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Salomon E, Vanko B, Homolka P, Cockmartin L, Figl M, Clauser P, Unger E, Bosmans H, Marshall N, Hummel J. A spiculated mass target model for clinical image quality control in digital mammography. Br J Radiol 2024; 97:560-566. [PMID: 38265303 DOI: 10.1093/bjr/tqad055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 11/16/2023] [Accepted: 12/04/2023] [Indexed: 01/25/2024] Open
Abstract
OBJECTIVES Quality assurance of breast imaging has a long history of using test objects to optimize and follow up imaging devices. In particular, the evaluation of new techniques benefits from suitable test objects. The applicability of a phantom consisting of spiculated masses to assess image quality and its dependence on dose in flat field digital mammography (FFDM) and digital breast tomosynthesis systems (DBT) is investigated. METHODS Two spiculated masses in five different sizes each were created from a database of clinical tumour models. The masses were produced using 3D printing and embedded into a cuboid phantom. Image quality is determined by the number of spicules identified by human observers. RESULTS The results suggest that the effect of dose on spicule detection is limited especially in cases with smaller objects and probably hidden by the inter-reader variability. Here, an average relative inter-reader variation of the counted number of 31% was found (maximum 83%). The mean relative intra-reader variability was found to be 17%. In DBT, sufficiently good results were obtained only for the largest masses. CONCLUSIONS It is possible to integrate spiculated masses into a cuboid phantom. It is easy to print and should allow a direct and prompt evaluation of the quality status of the device by counting visible spicules. Human readout presented the major uncertainty in this study, indicating that automated readout may improve the reproducibility and consistency of the results considerably. ADVANCES IN KNOWLEDGE A cuboid phantom including clinical objects as spiculated lesion models for visual assessing the image quality in FFDM and DBT was developed and is introduced in this work. The evaluation of image quality works best with the two larger masses with 21 spicules.
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Affiliation(s)
- Elisabeth Salomon
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna A-1090, Austria
| | - Bence Vanko
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna A-1090, Austria
| | - Peter Homolka
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna A-1090, Austria
| | | | - Michael Figl
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna A-1090, Austria
- Christian Doppler Laboratory for Mathematical Modeling and Simulation of Next-Generation Medical Ultrasound Devices, Vienna A-1090, Austria
| | - Paola Clauser
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna and General Hospital Vienna, Vienna A-1090, Austria
| | - Ewald Unger
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna A-1090, Austria
| | - Hilde Bosmans
- Department of Radiology, UZ Gasthuisberg, Leuven B-30008, Belgium
| | - Nicolas Marshall
- Department of Radiology, UZ Gasthuisberg, Leuven B-30008, Belgium
| | - Johann Hummel
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna A-1090, Austria
- Christian Doppler Laboratory for Mathematical Modeling and Simulation of Next-Generation Medical Ultrasound Devices, Vienna A-1090, Austria
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Lyu SH, Hernandez AM, Shakeri SA, Abbey CK, Boone JM. Model observer performance in contrast-enhanced lesions in breast CT: The influence of contrast concentration on detectability. Med Phys 2023; 50:6748-6761. [PMID: 37639329 PMCID: PMC10847956 DOI: 10.1002/mp.16667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 07/13/2023] [Accepted: 07/15/2023] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND The use of iodine-based contrast agent for better delineation of tumors in breast CT (bCT) has been shown to be compelling, similar to the tumor enhancement in contrast-enhanced breast MRI. Contrast-enhanced bCT (CE-bCT) is a relatively new tool, and a structured evaluation of different imaging parameters at play has yet to be conducted. In this investigation, data sets of acquired bCT images from 253 patients imaged at our institution were used in concert with simulated mathematically inserted spherical contrast-enhanced lesions to study the role of contrast enhancement on detectability. PURPOSE To quantitatively evaluate the improvement in lesion detectability due to contrast enhancement across lesion diameter, section thickness, view plane, and breast density using a pre-whitened matched filter (PWMF) model observer. METHODS The relationship between iodine concentration and Hounsfield units (HU) was measured using spectral modeling. The lesion enhancement from clinical CE-bCT images in 22 patients was evaluated, and the average contrast enhancement (ΔHU) was