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Wang J, Liu Y, Hu A, Wu Z, Zhang H, Li J, Qiu R. THUBreast: an open-source breast phantom generation software for x-ray imaging and dosimetry. Phys Med Biol 2024; 69:065004. [PMID: 38346343 DOI: 10.1088/1361-6560/ad2881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 02/12/2024] [Indexed: 03/08/2024]
Abstract
Objective. Establishing realistic phantoms of human anatomy is a continuing concern within virtual clinical trials of breast x-ray imaging. However, little attention has been paid to glandular distribution within these phantoms. The principal objective of this study was to develop breast phantoms considering the clinical glandular distribution.Approach. This research introduces an innovative method for integrating glandular distribution information into breast phantoms. We have developed an open-source software, THUBreast44http://github.com/true02Hydrogen/THUBreast/, which generates breast phantoms that accurately replicate both the structural texture and glandular distribution, two crucial elements in breast x-ray imaging and dosimetry. To validate the efficacy of THUBreast, we assembled three groups of breast phantoms (THUBreast, patient-based, homogeneous) for irradiation simulation and calculated the power-law exponents (β) and mean glandular dose (Dg), indicators of texture realism and radiation risk, respectively, utilizing MC-GPU.Main results. Upon the computation of theDgfor the THUBreast phantoms, it was found to be in agreement with that absorbed by the phantoms based on patients, with an average deviation of 4%. The estimates of averageDgthus obtained were on average 23% less than those computed for the homogeneous phantoms. It was observed that the homogeneous phantoms did overestimate the averageDgby 30% when compared to the phantoms based on patients. The mean value ofβfor the images of THUBreast phantoms was found to be 2.92 ± 0.08, which shows a commendable agreement with the findings of prior investigations.Significance. It is evidently clear from the results that THUBreast phantoms have a preliminary good performance in both imaging and dosimetry in terms of indicators of texture realism and glandular dose. THUBreast represents a further step towards developing a powerful toolkit for comprehensive evaluation of image quality and radiation risk.
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Affiliation(s)
- Jiahao Wang
- Department of Engineering Physics, Tsinghua University, Beijing 100084, People's Republic of China
- Key Laboratory of Particle and Radiation Imaging, Tsinghua University, Ministry of Education, Beijing 100084, People's Republic of China
| | - Yeqi Liu
- Department of Engineering Physics, Tsinghua University, Beijing 100084, People's Republic of China
- Key Laboratory of Particle and Radiation Imaging, Tsinghua University, Ministry of Education, Beijing 100084, People's Republic of China
| | - Ankang Hu
- Department of Engineering Physics, Tsinghua University, Beijing 100084, People's Republic of China
- Key Laboratory of Particle and Radiation Imaging, Tsinghua University, Ministry of Education, Beijing 100084, People's Republic of China
| | - Zhen Wu
- Joint Institute of Tsinghua University & Nuctech Company Limited Beijing, People's Republic of China
| | - Hui Zhang
- Department of Engineering Physics, Tsinghua University, Beijing 100084, People's Republic of China
- Key Laboratory of Particle and Radiation Imaging, Tsinghua University, Ministry of Education, Beijing 100084, People's Republic of China
| | - Junli Li
- Department of Engineering Physics, Tsinghua University, Beijing 100084, People's Republic of China
- Key Laboratory of Particle and Radiation Imaging, Tsinghua University, Ministry of Education, Beijing 100084, People's Republic of China
| | - Rui Qiu
- Department of Engineering Physics, Tsinghua University, Beijing 100084, People's Republic of China
- Key Laboratory of Particle and Radiation Imaging, Tsinghua University, Ministry of Education, Beijing 100084, People's Republic of China
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Simson WA, Paschali M, Sideri-Lampretsa V, Navab N, Dahl JJ. Investigating pulse-echo sound speed estimation in breast ultrasound with deep learning. ULTRASONICS 2024; 137:107179. [PMID: 37939413 PMCID: PMC10842235 DOI: 10.1016/j.ultras.2023.107179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 09/30/2023] [Accepted: 10/07/2023] [Indexed: 11/10/2023]
Abstract
Ultrasound is an adjunct tool to mammography that can quickly and safely aid physicians in diagnosing breast abnormalities. Clinical ultrasound often assumes a constant sound speed to form diagnostic B-mode images. However, the components of breast tissue, such as glandular tissue, fat, and lesions, differ in sound speed. Given a constant sound speed assumption, these differences can degrade the quality of reconstructed images via phase aberration. Sound speed images can be a powerful tool for improving image quality and identifying diseases if properly estimated. To this end, we propose a supervised deep-learning approach for sound speed estimation from analytic ultrasound signals. We develop a large-scale simulated ultrasound dataset that generates representative breast tissue samples by modeling breast gland, skin, and lesions with varying echogenicity and sound speed. We adopt a fully convolutional neural network architecture trained on a simulated dataset to produce an estimated sound speed map. The simulated tissue is interrogated with a plane wave transmit sequence, and the complex-value reconstructed images are used as input for the convolutional network. The network is trained on the sound speed distribution map of the simulated data, and the trained model can estimate sound speed given reconstructed pulse-echo signals. We further incorporate thermal noise augmentation during training to enhance model robustness to artifacts found in real ultrasound data. To highlight the ability of our model to provide accurate sound speed estimations, we evaluate it on simulated, phantom, and in-vivo breast ultrasound data.
