Internal breast dosimetry in mammography: Experimental methods and Monte Carlo validation with a monoenergetic x‐ray beam

Fedon, Christian; Caballo, Marco; Longo, Renata; Trianni, Annalisa; Sechopoulos, Ioannis

doi:10.1002/mp.12792

Cited by 15 publications

(31 citation statements)

References 49 publications

(122 reference statements)

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“…(a) and (b)]. Due to the beam hardening effect and the dosimeter's energy dependence, calibration has to be performed at each investigated depth. Thus, a varying number of phantom slabs were positioned on top of the compression paddle (Fig.…”

Section: Methodsmentioning

confidence: 99%

“…Analysis of the GafChromic™ film was performed using open source software (ImageJ; National Institutes of Health, Bethesda, MD, USA) following the procedure reported in Fedon et al which is based on the method proposed by Tomic et al…”

Section: Methodsmentioning

confidence: 99%

“…The 2D dose map (in mGy) was obtained using the best calibration fit function and the combined standard uncertainty (k = 1) was estimated as follows:

u_{GAF} = \sqrt{u_{ROI}^{2} + u_{Calib}^{2} + u_{IOC}^{2}}

where

u_{italicROI}^{2}

is a Type A uncertainty for a 1 cm 2 region of interest (ROI) while

u_{italicCalib}^{2}

and

u_{italicIOC}^{2}

are Type B uncertainties for the calibration and IOC, respectively, estimated on a rectangular‐based distribution.…”

Section: Methodsmentioning

confidence: 99%

“…The final dose value (

\bar{D_{MOSFET}}

) was obtained by averaging three exposures among the ratio (∆ V /CF). The combined standard uncertainty (k = 1) for

\bar{D_{MOSFET}}

is expressed as follows:

u_{\bar{D_{MOSFET}}} = \sqrt{u_{Δ V}^{2} + u_{CF}^{2} + u_{IOC}^{2} + u_{MOSFET}^{2}},

where

u_{normalΔ V}^{2}

and

u_{italicCF}^{2}

are Type A uncertainties for the signal response and calibration factor, respectively [see Eq. ]; and

u_{italicIOC}^{2}

and

u_{italicMOSFET}^{2}

are Type B uncertainties for the IOC and MOSFET accuracy, respectively, all estimated on a rectangular‐based distribution.…”

Section: Methodsmentioning

confidence: 99%

“…High sensitivity lithium fluoride (LiF: Mg, Cu, P) TLD chips (TLD‐100H, ThermoFisher Scientific, Waltham, MA, USA) were used in this study. The annealing and reading procedures are described in Fedon et al The dose is provided by the following equation:

D_{i}^{TLD} = Q_{i} x \frac{K_{italiccalib}}{S_{i}}

where Q i is the i th TLD reading (in nC), S i is a dimensionless sensitivity factor specific for each TLD, and K calib is the calibration factor (in mGy/nC). No correction was made for the TLD self‐absorption since, at this energy, the TLD thickness was assumed not to attenuate the beam to a significant degree …”

Section: Methodsmentioning

confidence: 99%

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Internal breast dosimetry in mammography: Monte Carlo validation in homogeneous and anthropomorphic breast phantoms with a clinical mammography system

2018

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PurposeTo validate Monte Carlo (MC)‐based breast dosimetry estimations using both a homogeneous and a 3D anthropomorphic breast phantom under polyenergetic irradiation for internal breast dosimetry purposes.MethodsExperimental measurements were performed with a clinical digital mammography system (Mammomat Inspiration, Siemens Healthcare), using the x‐ray spectrum selected by the automatic exposure control and a tube current‐exposure time product of 360 mAs. A homogeneous 50% glandular breast phantom and a 3D anthropomorphic breast phantom were used to investigate the dose at different depths (range 0–4 cm with 1 cm steps) for the homogeneous case and at a depth of 2.25 cm for the anthropomorphic case. Local dose deposition was measured using thermoluminescent dosimeters (TLD), metal oxide semiconductor field‐effect transistor dosimeters (MOSFET), and GafChromic™ films. A Geant4‐based MC simulation was modified to match the clinical experimental setup. Thirty sensitive volumes (3.2 × 3.2 × 0.38 mm3) on the axial‐phantom plane were included at each depth in the simulation to characterize the internal dose variation and compare it to the experimental TLD and MOSFET measurements. The experimental 2D dose maps obtained with the GafChromic™ films were compared to the simulated 2D dose distributions.ResultsDue to the energy dependence of the dosimeters and due to x‐ray beam hardening, dosimeters based on these three technologies have to be calibrated at each depth of the phantom. As expected, the dose was found to decrease with increasing phantom depth, with the reduction being ~93% after 4 cm for the homogeneous breast phantom. The 2D dose map showed nonuniformities in the dose distribution in the axial plane of the phantom. The mean combined standard uncertainty increased with phantom depth by up to 5.3% for TLD, 6.3% for MOSFET, and 9.6% for GafChromic™ film. In the case of a heterogeneous phantom, the dosimeters are able to detect local dose gradient variations. In particular, GafChromic™ film showed local dose variations of about 46% at the boundaries of two materials.ConclusionsResults showed a good agreement between experimental measurements (with TLD and MOSFET) and MC data for both homogeneous and anthropomorphic breast phantoms. Larger discrepancies are found when comparing the GafChromic™ dose values to the MC results due to the inherent less precise nature of the former.MC validations in a heterogeneous background at the level of local dose deposition and in absolute terms play a fundamental role in the development of an accurate method to estimate radiation dose. The potential introduction of a breast dosimetry model involving a nonhomogeneous glandular/adipose tissue composition makes the validation of internal dose distributions estimates crucial.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…The 2D dose map (in mGy) was obtained using the best calibration fit function and the combined standard uncertainty (k = 1) was estimated as follows:

u_{GAF} = \sqrt{u_{ROI}^{2} + u_{Calib}^{2} + u_{IOC}^{2}}

where

u_{italicROI}^{2}

is a Type A uncertainty for a 1 cm 2 region of interest (ROI) while

u_{italicCalib}^{2}

and

u_{italicIOC}^{2}

are Type B uncertainties for the calibration and IOC, respectively, estimated on a rectangular‐based distribution.…”

