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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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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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Abadi E, Segars WP, Tsui BMW, Kinahan PE, Bottenus N, Frangi AF, Maidment A, Lo J, Samei E. Virtual clinical trials in medical imaging: a review. J Med Imaging (Bellingham) 2020; 7:042805. [PMID: 32313817 PMCID: PMC7148435 DOI: 10.1117/1.jmi.7.4.042805] [Citation(s) in RCA: 73] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Accepted: 03/23/2020] [Indexed: 12/13/2022] Open
Abstract
The accelerating complexity and variety of medical imaging devices and methods have outpaced the ability to evaluate and optimize their design and clinical use. This is a significant and increasing challenge for both scientific investigations and clinical applications. Evaluations would ideally be done using clinical imaging trials. These experiments, however, are often not practical due to ethical limitations, expense, time requirements, or lack of ground truth. Virtual clinical trials (VCTs) (also known as in silico imaging trials or virtual imaging trials) offer an alternative means to efficiently evaluate medical imaging technologies virtually. They do so by simulating the patients, imaging systems, and interpreters. The field of VCTs has been constantly advanced over the past decades in multiple areas. We summarize the major developments and current status of the field of VCTs in medical imaging. We review the core components of a VCT: computational phantoms, simulators of different imaging modalities, and interpretation models. We also highlight some of the applications of VCTs across various imaging modalities.
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Affiliation(s)
- Ehsan Abadi
- Duke University, Department of Radiology, Durham, North Carolina, United States
| | - William P. Segars
- Duke University, Department of Radiology, Durham, North Carolina, United States
| | - Benjamin M. W. Tsui
- Johns Hopkins University, Department of Radiology, Baltimore, Maryland, United States
| | - Paul E. Kinahan
- University of Washington, Department of Radiology, Seattle, Washington, United States
| | - Nick Bottenus
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States
- University of Colorado Boulder, Department of Mechanical Engineering, Boulder, Colorado, United States
| | - Alejandro F. Frangi
- University of Leeds, School of Computing, Leeds, United Kingdom
- University of Leeds, School of Medicine, Leeds, United Kingdom
| | - Andrew Maidment
- University of Pennsylvania, Department of Radiology, Philadelphia, Pennsylvania, United States
| | - Joseph Lo
- Duke University, Department of Radiology, Durham, North Carolina, United States
| | - Ehsan Samei
- Duke University, Department of Radiology, Durham, North Carolina, United States
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Rossman AH, Catenacci M, Zhao C, Sikaria D, Knudsen JE, Dawes D, Gehm ME, Samei E, Wiley BJ, Lo JY. Three-dimensionally-printed anthropomorphic physical phantom for mammography and digital breast tomosynthesis with custom materials, lesions, and uniform quality control region. J Med Imaging (Bellingham) 2019; 6:021604. [PMID: 30915385 PMCID: PMC6428804 DOI: 10.1117/1.jmi.6.2.021604] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2018] [Accepted: 03/01/2019] [Indexed: 11/14/2022] Open
Abstract
Anthropomorphic breast phantoms mimic patient anatomy in order to evaluate clinical mammography and digital breast tomosynthesis system performance. Our goal is to create a modular phantom with an anthropomorphic region to allow for improved lesion and calcification detection as well as a uniform region to evaluate standard quality control (QC) metrics. Previous versions of this phantom used commercial photopolymer inkjet three-dimensional printers to recreate breast anatomy using four surfaces that were fabricated with commercial materials spanning only a limited breast density range of 36% to 64%. We use modified printers to create voxelized, dithered breast phantoms with continuous gradations between glandular and adipose tissues. Moreover, the new phantom replicates the low-end density (representing adipose tissue) using third party material, Jf Flexible, and increases the high-end density to the density of glandular tissue and beyond by either doping Jf Flexible with salts and nanoparticles or using a new commercial resin, VeroPureWhite. An insert design is utilized to add masses, calcifications, and iodinated objects into the phantom for increased utility. The uniform chest wall region provides a space for traditional QC objects such as line pair patterns for measuring resolution and scale bars for measuring printer linearity. Incorporating these distinct design modules enables us to create an improved, complete breast phantom to better evaluate clinical mammography systems for lesion and calcification detection and standard QC performance evaluation.