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Affiliation(s)
- Walter A Simson
- Chair for Computer Aided Medical Procedures and Augmented Reality, Technical University of Munich, Munich, Germany; Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA.
| | - Magdalini Paschali
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Vasiliki Sideri-Lampretsa
- Institute for Artificial Intelligence and Informatics in Medicine, Technical University of Munich, Munich, Germany
| | - Nassir Navab
- Chair for Computer Aided Medical Procedures and Augmented Reality, Technical University of Munich, Munich, Germany; Chair for Computer Aided Medical Procedures, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jeremy J Dahl
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA
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Monnin P, Damet J, Bosmans H, Marshall NW. Task-based detectability in anatomical background in digital mammography, digital breast tomosynthesis and synthetic mammography. Phys Med Biol 2024; 69:025017. [PMID: 38214048 DOI: 10.1088/1361-6560/ad1766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 12/20/2023] [Indexed: 01/13/2024]
Abstract
Objective.Determining the detectability of targets for the different imaging modalities in mammography in the presence of anatomical background noise is challenging. This work proposes a method to compare the image quality and detectability of targets in digital mammography (DM), digital breast tomosynthesis (DBT) and synthetic mammography.Approach. The low-frequency structured noise produced by a water phantom with acrylic spheres was used to simulate anatomical background noise for the different types of images. A method was developed to apply the non-prewhitening observer model with eye filter (NPWE) in these conditions. A homogeneous poly(methyl) methacrylate phantom with a 0.2 mm thick aluminium disc was used to calculate 2D in-plane modulation transfer function (MTF), noise power spectrum (NPS), noise equivalent quanta, and system detective quantum efficiency for 30, 50 and 70 mm thicknesses. The in-depth MTFs of DBT volumes were determined using a thin tungsten wire. The MTF, system NPS and anatomical NPS were used in the NPWE model to calculate the threshold gold thickness of the gold discs contained in the CDMAM phantom, which was taken as reference. Main results.The correspondence between the NPWE model and the CDMAM phantom (linear Pearson correlation 0.980) yielded a threshold detectability index that was used to determine the threshold diameter of spherical microcalcifications and masses. DBT imaging improved the detection of masses, which depended mostly on the reduction of anatomical background noise. Conversely, DM images yielded the best detection of microcalcifications.Significance.The method presented in this study was able to quantify image quality and object detectability for the different imaging modalities and levels of anatomical background noise.
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Affiliation(s)
- P Monnin
- Institute of radiation physics (IRA), Lausanne University Hospital (CHUV) and University of Lausanne, Rue du Grand-Pré 1, 1007 Lausanne, Switzerland
| | - J Damet
- Institute of radiation physics (IRA), Lausanne University Hospital (CHUV) and University of Lausanne, Rue du Grand-Pré 1, 1007 Lausanne, Switzerland
| | - H Bosmans
- UZ Gasthuisberg, Department of Radiology, Herestraat 49, 3000 Leuven, Belgium
- Medical Imaging Research Center, Medical Physics and Quality Assessment, Katholieke Universiteit Leuven, 3000 Leuven, Belgium
| | - N W Marshall
- UZ Gasthuisberg, Department of Radiology, Herestraat 49, 3000 Leuven, Belgium
- Medical Imaging Research Center, Medical Physics and Quality Assessment, Katholieke Universiteit Leuven, 3000 Leuven, Belgium
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Bermúdez J, Roque G, Calderón J, Pardo P, Sánchez M, Ramos V, Ávila C. 3D phantom for image quality assessment of mammography systems. Phys Med Biol 2023; 68:205019. [PMID: 37733054 DOI: 10.1088/1361-6560/acfc10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 09/21/2023] [Indexed: 09/22/2023]
Abstract
Objective.To present an innovative approach for the design of a 3D mammographic phantom for medical equipment quality assessment, estimation of the glandular tissue percentage in the patient's breast, and emulation of microcalcification (μC) breast lesions.Approach.Contrast-to noise ratio (CNR) measurements, as well as spatial resolution and intensity-to-glandularity calibrations under mammography conditions were performed to assess the effectiveness of the phantom. CNR measurements were applied to different groups of calcium hydroxyapatite (HA) and aluminum oxide (AO)μCs ranging from 200 to 600μm. Spatial resolution was characterized using an aluminum plate contained in the phantom and standard linear figures of merit, such as the line spread function and modulation transfer function (MTF). The intensity-to-glandularity calibration was developed using an x-ray attenuation matrix within the phantom to estimate the glandular tissue percentage in a breast with a compressed thickness of 4 cm.Main results.For the prototype studied, the minimum confidence level for detecting HAμCs is 95.4%, while for AOμCs is above 68.3%. It was also possible to determine that the MTF of the commercial mammography machine used for this study at the Nyquist frequency is 41%. Additionally, a one-to-one intensity-to-glandularity calibration was obtained and verified with Monte-Carlo simulation results.Significance.The phantom provides traditional arrangements presented in accreditation phantoms, which makes it competitive with available devices, but excelling in regarding affordability, modularity, and inlays distribution. Moreover, its design allows to be positioned in close proximity to the patient's breast during a medical screening for a simultaneous x-ray imaging, such that the features of the phantom can be used as reference values to specify characteristics of the real breast tissue, such as proportion of glandular/adipose composition and/orμC type and size lesions.