determined. Mathematically generated spherical mass lesions of varying diameters (1, 3, 5, 9, 11, 15 mm) and contrast enhancement levels (0, 0.25, 0.50, 0.75, 1) were inserted at random locations in 253 actual patient bCT datasets. Images with varying thicknesses (0.4-19.8 mm) were generated by slice averaging, and the role of view plane (coronal and axial planes) was studied. A PWMF was used to generate receiver operating characteristic (ROC) curves across parameters of lesion diameter, contrast enhancement, section thickness, view plane, and breast density. The area under the ROC curve (AUC) was used as the primary performance metric, generated from over 90,000 simulated lesions. RESULTS An average 20% improvement (ΔAUC = 0.1) in lesion detectability due to contrast enhancement was observed across lesion diameter, section thickness, breast density, and view plane. A larger improvement was observed when stratifying patients based on breast density. For patients with VGF ≤ 40%, detection performance improved up to 20% (until AUC →1), and for patients with denser breasts (VGF > 40%), detection performance improved more drastically, ranging from 20% to 80% for 1- and 5-mm lesions. For the 1 mm lesion, detection performance raised slightly at the 1.2 mm section thickness before falling off as thickness increased. For larger lesions, detection performance was generally unaffected as section thickness increased up until it reached 5.8 mm, where performance began to decline. Detection performance was higher in the axial plane compared to the coronal plane for smaller lesions and thicker sections. CONCLUSIONS For emerging diagnostic tools like CE-bCT, it is important to optimize imaging protocols for lesion detection. In this study, we found that intravenous contrast can be used to detect small lesions in dense breasts. Optimal section thickness for detectability has dependencies on breast density and lesion size, therefore, display thickness should be adjusted in real-time using display software. These findings may be useful for the development of CE-bCT as well as other x-ray-based breast imaging modalities.
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Affiliation(s)
- Su Hyun Lyu
- Department of Biomedical Engineering, University of California Davis, Davis, CA, 95618, USA
- Department of Radiology, University of California Davis, Sacramento, CA, 95817, USA
| | - Andrew M. Hernandez
- Department of Radiology, University of California Davis, Sacramento, CA, 95817, USA
| | | | - Craig K. Abbey
- Department of Psychological and Brain Sciences, UC Santa Barbara, Santa Barbara, CA, 93106 USA
| | - John M. Boone
- Department of Biomedical Engineering, University of California Davis, Davis, CA, 95618, USA
- Department of Radiology, University of California Davis, Sacramento, CA, 95817, USA
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Tomic H, Costa AC, Bjerkén A, Vieira MAC, Zackrisson S, Tingberg A, Timberg P, Dustler M, Bakic PR. Simulation of breast lesions based upon fractal Perlin noise. Phys Med 2023; 114:102681. [PMID: 37748358 DOI: 10.1016/j.ejmp.2023.102681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 07/03/2023] [Accepted: 09/11/2023] [Indexed: 09/27/2023] Open
Abstract
PURPOSE Steadily increasing use of computational/virtual phantoms in medical physics has motivated expanding development of new simulation methods and data representations for modelling human anatomy. This has emphasized the need for increased realism, user control, and availability. In breast cancer research, virtual phantoms have gained an important role in evaluating and optimizing imaging systems. For this paper, we have developed an algorithm to model breast abnormalities based on fractal Perlin noise. We demonstrate and characterize the extension of this approach to simulate breast lesions of various sizes, shapes, and complexity. MATERIALS AND METHOD Recently, we developed an algorithm for simulating the 3D arrangement of breast anatomy based on Perlin noise. In this paper, we have expanded the method to also model soft tissue breast lesions. We simulated lesions within the size range of clinically representative breast lesions (masses, 5-20 mm in size). Simulated lesions were blended into simulated breast tissue backgrounds and visualized as virtual digital mammography images. The lesions were evaluated by observers following the BI-RADS assessment criteria. RESULTS Observers categorized the lesions as round, oval or irregular, with circumscribed, microlobulated, indistinct or obscured margins. The majority of the simulated lesions were considered by the observers to have a realism score of moderate to well. The simulation method provides almost real-time lesion generation (average time and standard deviation: 1.4 ± 1.0 s). CONCLUSION We presented a novel algorithm for computer simulation of breast lesions using Perlin noise. The algorithm enables efficient simulation of lesions, with different sizes and appearances.
