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Okkalidis N, Bliznakova K. A voxel-by-voxel method for mixing two filaments during a 3D printing process for soft-tissue replication in an anthropomorphic breast phantom. Phys Med Biol 2022; 67. [PMID: 36541511 DOI: 10.1088/1361-6560/aca640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 11/25/2022] [Indexed: 11/26/2022]
Abstract
Objective. In this study, a novel voxel-by-voxel mixing method is presented, according to which two filaments of different material are combined during the three dimensional (3D) printing process.Approach. In our approach, two types of filaments were used for the replication of soft-tissues, a polylactic acid (PLA) filament and a polypropylene (PP) filament. A custom-made software was used, while a series of breast patient CT scan images were directly associated to the 3D printing process. Each phantom´s layer was printed twice, once with the PLA filament and a second time with the PP filament. For each material, the filament extrusion rate was controlled voxel-by-voxel and was based on the Hounsfield units (HU) of the imported CT images. The phantom was scanned at clinical CT, breast tomosynthesis and micro CT facilities, as the major processing was performed on data from the CT. A side by side comparison between patient´s and phantom´s CT slices by means of profile and histogram comparison was accomplished. Further, in case of profile comparison, the Pearson´s coefficients were calculated.Main results. The visual assessment of the distribution of the glandular tissue in the CT slices of the printed breast anatomy showed high degree of radiological similarity to the corresponding patient´s glandular distribution. The profile plots´ comparison showed that the HU of the replicated and original patient soft tissues match adequately. In overall, the Pearson´s coefficients were above 0.91, suggesting a close match of the CT images of the phantom with those of the patient. The overall HU were close in terms of HU ranges. The HU mean, median and standard deviation of the original and the phantom CT slices were -149, -167, ±65 and -121, -130, ±91, respectively.Significance. The results suggest that the proposed methodology is appropriate for manufacturing of anthropomorphic soft tissue phantoms for x-ray imaging and dosimetry purposes, since it may offer an accurate replication of these tissues.
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Affiliation(s)
- Nikiforos Okkalidis
- Research Institute, Medical University of Varna, Bulgaria.,Morphé, Praxitelous 1, Thessaloniki, Greece
| | - Kristina Bliznakova
- Department of Medical Equipment, Electronic and Information Technologies in Healthcare, Medical University of Varna, Varna, Bulgaria
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2
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Physical and digital phantoms for 2D and 3D x-ray breast imaging: Review on the state-of-the-art and future prospects. Radiat Phys Chem Oxf Engl 1993 2022. [DOI: 10.1016/j.radphyschem.2022.110715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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Caballo M, Rabin C, Fedon C, Rodríguez-Ruiz A, Diaz O, Boone JM, Dance DR, Sechopoulos I. Patient-derived heterogeneous breast phantoms for advanced dosimetry in mammography and tomosynthesis. Med Phys 2022; 49:5423-5438. [PMID: 35635844 PMCID: PMC9546119 DOI: 10.1002/mp.15785] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 04/26/2022] [Accepted: 05/24/2022] [Indexed: 12/03/2022] Open
Abstract
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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Affiliation(s)
- Marco Caballo
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands
| | - Carolina Rabin
- Instituto de Física, Facultad de Ciencias, Universidad de la República, Iguá 4225, Montevideo, 11600, Uruguay
| | - Christian Fedon
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands
| | - Alejandro Rodríguez-Ruiz
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands.,epartment of Image Guided Therapy Systems, Philips Healthcare, Veenpluis 6, 5684 PC Best, the Netherlands
| | - Oliver Diaz
- Department of Mathematics and Computer Science, University of Barcelona, Spain
| | - John M Boone