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Affiliation(s)
- J Bermúdez
- Physics Department, Universidad de los Andes, Bogotá, Colombia
| | - G Roque
- Physics Department, Universidad de los Andes, Bogotá, Colombia
| | - J Calderón
- Physics Department, Universidad de los Andes, Bogotá, Colombia
| | - P Pardo
- Physics Department, Universidad de los Andes, Bogotá, Colombia
| | - M Sánchez
- Physics Department, Universidad de los Andes, Bogotá, Colombia
| | - V Ramos
- Hospital Universitario San Ignacio (HUSI), Bogotá, Colombia
| | - C Ávila
- Physics Department, Universidad de los Andes, Bogotá, Colombia
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Li Z, Carton AK, Muller S, Almecija T, de Carvalho PM, Desolneux A. A 3D Mathematical Breast Texture Model With Parameters Automatically Inferred From Clinical Breast CT Images. IEEE TRANSACTIONS ON MEDICAL IMAGING 2023; 42:1107-1120. [PMID: 36417739 DOI: 10.1109/tmi.2022.3224223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
A numerical realistic 3D anthropomorphic breast model is useful for evaluating breast imaging applications. A method is proposed to model small and medium-scale fibroglandular and intra-glandular adipose tissues observed in the center part of clinical breast CT images. The method builds upon a previously proposed model formulated as stochastic geometric processes with mathematically tractable parameters. In this work, the medium-scale parameters were automatically and objectively inferred from breast CT images. We hypothesized that a set of random ellipsoids exhibiting cluster interaction is representative to model the medium-scale intra-glandular adipose compartments. The ellipsoids were reconstructed using a multiple birth, death and shift algorithm. Then, a Matérn cluster process was used to fit the reconstructed ellipsoid centers. Finally, distributions of the ellipsoid shapes and orientations were estimated using maximum likelihood estimators. Feasibility was demonstrated on 16 volumes of interests (VOI). To assess the realism of the 3D breast texture model, β and LFE metrics computed in simulated projection images of simulated texture realizations and clinical images were compared. Visual realism was illustrated. For 12 out of 16 VOIs, our hypothesis on clustering interaction process is confirmed. The average β values from simulated texture images (3.7 to 4.2) of the 12 different VOIs are higher than the average β value from 2D clinical images (2.87). LFE of simulated texture images and clinical mammograms are similar. Compared to our previous model, whereby simulation parameters were based upon empirical observations, our inference method substantially augments the ability to generate textures with higher visual realism and larger morphological variety.
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Kadry S. Three-dimensional reconstruction system in pulmonary broncho vascular surgery using AI. EBioMedicine 2023; 89:104495. [PMID: 36848697 PMCID: PMC9984767 DOI: 10.1016/j.ebiom.2023.104495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 02/09/2023] [Indexed: 03/01/2023] Open
Affiliation(s)
- Seifedine Kadry
- Artificial Intelligence Research Center (AIRC), Ajman University, Ajman, 346, United Arab Emirates; Department of Electrical and Computer Engineering, Lebanese American University, Byblos, Lebanon; Department of Applied Data Science, Noroff University College, Kristiansand 4612, Norway.
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Saleh G, Abuelhaija A, Alfaris B, Aljabr A, Zainalabedin M, Mhareb MHA, Alhashim M, Alenezi S. Heterogeneous breast phantom for computed tomography and magnetic resonance imaging. PLoS One 2023; 18:e0284531. [PMID: 37053345 PMCID: PMC10101397 DOI: 10.1371/journal.pone.0284531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Accepted: 04/02/2023] [Indexed: 04/15/2023] Open
Abstract
In this article, a heterogeneous multimodal anthropomorphic breast phantom with carcinoma is introduced to meet the response of the natural breast tissue when imaged using ionizing and non-ionizing machines. The skin, adipose, fibroglandular, pectoral muscle, and carcinoma tissue were mimicked. A T1-weighted breast magnetic resonance image with BI-RADS I tissue segmentation was used for molds creation. The tissue-mimicking materials (TMMs) were tailored in terms of their elemental composition weight fractions and their response to ionization radiation parameters. These are the mass attenuation coefficient (MAC), electron density (ne) and effective atomic number (Zeff). The behaviour of the TMMs, when exposed to a wide range of ionization radiation energy, was investigated analytically and numerically using X-COM. The achieved results showed an excellent agreement with the corresponding properties of the natural breast elemental compositions as reported by the International Commission on Radiation Units and Measurements (ICRU). The MAC of the TMMs and the ICRU-based breast tissue were found to be consistent. The maximum percentage of error in ne and Zeff amounts to only 2.93% and 5.76%, respectively. For non-ionizing imaging, the TMMs were characterized in term of T1 and T2 relaxation times. Using our preclinical MRI unit, the TMMs relaxation times were measured and compared to the natural tissue. The fabricated phantom was validated experimentally using CT, MRI, and Mammographic machines. The achieved images of the TMMs were in alignment with the real tissue in terms of CT HU values and grayscale colors. T1W and T2W images on MRI revealed the expected contrast between TMMs as in natural tissue.
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Affiliation(s)
- Gameel Saleh
- Department of Biomedical Engineering, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Ashraf Abuelhaija
- Department of Electrical Engineering, Faculty of Engineering and Technology, Applied Science Private University, Amman, Jordan
| | - Budour Alfaris
- Department of Biomedical Engineering, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Aljohara Aljabr
- Department of Biomedical Engineering, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Maryam Zainalabedin
- Department of Biomedical Engineering, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - M H A Mhareb
- Department of Physics, College of Science, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | | | - Salma Alenezi
- King Fahad Specialist Hospital (KFSH), Dammam, Saudi Arabia
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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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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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10
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Marshall NW, Bosmans H. Performance evaluation of digital breast tomosynthesis systems: physical methods and experimental data. Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac9a35] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 10/13/2022] [Indexed: 11/17/2022]
Abstract
Abstract
Digital breast tomosynthesis (DBT) has become a well-established breast imaging technique, whose performance has been investigated in many clinical studies, including a number of prospective clinical trials. Results from these studies generally point to non-inferiority in terms of microcalcification detection and superior mass-lesion detection for DBT imaging compared to digital mammography (DM). This modality has become an essential tool in the clinic for assessment and ad-hoc screening but is not yet implemented in most breast screening programmes at a state or national level. While evidence on the clinical utility of DBT has been accumulating, there has also been progress in the development of methods for technical performance assessment and quality control of these imaging systems. DBT is a relatively complicated ‘pseudo-3D’ modality whose technical assessment poses a number of difficulties. This paper reviews methods for the technical performance assessment of DBT devices, starting at the component level in part one and leading up to discussion of system evaluation with physical test objects in part two. We provide some historical and basic theoretical perspective, often starting from methods developed for DM imaging. Data from a multi-vendor comparison are also included, acquired under the medical physics quality control protocol developed by EUREF and currently being consolidated by a European Federation of Organisations for Medical Physics working group. These data and associated methods can serve as a reference for the development of reference data and provide some context for clinical studies.