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Affiliation(s)
- Hanna Tomic
- Diagnostic Radiology, Department of Translational Medicine, Faculty of Medicine, Lund University, Skåne University Hospital, Malmö, Sweden.
| | - Arthur C Costa
- Department of Electrical and Computer Engineering, University of São Paulo, São Carlos, Brazil
| | - Anna Bjerkén
- Medical Radiation Physics, Department of Translational Medicine, Faculty of Medicine, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Marcelo A C Vieira
- Department of Electrical and Computer Engineering, University of São Paulo, São Carlos, Brazil
| | - Sophia Zackrisson
- Diagnostic Radiology, Department of Translational Medicine, Faculty of Medicine, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Anders Tingberg
- Medical Radiation Physics, Department of Translational Medicine, Faculty of Medicine, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Pontus Timberg
- Medical Radiation Physics, Department of Translational Medicine, Faculty of Medicine, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Magnus Dustler
- Diagnostic Radiology, Department of Translational Medicine, Faculty of Medicine, Lund University, Skåne University Hospital, Malmö, Sweden; Medical Radiation Physics, Department of Translational Medicine, Faculty of Medicine, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Predrag R Bakic
- Diagnostic Radiology, Department of Translational Medicine, Faculty of Medicine, Lund University, Skåne University Hospital, Malmö, Sweden; Medical Radiation Physics, Department of Translational Medicine, Faculty of Medicine, Lund University, Skåne University Hospital, Malmö, Sweden
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Salomon E, Unger E, Homolka P, Cockmartin L, Petrov D, Semturs F, Songsaeng C, Panagiotis K, Vancoillie L, Figl M, Sommer A, Bosmans H, Hummel J. Technical note: Realization and uncertainty analysis for an adjustable 3D structured breast phantom in digital breast tomosynthesis. Med Phys 2023; 50:4816-4824. [PMID: 37438921 DOI: 10.1002/mp.16600] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 04/09/2023] [Accepted: 06/07/2023] [Indexed: 07/14/2023] Open
Abstract
BACKGROUND Projection imaging phantoms are often optimized for 2-dimensional image characteristics in homogeneous backgrounds. Therefore, evaluation of image quality in tomosynthesis (DBT) lacks accepted and established phantoms. PURPOSE We describe a 3D breast phantom with a structured, variable background. The phantom is an adaptable and advanced version of the L1 phantom by Cockmartin et al. Phantom design and its use for quality assurance measurements for DBT devices are described. Four phantoms were compared to assess the objectivity. METHODS The container size was increased to a diameter of 24 cm and a total height of 53.5 mm. Spiculated masses were replaced by five additional non-spiculated masses for higher granularity in threshold diameter resolution. These patterns are adjustable to the imaging device. The masses were printed in one session with a base layer using two-component 3D printing. New materials compared to the L1 phantom improved the attenuation difference between the lesion models and the background. Four phantoms were built and intra-human observer, inter-human observer and inter-phantom variations were determined. The latter assess the reproducibility of the phantom production. Coefficients of variance (V) were calculated for all three variations. RESULTS The difference of the attenuation coefficients between the lesion models and the background was 0.20 cm-1 (with W/Al at 32 kV, equivalent to 19-20 keV effective energy) compared to 0.21 cm-1 for 50/50 glandular/adipose breast tissue and cancerous lesions. PMMA equivalent thickness of the phantom was 47.0 mm for the Siemens Mammomat Revelation. For the masses, theV i n t r a $V_{intra}$ for the intra-observer variation was 0.248, the averaged inter-observer variation,V ¯ i n t e r $\overline{V}_{inter}$ was 0.383.V p h a n t o m $V_{phantom}$ for phantom variance was 0.321. For the micro-calcifications,V i n t r a $V_{intra}$ was 0.0429,V ¯ i n t e r = $\overline{V}_{inter}=$ 0.0731 andV p h a n t o m = $V_{phantom}=$ 0.0759. CONCLUSIONS Position, orientation and shape of the masses are reproducible and attenuation differences appropriate. The phantom presented proved to be a candidate test object for quality control.