- Department of Radiology and Biomedical Engineering, University of California Davis Health, 4860 "Y" Street, suite 3100 Ellison building, Sacramento, CA, 95817, USA
| | - David R Dance
- National Co-ordinating Centre for the Physics of Mammography (NCCPM), Royal Surrey County Hospital, Department of Physics, University of Surrey, Guildford, GU2 7XH, United Kingdom
| | - Ioannis Sechopoulos
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands.,Dutch Expert Centre for Screening (LRCB), Wijchenseweg 101, 6538 SW, Nijmegen, The Netherlands.,Technical Medicine Centre, University of Twente, Hallenweg 5, 7522 NH, Enschede, The Netherlands
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Varallo A, Sarno A, Castriconi R, Mazzilli A, Loria A, Del Vecchio A, Orientale A, Pilotti IAM, D'Andria P, Bliznakova K, Ricciardi R, Mettivier G, Russo P. Fabrication of 3D printed patient-derived anthropomorphic breast phantoms for mammography and digital breast tomosynthesis: Imaging assessment with clinical X-ray spectra. Phys Med 2022; 98:88-97. [PMID: 35526373 DOI: 10.1016/j.ejmp.2022.04.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 04/08/2022] [Accepted: 04/11/2022] [Indexed: 10/18/2022] Open
Abstract
PURPOSE To design, fabricate and characterize 3D printed, anatomically realistic, compressed breast phantoms for digital mammography (DM) and digital breast tomosynthesis (DBT) x-ray imaging. MATERIALS We realized 3D printed phantoms simulating healthy breasts, via fused deposition modeling (FDM), with a layer resolution of 0.1 mm and 100% infill density, using a dual extruder printer. The digital models were derived from a public dataset of segmented clinical breast computed tomography scans. Three physical phantoms were printed in polyethylene terephthalate (PET), acrylonitrile-butadiene-styrene (ABS), or in polylactic-acid (PLA) materials, using ABS as a substitute for adipose tissue, and PLA or PET filaments for replicating glandular and skin tissues. 3D printed phantoms were imaged at three clinical centers with DM and DBT scanners, using typical spectra. Anatomical noise of the manufactured phantoms was evaluated via the estimates of the β parameter both in DM images and in images acquired via a clinical computed tomography (CT) scanner. RESULTS DM and DBT phantom images showed an inner texture qualitatively similar to the images of a clinical DM or DBT exam, suitably reproducing the glandular structure of their computational phantoms. β parameters evaluated in DM images of the manufactured phantoms ranged between 2.84 and 3.79; a lower β was calculated from the CT scan. CONCLUSIONS FDM 3D printed compressed breast phantoms have been fabricated using ABS, PLA and PET filaments. DM and DBT images with clinical x-ray spectra showed realistic textures. These phantoms appear promising for clinical applications in quality assurance, image quality and dosimetry assessments.
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Affiliation(s)
- Antonio Varallo
- University of Naples Federico II, Dept. of Physics "Ettore Pancini", Naples, Italy; INFN Division of Naples, Naples, Italy; University of Naples Federico II, Specialty School of Medical Physics, Naples, Italy
| | - Antonio Sarno
- University of Naples Federico II, Dept. of Physics "Ettore Pancini", Naples, Italy; INFN Division of Naples, Naples, Italy
| | - Roberta Castriconi
- Medical Physics Dept, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Aldo Mazzilli
- Medical Physics Dept, IRCCS San Raffaele Scientific Institute, Milan, Italy; University Hospital of Parma, Parma, Italy
| | - Alessandro Loria
- Medical Physics Dept, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | - Antonio Orientale
- University Hospital "San Giovanni di Dio Ruggi D'Aragona", Salerno, Italy
| | | | - Pasquale D'Andria
- University Hospital "San Giovanni di Dio Ruggi D'Aragona", Salerno, Italy
| | | | - Roberta Ricciardi
- University of Naples Federico II, Dept. of Physics "Ettore Pancini", Naples, Italy; INFN Division of Naples, Naples, Italy; University of Naples Federico II, Specialty School of Medical Physics, Naples, Italy
| | - Giovanni Mettivier
- University of Naples Federico II, Dept. of Physics "Ettore Pancini", Naples, Italy; INFN Division of Naples, Naples, Italy.