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Mettivier G, Sarno A, Varallo A, Russo P. Attenuation coefficient in the energy range 14–36 keV of 3D printing materials for physical breast phantoms. Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac8966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 08/12/2022] [Indexed: 11/11/2022]
Abstract
Abstract
Objective. To measure the monoenergetic x-ray linear attenuation coefficient, μ, of fused deposition modeling (FDM) colored 3D printing materials (ABS, PLAwhite, PLAorange, PET and NYLON), used as adipose, glandular or skin tissue substitutes for manufacturing physical breast phantoms. Approach. Attenuation data (at 14, 18, 20, 24, 28, 30 and 36 keV) were acquired at Elettra synchrotron radiation facility, with step-wedge objects, using the Lambert–Beer law and a CCD imaging detector. Test objects were 3D printed using the Ultimaker 3 FDM printer. PMMA, Nylon-6 and high-density polyethylene step objects were also investigated for the validation of the proposed methodology. Printing uniformity was assessed via monoenergetic and polyenergetic imaging (32 kV, W/Rh). Main results. Maximum absolute deviation of μ for PMMA, Nylon-6 and HD-PE was 5.0%, with reference to literature data. For ABS and NYLON, μ differed by less than 6.1% and 7.1% from that of adipose tissue, respectively; for PET and PLAorange the difference was less than 11.3% and 6.3% from glandular tissue, respectively. PLAorange is a good substitute of skin (differences from −9.4% to +1.2%). Hence, ABS and NYLON filaments are suitable adipose tissue substitutes, while PET and PLAorange mimick the glandular tissue. PLAwhite could be printed at less than 100% infill density for matching the attenuation of glandular tissue, using the measured density calibration curve. The printing mesh was observed for sample thicknesses less than 60 mm, imaged in the direction normal to the printing layers. Printing dimensional repeatability and reproducibility was less 1%. Significance. For the first time an experimental determination was provided of the linear attenuation coefficient of common 3D printing filament materials with estimates of μ at all energies in the range 14–36 keV, for their use in mammography, breast tomosynthesis and breast computed tomography investigations.
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Okkalidis N. 3D printing methods for radiological anthropomorphic phantoms. Phys Med Biol 2022; 67. [PMID: 35830787 DOI: 10.1088/1361-6560/ac80e7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Accepted: 07/13/2022] [Indexed: 01/06/2023]
Abstract
Three dimensional (3D) printing technology has been widely evaluated for the fabrication of various anthropomorphic phantoms during the last couple of decades. The demand for such high quality phantoms is constantly rising and gaining an ever-increasing interest. Although, in a short time 3D printing technology provided phantoms with more realistic features when compared to the previous conventional methods, there are still several aspects to be explored. One of these aspects is the further development of the current 3D printing methods and software devoted to radiological applications. The current 3D printing software and methods usually employ 3D models, while the direct association of medical images with the 3D printing process is needed in order to provide results of higher accuracy and closer to the actual tissues' texture. Another aspect of high importance is the development of suitable printing materials. Ideally, those materials should be able to emulate the entire range of soft and bone tissues, while still matching the human's anatomy. Five types of 3D printing methods have been mainly investigated so far: (a) solidification of photo-curing materials; (b) deposition of melted plastic materials; (c) printing paper-based phantoms with radiopaque ink; (d) melting or binding plastic powder; and (e) bio-printing. From the first and second category, polymer jetting technology and fused filament fabrication (FFF), also known as fused deposition modelling (FDM), are the most promising technologies for the fulfilment of the requirements of realistic and radiologically equivalent anthropomorphic phantoms. Another interesting approach is the fabrication of radiopaque paper-based phantoms using inkjet printers. Although, this may provide phantoms of high accuracy, the utilized materials during the fabrication process are restricted to inks doped with various contrast materials. A similar condition applies to the polymer jetting technology, which despite being quite fast and very accurate, the utilized materials are restricted to those capable of polymerization. The situation is better for FFF/FDM 3D printers, since various compositions of plastic filaments with external substances can be produced conveniently. Although, the speed and accuracy of this 3D printing method are lower compared to the others, the relatively low-cost, constantly improving resolution, sufficient printing volume and plethora of materials are quite promising for the creation of human size heterogeneous phantoms and their adaptation to the treatment procedures of patients in the current health systems.