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Affiliation(s)
- Elisabeth Salomon
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Spitalgasse, Vienna, Austria
| | - Ewald Unger
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Spitalgasse, Vienna, Austria
| | - Peter Homolka
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Spitalgasse, Vienna, Austria
| | | | - Dimitar Petrov
- Department of Radiology, UZ Gasthuisberg, Leuven, Belgium
| | - Friedrich Semturs
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Spitalgasse, Vienna, Austria
| | - Chatsuda Songsaeng
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Spitalgasse, Vienna, Austria
- Christian Doppler Laboratory for Mathematical Modelling and Simulation of Next-Generation Medical Ultrasound Devices, Vienna, Austria
| | - Kapetas Panagiotis
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna and General Hospital, Spitalgasse, Vienna, Austria
| | | | - Michael Figl
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Spitalgasse, Vienna, Austria
- Christian Doppler Laboratory for Mathematical Modelling and Simulation of Next-Generation Medical Ultrasound Devices, Vienna, Austria
| | - Alexander Sommer
- Clinic for Radiology and Reference Center for Mammography Münster, University of Münster and University Hospital Münster, Münster, Germany
| | - Hilde Bosmans
- Department of Radiology, UZ Gasthuisberg, Leuven, Belgium
| | - Johann Hummel
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Spitalgasse, Vienna, Austria
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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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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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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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Petrov D, Marshall NW, Young KC, Bosmans H. Systematic approach to a channelized Hotelling model observer implementation for a physical phantom containing mass-like lesions: Application to digital breast tomosynthesis. Phys Med 2019; 58:8-20. [PMID: 30824154 DOI: 10.1016/j.ejmp.2018.12.033] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Revised: 12/05/2018] [Accepted: 12/25/2018] [Indexed: 10/27/2022] Open
Abstract
PURPOSE to develop a channelized model observer (CHO) that matches human reader (HR) scoring of a physical phantom containing breast simulating structure and mass lesion-like targets for use in quality control of digital breast tomosynthesis (DBT) imaging systems. METHODS A total of 108 DBT scans of the phantom was acquired using a Siemens Inspiration DBT system. The detectability of mass-like targets was evaluated by human readers using a 4-alternative forced choice (4-AFC) method. The percentage correct (PC) values were then used as the benchmark for CHO tuning, again using a 4-AFC method. Three different channel functions were considered: Gabor, Laguerre-Gauss and Difference of Gaussian. With regard to the observer template, various methods for generating the expected signal were studied along with the influence of the number of training images used to form the covariance matrix for the observer template. Impact of bias in the training process on the observer template was evaluated next, as well as HR and CHO reproducibility. RESULTS HR performance was most closely matched by 8 Gabor channels with tuned phase, orientation and frequency, using an observer template generated from training image data. Just 24 DBT image stacks were required to give robust CHO performance with 0% bias, although a bias of up to 33% in the training images also gave acceptable performance. CHO and HR reproducibility were similar (on average 3.2 PC versus 3.4 PC). CONCLUSIONS The CHO algorithm developed matches human reader performance and is therefore a promising candidate for automated readout of phantom studies.
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Affiliation(s)
- Dimitar Petrov
- Dept. of Medical Physics and Quality Assessment, KU Leuven, Leuven, Belgium.
| | - Nicholas W Marshall
- Dept. of Medical Physics and Quality Assessment, KU Leuven, Leuven, Belgium; Dept. of Radiology, UZ Leuven, Belgium
| | | | - Hilde Bosmans
- Dept. of Medical Physics and Quality Assessment, KU Leuven, Leuven, Belgium; Dept. of Radiology, UZ Leuven, Belgium
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Kainz W, Neufeld E, Bolch WE, Graff CG, Kim CH, Kuster N, Lloyd B, Morrison T, Segars P, Yeom YS, Zankl M, Xu XG, Tsui BMW. Advances in Computational Human Phantoms and Their Applications in Biomedical Engineering - A Topical Review. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2019; 3:1-23. [PMID: 30740582 PMCID: PMC6362464 DOI: 10.1109/trpms.2018.2883437] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Over the past decades, significant improvements have been made in the field of computational human phantoms (CHPs) and their applications in biomedical engineering. Their sophistication has dramatically increased. The very first CHPs were composed of simple geometric volumes, e.g., cylinders and spheres, while current CHPs have a high resolution, cover a substantial range of the patient population, have high anatomical accuracy, are poseable, morphable, and are augmented with various details to perform functionalized computations. Advances in imaging techniques and semi-automated segmentation tools allow fast and personalized development of CHPs. These advances open the door to quickly develop personalized CHPs, inherently including the disease of the patient. Because many of these CHPs are increasingly providing data for regulatory submissions of various medical devices, the validity, anatomical accuracy, and availability to cover the entire patient population is of utmost importance. The article is organized into two main sections: the first section reviews the different modeling techniques used to create CHPs, whereas the second section discusses various applications of CHPs in biomedical engineering. Each topic gives an overview, a brief history, recent developments, and an outlook into the future.