| | - Paolo Russo
- University of Naples Federico II, Dept. of Physics "Ettore Pancini", Naples, Italy; INFN Division of Naples, Naples, Italy
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Marinov S, Buliev I, Cockmartin L, Bosmans H, Bliznakov Z, Mettivier G, Russo P, Bliznakova K. Radiomics software for breast imaging optimization and simulation studies. Phys Med 2021; 89:114-128. [PMID: 34364255 DOI: 10.1016/j.ejmp.2021.07.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 07/07/2021] [Accepted: 07/13/2021] [Indexed: 10/20/2022] Open
Abstract
BACKGROUND AND OBJECTIVE The development, control and optimisation of new x-ray breast imaging modalities could benefit from a quantitative assessment of the resulting image textures. The aim of this work was to develop a software tool for routine radiomics applications in breast imaging, which will also be available upon request. METHODS The tool (developed in MATLAB) allows image reading, selection of Regions of Interest (ROI), analysis and comparison. Requirements towards the tool also included convenient handling of common medical and simulated images, building and providing a library of commonly applied algorithms and a friendly graphical user interface. Initial set of features and analyses have been selected after a literature search. Being open, the tool can be extended, if necessary. RESULTS The tool allows semi-automatic extracting of ROIs, calculating and processing a total of 23 different metrics or features in 2D images and/or in 3D image volumes. Computations of the features were verified against computations with other software packages performed with test images. Two case studies illustrate the applicability of the tool - (i) features on a series of 2D 'left' and 'right' CC mammograms acquired on a Siemens Inspiration system were computed and compared, and (ii) evaluation of the suitability of newly proposed and developed breast phantoms for x-ray-based imaging based on reference values from clinical mammography images. Obtained results could steer the further development of the physical breast phantoms. CONCLUSIONS A new image analysis toolbox was realized and can now be used in a multitude of radiomics applications, on both clinical and test images.
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Affiliation(s)
- Stoyko Marinov
- Medical Physics and Quality Assessment, Department of Imaging and Pathology, KU Leuven, Herestraat 49, 3000 Leuven, Belgium
| | | | - Lesley Cockmartin
- Department of Radiology, University Hospitals Leuven, Herestraat 49, 3000 Leuven, Belgium
| | - Hilde Bosmans
- Department of Radiology, University Hospitals Leuven, Herestraat 49, 3000 Leuven, Belgium; Medical Physics and Quality Assessment, Department of Imaging and Pathology, KU Leuven, Herestraat 49, 3000 Leuven, Belgium
| | - Zhivko Bliznakov
- Department of Medical Equipment, Electronic and Information Technologies in Healthcare, Medical University of Varna, Varna, Bulgaria
| | - Giovanni Mettivier
- Dipartimento di Fisica "Ettore Pancini", Universita' di Napoli Federico II and INFN Sezione di Napoli, Naples, Italy
| | - Paolo Russo
- Dipartimento di Fisica "Ettore Pancini", Universita' di Napoli Federico II and INFN Sezione di Napoli, Naples, Italy
| | - Kristina Bliznakova
- Department of Medical Equipment, Electronic and Information Technologies in Healthcare, Medical University of Varna, Varna, Bulgaria.