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Affiliation(s)
- Nikiforos Okkalidis
- Research Institute, Medical University of Varna, Bulgaria.,Morphé, Praxitelous 1, Thessaloniki, Greece
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Mackenzie A, Boita J, Dance DR, Young KC. Development of an algorithm to convert mammographic images to appear as if acquired with different technique factors. J Med Imaging (Bellingham) 2022; 9:033504. [DOI: 10.1117/1.jmi.9.3.033504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 05/12/2022] [Indexed: 11/14/2022] Open
Affiliation(s)
- Alistair Mackenzie
- Royal Surrey NHS Foundation Trust, National Coordinating Centre for the Physics of Mammography, Guil
| | - Joana Boita
- Radboud University Medical Centre, Department of Medical Imaging, Nijmegen
| | - David R. Dance
- Royal Surrey NHS Foundation Trust, National Coordinating Centre for the Physics of Mammography, Guil
| | - Kenneth C. Young
- Royal Surrey NHS Foundation Trust, National Coordinating Centre for the Physics of Mammography, Guil
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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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15
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Barufaldi B, Vent TL, Bakic PR, Maidment ADA. Computer Simulations of Case Difficulty in Digital Breast Tomosynthesis Using Virtual Clinical Trials. Med Phys 2022; 49:2220-2232. [PMID: 35212403 DOI: 10.1002/mp.15553] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 02/07/2022] [Accepted: 02/13/2022] [Indexed: 11/10/2022] Open
Abstract
PURPOSE Virtual clinical trials (VCTs) require computer simulations of representative patients and images to evaluate and compare changes in performance of imaging technologies. The simulated images are usually interpreted by model observers whose performance depends upon the selection of imaging cases used in training evaluation models. This work proposes an efficient method to simulate and calibrate soft tissue lesions, which matches the detectability threshold of virtual and human readings. METHODS Anthropomorphic breast phantoms were used to evaluate the simulation of four mass models (I-IV) that vary in shape and composition of soft tissue. Ellipsoidal (I) and spiculated (II-IV) masses were simulated using composite voxels with partial volumes. Digital breast tomosynthesis projections and reconstructions of a clinical system were simulated. Channelized Hotelling observers (CHOs) were evaluated using reconstructed slices of masses that varied in shape, composition, and density of surrounded tissue. The detectability threshold of each mass model was evaluated using receiver operating characteristic (ROC) curves calculated with the CHO's scores. RESULTS The area under the curve (AUC) of each calibrated mass model were within the 95% confidence interval (mean AUC [95% CI]) reported in a previous reader study (0.93 [0.89, 0.97]). The mean AUC [95% CI] obtained were 0.94 [0.93, 0.96], 0.92 [0.90, 0.93], 0.92 [0.90, 0.94], 0.93 [0.92, 0.95] for models I to IV, respectively. The mean AUC results varied substantially as a function of shape, composition, and density of surrounded tissue. CONCLUSIONS For successful VCTs, lesions composed of soft tissue should be calibrated to simulate imaging cases that match the case difficulty predicted by human readers. Lesion composition, shape, and size are parameters that should be carefully selected to calibrate VCTs. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Bruno Barufaldi
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, United States
| | - Trevor L Vent
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, United States
| | - Predrag R Bakic
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, United States.,Department of Translational Medicine, Lund University, Malmö, 20502, Sweden
| | - Andrew D A Maidment
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, United States
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16
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Dukov N, Bliznakova K, Okkalidis N, Teneva T, Encheva E, Bliznakov Z. Thermoplastic 3D printing technology using a single filament for producing realistic patient-derived breast models. Phys Med Biol 2022; 67. [PMID: 35038693 DOI: 10.1088/1361-6560/ac4c30] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 01/17/2022] [Indexed: 12/29/2022]
Abstract
Objective. This work describes an approach for producing physical anthropomorphic breast phantoms from clinical patient data using three-dimensional (3D) fused-deposition modelling (FDM) printing.Approach. The source of the anthropomorphic model was a clinical Magnetic Resonance Imaging (MRI) patient image set, which was segmented slice by slice into adipose and glandular tissues, skin and tumour formations; thus obtaining a four component computational breast model. The segmented tissues were mapped to specific Hounsfield Units (HU) values, which were derived from clinical breast Computed Tomography (CT) data. The obtained computational model was used as a template for producing a physical anthropomorphic breast phantom using 3D printing. FDM technology with only one polylactic acid filament was used. The physical breast phantom was scanned at Siemens SOMATOM Definition CT. Quantitative and qualitative evaluation were carried out to assess the clinical realism of CT slices of the physical breast phantom.Main results. The comparison between selected slices from the computational breast phantom and CT slices of the physical breast phantom shows similar visual x-ray appearance of the four breast tissue structures: adipose, glandular, tumour and skin. The results from the task-based evaluation, which involved three radiologists, showed a high degree of realistic clinical radiological appearance of the modelled breast components. Measured HU values of the printed structures are within the range of HU values used in the computational phantom. Moreover, measured physical parameters of the breast phantom, such as weight and linear dimensions, agreed very well with the corresponding ones of the computational breast model.Significance. The presented approach, based on a single FDM material, was found suitable for manufacturing of a physical breast phantom, which mimics well the 3D spatial distribution of the different breast tissues and their x-ray absorption properties. As such, it could be successfully exploited in advanced x-ray breast imaging research applications.
