and without the so-called normalization screening correction are denoted as ‘renormalized’ or ‘un-normalized’, respectively. The simulations were performed with the PENELOPE/penEasy code system, for a geometry resembling a mammography examination. The mean glandular dose (MGD), incident air kerma (K air), normalized glandular dose (DgN) and glandular depth-dose (GDD(z)) were scored, for homogeneous breast phantoms, using both databases. The AAPM Report TG-195 case 3 was replicated, and the results were included. Moreover, cases with heterogeneous and anthropomorphic breast phantoms were also addressed. The results simulated with the un-normalized cross sections are in better overall agreement with the TG-195 data than those from the renormalized cross sections; for MGD the largest discrepancies are 0.13(6)% and 0.74(5)%, respectively. The MGD, K air and DgN values simulated with the two databases show differences that diminish from approximately 10%/3%/6.8% at 8.25 keV down to 1.5%/1.7%/0.4% at 48.75 keV, respectively. For polyenergetic spectra, deviations up to 2.5% were observed. The disagreement between the GDDs simulated with the analyzed databases increases with depth, ranging from −1% near the breast entrance to 4% near the bottom. Thus, the choice of photoelectric cross section database affects the MC simulation results of breast dosimetry and adds a non-negligible systematic uncertainty to the dosimetric quantities used in mammography.

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“…Nowadays, there is a consensus that DgN could be significantly overestimated if simplified homogeneous approximation are applied instead of more realistic heterogeneous breast models (Sechopoulos et al 2012, Hernandez et al 2015, Sarno et al 2018, Tucciariello et al 2021, Caballo et al 2022. The average over-estimation of the MGD is around 30%, with largest variations (up to 120%) observed for thicker breasts and lower energy beams (Sechopoulos et al 2012, Hernandez et al 2015.…”

Section: Introductionmentioning

confidence: 99%

“…However, the use of patient-derived breast models is restricted to a few numbers of phantoms or studies, being limited by small cohorts or a small number of breast CT images. An alternative is the use of heterogeneous voxelized phantoms generated based on probabilistic distributions of fibroglandular tissue inside the breast, in particular, gaussian or double-gaussian distributions and more realistic distributions based on patient-derived data from breast CT images (Hernandez et al 2015, Tucciariello et al 2021, Caballo et al 2022. Although voxelized heterogeneous breast models do not represent real tissue distributions for patient-derived studies, they can be generated based on data of mean distributions of fibroglandular tissue, allowing for a large variability of breast characteristics (i.e.…”

Section: Introductionmentioning

confidence: 99%

Impact of fibroglandular tissue distribution and breast shape in voxelized breast models for dosimetry in mammography

et al. 2023

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Objectives. This work proposes to study the impact of different voxelized heterogeneous breast models (gaussian centered - GaussC; gaussian lower - GaussL; and fitted equation patient-based on 3D realistic distribution (Fedon et al., 2021) - FitPB) for dosimetry in mammography compared to a well-established homogeneous approximation. Influence of breast outer shape also was investigated by comparing semicylindric and anthropomorphic breasts. Approach. By using the PENELOPE (v. 2018) + penEasy (v. 2020) MC code, simulations were performed to evaluate the normalized glandular dose (DgN) and the glandular depth dose (GDD(z)) for different breast characteristics and x-ray beam spectra. Main results. The average DgN overestimation caused by homogeneous tissue approximation was 33.0%, with the highest values attributed to GaussL and FitPB models, where fibroglandular tissue is concentrated deeper in the breast. The variation observed between anthropomorphic and semicylindrical breast shapes was, on average, 5.6%, legitimizing the latter approximation for breast dosimetry. Thicker breasts and lower energy beams resulted in larger overestimation caused by the homogeneous approach, while variations in DgN values among different heterogeneous models were higher for thinner breast and lower energy beams. Moreover, the depth where differences between GDD(z) for different breast models became maximum depends on the axial variation of fibroglandular tissue concentration between each model. The GDD(z) dependence results in a significant variation of the contribution of each breast depth to MGD among the breast models studied. Significance. Inter comparison between different breast models for dosimetry can be useful for estimating more accurate MGD values for population-based dosimetry, for exploring the use of 1D gaussian distribution for breast dosimetry, and for understanding the dose distributions inside the fibroglandular tissues, which could be a novel source of information for risk estimations.

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Voxelized Breast Phantoms for Dosimetry in Mammography

Cited by 5 publications

References 0 publications

Multiscale Monte Carlo simulations for dosimetry in x‐ray breast imaging: Part II ‐ Microscopic scales

Multiscale Monte Carlo simulations for dosimetry in x‐ray breast imaging: Part II ‐ Microscopic scales

Impact of photoelectric cross section data on systematic uncertainties for Monte Carlo breast dosimetry in mammography

Impact of fibroglandular tissue distribution and breast shape in voxelized breast models for dosimetry in mammography

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