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Sarno A, Mettivier G, di Franco F, Varallo A, Bliznakova K, Hernandez AM, Boone JM, Russo P. Dataset of patient-derived digital breast phantoms for in silico studies in breast computed tomography, digital breast tomosynthesis, and digital mammography. Med Phys 2021; 48:2682-2693. [PMID: 33683711 DOI: 10.1002/mp.14826] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 02/22/2021] [Accepted: 02/28/2021] [Indexed: 01/10/2023] Open
Abstract
PURPOSE To present a dataset of computational digital breast phantoms derived from high-resolution three-dimensional (3D) clinical breast images for the use in virtual clinical trials in two-dimensional (2D) and 3D x-ray breast imaging. ACQUISITION AND VALIDATION METHODS Uncompressed computational breast phantoms for investigations in dedicated breast CT (BCT) were derived from 150 clinical 3D breast images acquired via a BCT scanner at UC Davis (California, USA). Each image voxel was classified in one out of the four main materials presented in the field of view: fibroglandular tissue, adipose tissue, skin tissue, and air. For the image classification, a semi-automatic software was developed. The semi-automatic classification was compared via manual glandular classification performed by two researchers. A total of 60 compressed computational phantoms for virtual clinical trials in digital mammography (DM) and digital breast tomosynthesis (DBT) were obtained from the corresponding uncompressed phantoms via a software algorithm simulating the compression and the elastic deformation of the breast, using the tissue's elastic coefficient. This process was evaluated in terms of glandular fraction modification introduced by the compression procedure. The generated cohort of 150 uncompressed computational breast phantoms presented a mean value of the glandular fraction by mass of 12.3%; the average diameter of the breast evaluated at the center of mass was 105 mm. Despite the slight differences between the two manual segmentations, the resulting glandular tissue segmentation did not consistently differ from that obtained via the semi-automatic classification. The difference between the glandular fraction by mass before and after the compression was 2.1% on average. The 60 compressed phantoms presented an average glandular fraction by mass of 12.1% and an average compressed thickness of 61 mm. DATA FORMAT AND ACCESS The generated digital breast phantoms are stored in DICOM files. Image voxels can present one out of four values representing the different classified materials: 0 for the air, 1 for the adipose tissue, 2 for the glandular tissue, and 3 for the skin tissue. The generated computational phantoms datasets were stored in the Zenodo public repository for research purposes (http://doi.org/10.5281/zenodo.4529852, http://doi.org/10.5281/zenodo.4515360). POTENTIAL APPLICATIONS The dataset developed within the INFN AGATA project will be used for developing a platform for virtual clinical trials in x-ray breast imaging and dosimetry. In addition, they will represent a valid support for introducing new breast models for dose estimates in 2D and 3D x-ray breast imaging and as models for manufacturing anthropomorphic physical phantoms.
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Affiliation(s)
| | - Giovanni Mettivier
- INFN Sezione di Napoli, Naples, Italy.,Dipartimento di Fisica "Ettore Pancini", Università di Napoli Federico II, Naples, Italy
| | - Francesca di Franco
- INFN Sezione di Napoli, Naples, Italy.,Dipartimento di Fisica "Ettore Pancini", Università di Napoli Federico II, Naples, Italy.,Léon Bérard Cancer Center, University of Lyon & CREATiS, University of Lyon, CNRS, Lyon, France
| | - Antonio Varallo
- Dipartimento di Fisica "Ettore Pancini", Università di Napoli Federico II, Naples, Italy
| | - Kristina Bliznakova
- Department of Medical Equipment, Electronic and Information Technologies in Healthcare, Medical University of Varna, Varna, Bulgaria
| | - Andrew M Hernandez
- Department of Radiology, University of California Davis, Sacramento, CA, USA
| | - John M Boone
- Department of Radiology, University of California Davis, Sacramento, CA, USA
| | - Paolo Russo
- INFN Sezione di Napoli, Naples, Italy.,Dipartimento di Fisica "Ettore Pancini", Università di Napoli Federico II, Naples, Italy
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7
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Bliznakova K. The advent of anthropomorphic three-dimensional breast phantoms for X-ray imaging. Phys Med 2020; 79:145-161. [DOI: 10.1016/j.ejmp.2020.11.025] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2020] [Revised: 11/16/2020] [Accepted: 11/19/2020] [Indexed: 10/22/2022] Open