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Affiliation(s)
- Nikolay Dukov
- Department of Medical Equipment, Electronic and Information Technologies in Healthcare, Medical University of Varna, Varna, Bulgaria
| | - Kristina Bliznakova
- Department of Medical Equipment, Electronic and Information Technologies in Healthcare, Medical University of Varna, Varna, Bulgaria
| | | | - Tsvetelina Teneva
- Department of Imaging Diagnostics, Interventional Radiology and Radiotherapy, Medical University of Varna, Bulgaria
| | - Elitsa Encheva
- Department of Imaging Diagnostics, Interventional Radiology and Radiotherapy, Medical University of Varna, Bulgaria
| | - Zhivko Bliznakov
- Department of Medical Equipment, Electronic and Information Technologies in Healthcare, Medical University of Varna, Varna, Bulgaria
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17
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Fitton I, Noel A, Minassian J, Zerhouni M, Wojak J, Adel M, Fournier L. Technical note: Design and initial evaluation of a novel physical breast phantom to monitor image quality in digital breast tomosynthesis. Med Phys 2022; 49:2355-2365. [DOI: 10.1002/mp.15498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 12/08/2021] [Accepted: 01/17/2022] [Indexed: 11/10/2022] Open
Affiliation(s)
- Isabelle Fitton
- Radiology department AP‐HP Hôpital européen Georges Pompidou Paris F‐75015 France
| | | | | | | | - Julien Wojak
- Aix Marseille Univ CNRS Centrale Marseille Institut Fresnel Marseille France
| | - Mouloud Adel
- Aix Marseille Univ CNRS Centrale Marseille Institut Fresnel Marseille France
| | - Laure Fournier
- Radiology department AP‐HP Hôpital européen Georges Pompidou Paris F‐75015 France
- Université de Paris PARCC INSERM Paris F‐75015 France
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18
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Polat A, Kumrular RK. A Realistic Breast Phantom Proposal for 3D Image Reconstruction in Digital Breast Tomosynthesis. Technol Cancer Res Treat 2022; 21:15330338221104567. [PMID: 36071652 PMCID: PMC9459460 DOI: 10.1177/15330338221104567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Objectives: Iterative (eg, simultaneous algebraic reconstruction
technique [SART]) and analytical (eg, filtered back projection [FBP]) image
reconstruction techniques have been suggested to provide adequate
three-dimensional (3D) images of the breast for capturing microcalcifications in
digital breast tomosynthesis (DBT). To decide on the reconstruction method in
clinical DBT, it must first be tested in a simulation resembling the real
clinical environment. The purpose of this study is to introduce a 3D realistic
breast phantom for determining the reconstruction method in clinical
applications. Methods: We designed a 3D realistic breast phantom
with varying dimensions (643-5123) mimicking some
structures of a real breast such as milk ducts, lobules, and ribs using
TomoPhantom software. We generated microcalcifications, which mimic cancerous
cells, with a separate MATLAB code and embedded them into the phantom for
testing and benchmark studies in DBT. To validate the characterization of the
phantom, we tested the distinguishability of microcalcifications by performing
3D image reconstruction methods (SART and FBP) using Laboratory of Computer
Vision (LAVI) open-source reconstruction toolbox. Results: The
creation times of the proposed realistic breast phantom were seconds of 2.5916,
8.4626, 57.6858, and 472.1734 for 643, 1283,
2563, and 5123, respectively. We presented
reconstructed images and quantitative results of the phantom for SART (1-2-4-8
iterations) and FBP, with 11 to 23 projections. We determined qualitatively and
quantitatively that SART (2-4 iter.) yields better results than FBP. For
example, for 23 projections, the contrast-to-noise ratio (CNR) values of SART (2
iter.) and FBP were 2.871 and 0.497, respectively. Conclusions: We
created a computationally efficient realistic breast phantom that is eligible
for reconstruction and includes anatomical structures and microcalcifications,
successfully. By proposing this breast phantom, we provided the opportunity to
test which reconstruction methods can be used in clinical applications vary
according to various parameters such as the No. of iterations and projections in
DBT.
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Affiliation(s)
- Adem Polat
- 52950Department of Electrical-Electronics Engineering, Çanakkale Onsekiz Mart University, Çanakkale, Turkey
| | - Raziye Kubra Kumrular
- Institute of Sound and Vibration Research, 7423University of Southampton, Southampton, UK
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19
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Chen J, Li CX, Shao SH, Yao MH, Su YJ, Wu R. The association between conventional ultrasound and contrast-enhanced ultrasound appearances and pathological features in small breast cancer. Clin Hemorheol Microcirc 2021; 80:413-422. [PMID: 34842181 DOI: 10.3233/ch-211291] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
OBJECTIVE To investigate the association between ultrasound appearances and pathological features in small breast cancer. MATERIALS AND METHODS A total of 186 small breast cancers in 186 patients were analyzed in this retrospective study from January 2015 to December 2019 according to pathological results. Forty-seven cases of axillary lymph node metastasis were found. All patients underwent radical axillary surgery following conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS) examinations. The association between ultrasound appearances and pathological features was analyzed using univariate distributions and multivariate analysis. Then, a logistic regression model was established using the pathological diagnosis of lymph node metastasis and biochemical indicators as the dependent variable and the ultrasound appearances as independent variables. RESULTS In small breast cancer, risk factors of axillary lymph node metastasis were crab claw-like enhancement on CEUS and abnormal axillary lymph nodes on US. The logistic regression model was established as follows: (axillary lymph node metastasis) = 1.100×(crab claw-like enhancement of CEUS) + 2.749×(abnormal axillary lymph nodes of US) -5.790. In addition, irregular shape on CEUS and posterior echo attenuation on US were risk factors for both positive estrogen receptor and progesterone receptor expression, whereas calcification on US was a risk factor for positive Her-2 expression. A specific relationship could be found using the following logistic models: (positive ER expression) = 1.367×(irregular shape of CEUS) + 1.441×(posterior echo attenuation of US) -5.668; (positive PR expression) = 1.265×(irregular shape of CEUS) + 1.136×(posterior echo attenuation of US) -4.320; (positive Her-2 expression) = 1.658×(calcification of US) -0.896. CONCLUSION Logistic models were established to provide significant value for the prediction of pre-operative lymph node metastasis and positive biochemical indicators, which may guide clinical treatment.