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Affiliation(s)
- Andrea H Rossman
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States.,Duke University School of Medicine, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Durham, North Carolina, United States
| | - Matthew Catenacci
- Duke University, Department of Chemistry, Durham, North Carolina, United States
| | - Christine Zhao
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States.,Duke University School of Medicine, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Durham, North Carolina, United States.,Duke University, Department of Electrical and Computer Engineering, Durham, North Carolina, United States
| | - Dhiraj Sikaria
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States.,Duke University School of Medicine, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Durham, North Carolina, United States
| | - John E Knudsen
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States.,Duke University School of Medicine, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Durham, North Carolina, United States
| | - Danielle Dawes
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States.,Duke University School of Medicine, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Durham, North Carolina, United States
| | - Michael E Gehm
- Duke University, Department of Electrical and Computer Engineering, Durham, North Carolina, United States
| | - Ehsan Samei
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States.,Duke University School of Medicine, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Durham, North Carolina, United States.,Duke University, Department of Electrical and Computer Engineering, Durham, North Carolina, United States
| | - Benjamin J Wiley
- Duke University, Department of Chemistry, Durham, North Carolina, United States
| | - Joseph Y Lo
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States.,Duke University School of Medicine, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Durham, North Carolina, United States.,Duke University, Department of Electrical and Computer Engineering, Durham, North Carolina, United States
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Wen G, Markey MK, Haygood TM, Park S. Model observer for assessing digital breast tomosynthesis for multi-lesion detection in the presence of anatomical noise. ACTA ACUST UNITED AC 2018; 63:045017. [DOI: 10.1088/1361-6560/aaab3a] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Wen G, Chang HC, Reinhold J, Lo JY, Markey MK. Virtual assessment of stereoscopic viewing of digital breast tomosynthesis projection images. J Med Imaging (Bellingham) 2018; 5:015501. [PMID: 29376103 DOI: 10.1117/1.jmi.5.1.015501] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2017] [Accepted: 12/12/2017] [Indexed: 11/14/2022] Open
Abstract
Digital breast tomosynthesis (DBT) acquires a series of projection images from different angles as an x-ray source rotates around the breast. Such imaging geometry lends DBT naturally to stereoscopic viewing as two projection images with a reasonable separation angle can easily form a stereo pair. This simulation study assessed the efficacy of stereo viewing of DBT projection images. Three-dimensional computational breast phantoms with realistically shaped synthetic lesions were scanned by three simulated DBT systems. The projection images were combined into a sequence of stereo pairs and presented to a stereomatching-based model observer for deciding lesion presence. Signal-to-noise ratio was estimated, and the detection performance with stack viewing of reconstructed slices was the benchmark. We have shown that: (1) stereo viewing of projection images may underperform stack viewing of reconstructed slices for current DBT geometries; (2) DBT geometries may impact the efficacy of the two viewing modes differently: narrow-arc and wide-arc geometries may be better for stereo viewing and stack viewing, respectively; (3) the efficacy of stereo viewing may be more robust than stack viewing to reductions in dose. While in principle stereo viewing is potentially effective for visualizing DBT data, effective stereo viewing may require specifically optimized DBT image acquisition.
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Affiliation(s)
- Gezheng Wen
- University of Texas at Austin, Electrical and Computer Engineering, Austin, Texas, United States
| | - Ho-Chang Chang
- University of Texas at Austin, Electrical and Computer Engineering, Austin, Texas, United States
| | - Jacob Reinhold
- University of Texas at Austin, Applied Research Laboratories, Austin, Texas, United States
| | - Joseph Y Lo
- Duke University School of Medicine, Diagnostic Radiology, Durham, North Carolina, United States
| | - Mia K Markey
- University of Texas at Austin, Biomedical Engineering, Austin, Texas, United States.,University of Texas MD Anderson Cancer Center, Imaging Physics, Houston, Texas, United States
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Elangovan P, Mackenzie A, Dance DR, Young KC, Cooke V, Wilkinson L, Given-Wilson RM, Wallis MG, Wells K. Design and validation of realistic breast models for use in multiple alternative forced choice virtual clinical trials. Phys Med Biol 2017; 62:2778-2794. [PMID: 28291738 DOI: 10.1088/1361-6560/aa622c] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
A novel method has been developed for generating quasi-realistic voxel phantoms which simulate the compressed breast in mammography and digital breast tomosynthesis (DBT). The models are suitable for use in virtual clinical trials requiring realistic anatomy which use the multiple alternative forced choice (AFC) paradigm and patches from the complete breast image. The breast models are produced by extracting features of breast tissue components from DBT clinical images including skin, adipose and fibro-glandular tissue, blood vessels and Cooper's ligaments. A range of different breast models can then be generated by combining these components. Visual realism was validated using a receiver operating characteristic (ROC) study of patches from simulated images calculated using the breast models and from real patient images. Quantitative analysis was undertaken using fractal dimension and power spectrum analysis. The average areas under the ROC curves for 2D and DBT images were 0.51 ± 0.06 and 0.54 ± 0.09 demonstrating that simulated and real images were statistically indistinguishable by expert breast readers (7 observers); errors represented as one standard error of the mean. The average fractal dimensions (2D, DBT) for real and simulated images were (2.72 ± 0.01, 2.75 ± 0.01) and (2.77 ± 0.03, 2.82 ± 0.04) respectively; errors represented as one standard error of the mean. Excellent agreement was found between power spectrum curves of real and simulated images, with average β values (2D, DBT) of (3.10 ± 0.17, 3.21 ± 0.11) and (3.01 ± 0.32, 3.19 ± 0.07) respectively; errors represented as one standard error of the mean. These results demonstrate that radiological images of these breast models realistically represent the complexity of real breast structures and can be used to simulate patches from mammograms and DBT images that are indistinguishable from patches from the corresponding real breast images. The method can generate about 500 radiological patches (~30 mm × 30 mm) per day for AFC experiments on a single workstation. This is the first study to quantitatively validate the realism of simulated radiological breast images using direct blinded comparison with real data via the ROC paradigm with expert breast readers.
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Affiliation(s)
- Premkumar Elangovan
- Medical Imaging Group, Centre for Vision, Speech, and Signal Processing, University of Surrey, Guildford, GU2 7XH, United Kingdom. National Coordination Centre for the Physics of Mammography (NCCPM), Royal Surrey County Hospital, Guildford, GU2 7XX, United Kingdom
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