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Esposito G, Mettivier G, Bliznakova K, Bliznakov Z, Bosmans H, Bravin A, Buliev I, Di Lillo F, Ivanov D, Minutillo M, Sarno A, Vignero J, Russo P. Investigation of the refractive index decrement of 3D printing materials for manufacturing breast phantoms for phase contrast imaging. ACTA ACUST UNITED AC 2019; 64:075008. [DOI: 10.1088/1361-6560/ab0670] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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9
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Models of breast lesions based on three-dimensional X-ray breast images. Phys Med 2019; 57:80-87. [DOI: 10.1016/j.ejmp.2018.12.012] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2018] [Revised: 11/30/2018] [Accepted: 12/17/2018] [Indexed: 02/08/2023] Open
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Narayanan D, Berg WA. Dedicated Breast Gamma Camera Imaging and Breast PET: Current Status and Future Directions. PET Clin 2018; 13:363-381. [PMID: 30100076 DOI: 10.1016/j.cpet.2018.02.008] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Recent advances in nuclear medicine instrumentation have led to the emergence of improved molecular imaging techniques to image breast cancer: dedicated gamma cameras using γ-emitting 99mTc-sestamibi and breast-specific PET cameras using 18F-fluorodeoxyglucose. This article focuses on the current role of such approaches in the clinical setting including diagnosis, assessing local extent of disease, monitoring response to therapy, and, for gamma camera imaging, possible supplemental screening in women with dense breasts. Barriers to clinical adoption and technologies and radiotracers under development are also discussed.
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Affiliation(s)
- Deepa Narayanan
- National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850, USA.
| | - Wendie A Berg
- Department of Radiology, University of Pittsburgh School of Medicine, Magee-Womens Hospital of UPMC, 300 Halket Street, Pittsburgh, PA 15213
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Normalized glandular dose coefficients in mammography, digital breast tomosynthesis and dedicated breast CT. Phys Med 2018; 55:142-148. [DOI: 10.1016/j.ejmp.2018.09.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2018] [Revised: 09/03/2018] [Accepted: 09/10/2018] [Indexed: 12/15/2022] Open
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Ivanov D, Bliznakova K, Buliev I, Popov P, Mettivier G, Russo P, Di Lillo F, Sarno A, Vignero J, Bosmans H, Bravin A, Bliznakov Z. Suitability of low density materials for 3D printing of physical breast phantoms. ACTA ACUST UNITED AC 2018; 63:175020. [DOI: 10.1088/1361-6560/aad315] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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Glick SJ, Ikejimba LC. Advances in digital and physical anthropomorphic breast phantoms for x-ray imaging. Med Phys 2018; 45:e870-e885. [DOI: 10.1002/mp.13110] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2017] [Revised: 06/05/2018] [Accepted: 06/10/2018] [Indexed: 01/27/2023] Open
Affiliation(s)
- Stephen J. Glick
- Division of Imaging, Diagnostics, and Software Reliability; Office of Science and Engineering Laboratories; Center for Devices and Radiological Health, Food and Drug Administration; Silver Spring MD 20993 USA
| | - Lynda C. Ikejimba
- Division of Imaging, Diagnostics, and Software Reliability; Office of Science and Engineering Laboratories; Center for Devices and Radiological Health, Food and Drug Administration; Silver Spring MD 20993 USA
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Homogeneous vs. patient specific breast models for Monte Carlo evaluation of mean glandular dose in mammography. Phys Med 2018; 51:56-63. [DOI: 10.1016/j.ejmp.2018.04.392] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 04/05/2018] [Accepted: 04/17/2018] [Indexed: 12/15/2022] Open
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Sarno A, Mettivier G, Tucciariello RM, Bliznakova K, Boone JM, Sechopoulos I, Di Lillo F, Russo P. Monte Carlo evaluation of glandular dose in cone-beam X-ray computed tomography dedicated to the breast: Homogeneous and heterogeneous breast models. Phys Med 2018; 51:99-107. [DOI: 10.1016/j.ejmp.2018.05.021] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Revised: 05/04/2018] [Accepted: 05/23/2018] [Indexed: 12/11/2022] Open
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