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Affiliation(s)
- Jing Chen
- Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chun-Xiao Li
- Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Si-Hui Shao
- Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ming-Hua Yao
- Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yi-Jin Su
- Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Rong Wu
- Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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20
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Mackenzie A, Kaur S, Thomson EL, Mitchell M, Elangovan P, Warren LM, Dance DR, Young KC. Effect of glandularity on the detection of simulated cancers in planar, tomosynthesis, and synthetic 2D imaging of the breast using a hybrid virtual clinical trial. Med Phys 2021; 48:6859-6868. [PMID: 34496038 DOI: 10.1002/mp.15216] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 07/19/2021] [Accepted: 08/26/2021] [Indexed: 12/15/2022] Open
Abstract
PURPOSE The purpose of this study was to measure the threshold diameter of calcifications and masses for 2D imaging, digital breast tomosynthesis (DBT), and synthetic 2D images, for a range of breast glandularities. This study shows the limits of detection for each of the technologies and the strengths and weaknesses of each in terms of visualizing the radiological features of small cancers. METHODS Mathematical voxel breast phantoms with glandularities by volume of 9%, 18%, and 30% with a thickness of 53 mm were created. Simulated ill-defined masses and calcification clusters with a range of diameters were inserted into some of these breast models. The imaging characteristics of a Siemens Inspiration X-ray system were measured for a 29 kV, tungsten/rhodium anode/filter combination. Ray tracing through the breast models was undertaken to create simulated 2D and DBT projection images. These were then modified to adjust the image sharpness, and to add scatter and noise. The mean glandular doses for the images were 1.43, 1.47, and 1.47 mGy for 2D and 1.92, 1.97, and 1.98 mGy for DBT for the three glandularities. The resultant images were processed to create 2D, DBT planes and synthetic 2D images. Patches of the images with or without a simulated lesion were extracted, and used in a four-alternative forced choice study to measure the threshold diameters for each imaging mode, lesion type, and glandularity. The study was undertaken by six physicists. RESULTS The threshold diameters of the lesions were 6.2, 4.9, and 6.7 mm (masses) and 225, 370, and 399 μm, (calcifications) for 2D, DBT, and synthetic 2D, respectively, for a breast glandularity of 18%. The threshold diameter of ill-defined masses is significantly smaller for DBT than for both 2D (p≤0.006) and synthetic 2D (p≤0.012) for all glandularities. Glandularity has a significant effect on the threshold diameter of masses, even for DBT where there is reduced background structure in the images. The calcification threshold diameters for 2D images were significantly smaller than for DBT and synthetic 2D for all glandularities. There were few significant differences for the threshold diameter of calcifications between glandularities, indicating that the background structure has little effect on the detection of calcifications. We measured larger but nonsignificant differences in the threshold diameters for synthetic 2D imaging than for 2D imaging for masses in the 9% (p = 0.059) and 18% (p = 0.19) glandularities. The threshold diameters for synthetic 2D imaging were larger than for 2D imaging for calcifications (p < 0.001) for all glandularities. CONCLUSIONS We have shown that glandularity has only a small effect on the detection of calcifications, but the threshold diameter of masses was significantly larger for higher glandularity for all of the modalities tested. We measured nonsignificantly larger threshold diameters for synthetic 2D imaging than for 2D imaging for masses at the 9% (p = 0.059) and 18% (p = 0.19) glandularities and significantly larger diameters for calcifications (p < 0.001) for all glandularities. The lesions simulated were very subtle and further work is required to examine the clinical effect of not seeing the smallest calcifications in clusters.
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Affiliation(s)
- Alistair Mackenzie
- National Coordinating Centre for the Physics of Mammography (NCCPM), Royal Surrey NHS Foundation Trust, Guildford, UK
| | - Sukhmanjit Kaur
- National Coordinating Centre for the Physics of Mammography (NCCPM), Royal Surrey NHS Foundation Trust, Guildford, UK
- Department of Physics, University of Surrey, Guildford, UK
| | - Emma L Thomson
- National Coordinating Centre for the Physics of Mammography (NCCPM), Royal Surrey NHS Foundation Trust, Guildford, UK
- Department of Physics, University of Surrey, Guildford, UK
| | - Melissa Mitchell
- National Coordinating Centre for the Physics of Mammography (NCCPM), Royal Surrey NHS Foundation Trust, Guildford, UK
- Department of Physics, University of Surrey, Guildford, UK
| | - Premkumar Elangovan
- National Coordinating Centre for the Physics of Mammography (NCCPM), Royal Surrey NHS Foundation Trust, Guildford, UK
| | - Lucy M Warren
- National Coordinating Centre for the Physics of Mammography (NCCPM), Royal Surrey NHS Foundation Trust, Guildford, UK
| | - David R Dance
- National Coordinating Centre for the Physics of Mammography (NCCPM), Royal Surrey NHS Foundation Trust, Guildford, UK
- Department of Physics, University of Surrey, Guildford, UK
| | - Kenneth C Young
- National Coordinating Centre for the Physics of Mammography (NCCPM), Royal Surrey NHS Foundation Trust, Guildford, UK
- Department of Physics, University of Surrey, Guildford, UK
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21
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Boita J, Mackenzie A, van Engen RE, Broeders M, Sechopoulos I. Validation of a mammographic image quality modification algorithm using 3D-printed breast phantoms. J Med Imaging (Bellingham) 2021; 8:033502. [PMID: 34026921 PMCID: PMC8134780 DOI: 10.1117/1.jmi.8.3.033502] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Accepted: 04/28/2021] [Indexed: 11/14/2022] Open
Abstract
Purpose: To validate a previously proposed algorithm that modifies a mammogram to appear as if it was acquired with different technique factors using realistic phantom-based mammograms. Approach: Two digital mammography systems (an indirect- and a direct-detector-based system) were used to acquire realistic mammographic images of five 3D-printed breast phantoms with the technique factors selected by the automatic exposure control and at various other conditions (denoted by the original images). Additional images under other simulated conditions were also acquired: higher or lower tube voltages, different anode/filter combinations, or lower tube current-time products (target images). The signal and noise in the original images were modified to simulate the target images (simulated images). The accuracy of the image modification algorithm was validated by comparing the target and simulated images using the local mean, local standard deviation (SD), local variance, and power spectra (PS) of the image signals. The absolute relative percent error between the target and simulated images for each parameter was calculated at each sub-region of interest (local parameters) and frequency (PS), and then averaged. Results: The local mean signal, local SD, local variance, and PS of the target and simulated images were very similar, with a relative percent error of 5.5%, 3.8%, 7.8%, and 4.4% (indirect system), respectively, and of 3.7%, 3.8%, 7.7%, and 7.5% (direct system), respectively. Conclusions: The algorithm is appropriate for simulating different technique factors. Therefore, it can be used in various studies, for instance to evaluate the impact of technique factors in cancer detection using clinical images.