Section: Methodsmentioning

confidence: 99%

“…The final dose value (

\bar{D_{MOSFET}}

) was obtained by averaging three exposures among the ratio (∆ V /CF). The combined standard uncertainty (k = 1) for

\bar{D_{MOSFET}}

is expressed as follows:

u_{\bar{D_{MOSFET}}} = \sqrt{u_{Δ V}^{2} + u_{CF}^{2} + u_{IOC}^{2} + u_{MOSFET}^{2}},

where

u_{normalΔ V}^{2}

and

u_{italicCF}^{2}

are Type A uncertainties for the signal response and calibration factor, respectively [see Eq. ]; and

u_{italicIOC}^{2}

and

u_{italicMOSFET}^{2}

are Type B uncertainties for the IOC and MOSFET accuracy, respectively, all estimated on a rectangular‐based distribution.…”

Section: Methodsmentioning

confidence: 99%

D_{i}^{TLD} = Q_{i} x \frac{K_{italiccalib}}{S_{i}}

Section: Methodsmentioning

confidence: 99%

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Internal breast dosimetry in mammography: Monte Carlo validation in homogeneous and anthropomorphic breast phantoms with a clinical mammography system

2018

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Report on G4‐Med, a Geant4 benchmarking system for medical physics applications developed by the Geant4 Medical Simulation Benchmarking Group

et al. 2020

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Geant4 is a Monte Carlo code extensively used in medical physics for a wide range of applications, such as dosimetry, micro-and nano-dosimetry, imaging, radiation protection and nuclear medicine. Geant4 is continuously evolving, so it is crucial to have a system that benchmarks this Monte Carlo code for medical physics against reference data and to perform regression testing. To respond to these needs, we developed G4-Med, a benchmarking and regression testing system of Geant4 for medical physics, that currently includes 18 tests. They range from the benchmarking of fundamental physics quantities to the testing of Monte Carlo simulation setups typical of medical physics applications. Both electromagnetic and hadronic physics processes and models within the pre-built, Geant4 physics lists are tested. The tests included in G4-Med are executed on the CERN computing infrastructure via the use of the geant-val web application, developed at CERN for Geant4 testing. The physical observables can be compared to reference data for benchmarking and to results of previous Geant4 versions for regression testing purposes. This paper describes the tests included in G4-Med and shows the results derived from the benchmarking of Geant4 10.5 against reference data. The results presented and discussed in this paper will aid users in tailoring physics lists to their particular application.

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Patient‐derived heterogeneous breast phantoms for advanced dosimetry in mammography and tomosynthesis

et al. 2022

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Background Understanding the magnitude and variability of the radiation dose absorbed by the breast fibroglandular tissue during mammography and digital breast tomosynthesis (DBT) is of paramount importance to assess risks versus benefits. Although homogeneous breast models have been proposed and used for decades for this purpose, they do not accurately reflect the actual heterogeneous distribution of the fibroglandular tissue in the breast, leading to biases in the estimation of dose from these modalities. Purpose To develop and validate a method to generate patient‐derived, heterogeneous digital breast phantoms for breast dosimetry in mammography and DBT. Methods The proposed phantoms were developed starting from patient‐based models of compressed breasts, generated for multiple thicknesses and representing the two standard views acquired in mammography and DBT, that is, cranio‐caudal (CC) and medio‐lateral‐oblique (MLO). Internally, the breast phantoms were defined as consisting of an adipose/fibroglandular tissue mixture, with a nonspatially uniform relative concentration. The parenchyma distributions were obtained from a previously described model based on patient breast computed tomography data that underwent simulated compression. Following these distributions, phantoms with any glandular fraction (1%–100%) and breast thickness (12–125 mm) can be generated, for both views. The phantoms were validated, in terms of their accuracy for average normalized glandular dose (DgN) estimation across samples of patient breasts, using 88 patient‐specific phantoms involving actual patient distribution of the fibroglandular tissue in the breast, and compared to that obtained using a homogeneous model similar to those currently used for breast dosimetry. Results The average DgN estimated for the proposed phantoms was concordant with that absorbed by the patient‐specific phantoms to within 5% (CC) and 4% (MLO). These DgN estimates were over 30% lower than those estimated with the homogeneous models, which overestimated the average DgN by 43% (CC), and 32% (MLO) compared to the patient‐specific phantoms. Conclusions The developed phantoms can be used for dosimetry simulations to improve the accuracy of dose estimates in mammography and DBT.

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Internal breast dosimetry in mammography: Experimental methods and Monte Carlo validation with a monoenergetic x‐ray beam

Cited by 15 publications

References 49 publications

Internal breast dosimetry in mammography: Monte Carlo validation in homogeneous and anthropomorphic breast phantoms with a clinical mammography system

Internal breast dosimetry in mammography: Monte Carlo validation in homogeneous and anthropomorphic breast phantoms with a clinical mammography system

Report on G4‐Med, a Geant4 benchmarking system for medical physics applications developed by the Geant4 Medical Simulation Benchmarking Group

Patient‐derived heterogeneous breast phantoms for advanced dosimetry in mammography and tomosynthesis

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