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Affiliation(s)
- Joana Boita
- Radboud University Medical Center, Department of Medical Imaging, Nijmegen, The Netherlands
- Dutch Expert Centre for Screening (LRCB), Nijmegen, The Netherlands
| | - Alistair Mackenzie
- Royal Surrey NHS Foundation Trust, National Coordinating Centre for the Physics of Mammography, Guildford, United Kingdom
| | | | - Mireille Broeders
- Dutch Expert Centre for Screening (LRCB), Nijmegen, The Netherlands
- Radboud University Medical Center, Department for Health Evidence, Nijmegen, The Netherlands
| | - Ioannis Sechopoulos
- Radboud University Medical Center, Department of Medical Imaging, Nijmegen, The Netherlands
- Dutch Expert Centre for Screening (LRCB), Nijmegen, The Netherlands
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22
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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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23
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Monnin P, Verdun FR, Bosmans H, Marshall NW. In-plane image quality and NPWE detectability index in digital breast tomosynthesis. Phys Med Biol 2020; 65:095013. [PMID: 32191923 DOI: 10.1088/1361-6560/ab8147] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
A rigorous 2D analysis of signal and noise transfer applied to reconstructed planes in digital breast tomosynthesis (DBT) is necessary for system characterization and optimization. This work proposes a method for assessing technical image quality and system detective quantum efficiency (DQEsys) for reconstructed planes in DBT. Measurements of 2D in-plane modulation transfer function (MTF) and noise power spectrum (NPS) were made on five DBT systems using different acquisition parameters, reconstruction algorithms and plane spacing. This work develops the noise equivalent quanta (NEQ), DQEsys and detectability index (d') calculated using a non-prewhitening model observer with eye filter (NPWE) for reconstructed DBT planes. The images required for this implementation were acquired using a homogeneous test object of thickness 40 mm poly(methyl) methacrylate plus 0.5 mm Al; 2D MTF was calculated from an Al disc of thickness 0.2 mm and diameter 50 mm positioned within the phantom. The radiant contrast of the MTF disc and the air kerma at the system input were used as normalization factors. The NPWE detectability index was then compared to the in-plane contrast-detail (c-d) threshold measured using the CDMAM phantom. The MTF and NPS measured on the different systems showed a strong anisotropy, consistent with the cascaded models developed in the literature for DBT. Detectability indices calculated from the measured MTF and NPS successfully predicted changes in c-d detectability for details between 0.1 mm and 2.0 mm, for DBT plane spacings between 0.5 mm and 10 mm, and for air kerma values at the system input between 157 µGy and 1170 μGy. The linear Pearson correlation between the detectability index and threshold gold thickness of the CDMAM phantom was -0.996. The method implements a parametric means of assessing the technical image quality of reconstructed DBT planes, providing valuable information for optimization of DBT systems.
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Affiliation(s)
- P Monnin
- Institute of Radiation Physics (IRA), Lausanne University Hospital (CHUV) and University of Lausanne, Rue du Grand-Pré 1, 1007 Lausanne, Switzerland. Author to whom any correspondence should be addressed
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BOLD signal simulation and fMRI quality control base on an active phantom: a preliminary study. Med Biol Eng Comput 2020; 58:831-842. [PMID: 32034636 PMCID: PMC7156364 DOI: 10.1007/s11517-020-02133-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Accepted: 01/21/2020] [Indexed: 11/23/2022]
Abstract
Blood-oxygen-level-dependent (BOLD) signal has been commonly used in functional magnetic resonance imaging (fMRI) to observe the activity in different areas of the brain or other organs. This signal is difficult to simulate, because its amplitude is nearly 1~3% and it is influenced by multiple factors. This study aimed to design and construct an active BOLD simulation phantom and test its stability and repeatability. The phantom consisted of two perpendicular loops. The BOLD signal was simulated by different stimuli generated by a regular periodic vibration current and transmission loops. Three scanners (Siemens skyra 3.0 T, Siemens verio 3.0 T, and GE signa HD 1.5 T) were used to test the stability and repeatability of the BOLD signal detection of the phantom. The percent signal change (PSC) was calculated for each stimulus. At baseline, the phantom exhibited stability, and the average signal variation was below 1% as revealed by the three scanners. The SNR of ROIs with different sizes were markedly high, being 2326.58 and 2389.24; and the ghosting ratio were 0.39% and 0.38%, and the stimuli detection efficiency for Siemens verio and Siemens skyra was 60% and 75%, respectively. The repeated scans of the same scanner for different stimuli were highly reproducible. In the three scanners, the PSC at the same location varied from nearly 1 to 3%. The areas activated on the phantom revealed by different scanners were comparatively consistent. The phantom designed for fMRI quantitative quality control displays good adaptability to different scanners and is easy to operate. It can reliably collect data by simple data processing. fMRI phantom testing process ![]()
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Comparative analysis of the transmission properties of tissue equivalent materials. Radiat Phys Chem Oxf Engl 1993 2020. [DOI: 10.1016/j.radphyschem.2019.04.050] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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