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Affiliation(s)
- Wolfgang Kainz
- Food and Drug Administration (FDA), Center for Devices and Radiological Health (CDRH), Silver Spring, MD 20993 USA
| | - Esra Neufeld
- Foundation for Research on Information Technologies in Society (IT'IS), Zurich, Switzerland
| | | | - Christian G Graff
- Food and Drug Administration (FDA), Center for Devices and Radiological Health (CDRH), Silver Spring, MD 20993 USA
| | | | - Niels Kuster
- Swiss Federal Institute of Technology, ETH Zürich, and the Foundation for Research on Information Technologies in Society (IT'IS), Zürich, Switzerland
| | - Bryn Lloyd
- Foundation for Research on Information Technologies in Society (IT'IS), Zurich, Switzerland
| | - Tina Morrison
- Food and Drug Administration (FDA), Center for Devices and Radiological Health (CDRH), Silver Spring, MD 20993 USA
| | | | | | - Maria Zankl
- Helmholtz Zentrum München German Research Center for Environmental Health, Munich, Germany
| | - X George Xu
- Rensselaer Polytechnic Institute, Troy, NY, USA
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Vignero J, Marshall NW, Bliznakova K, Bosmans H. A hybrid simulation framework for computer simulation and modelling studies of grating-based x-ray phase-contrast images. ACTA ACUST UNITED AC 2018; 63:14NT03. [DOI: 10.1088/1361-6560/aaceb8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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Salvagnini E, Bosmans H, Van Ongeval C, Van Steen A, Michielsen K, Cockmartin L, Struelens L, Marshall NW. Impact of compressed breast thickness and dose on lesion detectability in digital mammography: FROC study with simulated lesions in real mammograms. Med Phys 2017; 43:5104. [PMID: 27587041 DOI: 10.1118/1.4960630] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
PURPOSE The aim of this work was twofold: (1) to examine whether, with standard automatic exposure control (AEC) settings that maintain pixel values in the detector constant, lesion detectability in clinical images decreases as a function of breast thickness and (2) to verify whether a new AEC setup can increase lesion detectability at larger breast thicknesses. METHODS Screening patient images, acquired on two identical digital mammography systems, were collected over a period of 2 yr. Mammograms were acquired under standard AEC conditions (part 1) and subsequently with a new AEC setup (part 2), programmed to use the standard AEC settings for compressed breast thicknesses ≤49 mm, while a relative dose increase was applied above this thickness. The images were divided into four thickness groups: T1 ≤ 29 mm, T2 = 30-49 mm, T3 = 50-69 mm, and T4 ≥ 70 mm, with each thickness group containing 130 randomly selected craniocaudal lesion-free images. Two measures of density were obtained for every image: a BI-RADS score and a map of volumetric breast density created with a software application (VolparaDensity, Matakina, NZ). This information was used to select subsets of four images, containing one image from each thickness group, matched to a (global) BI-RADS score and containing a region with the same (local) volpara volumetric density value. One selected lesion (a microcalcification cluster or a mass) was simulated into each of the four images. This process was repeated so that, for a given thickness group, half the images contained a single lesion and half were lesion-free. The lesion templates created and inserted in groups T3 and T4 for the first part of the study were then inserted into the images of thickness groups T3 and T4 acquired with higher dose settings. Finally, all images were visualized using the ViewDEX software and scored by four radiologists performing a free search study. A statistical jackknife-alternative free-response receiver operating characteristic analysis was applied. RESULTS For part 1, the alternative free-response receiver operating characteristic curves for the four readers were 0.80, 0.65, 0.55 and 0.56 in going from T1 to T4, indicating a decrease in detectability with increasing breast thickness. P-values and the 95% confidence interval showed no significant difference for the T3-T4 comparison (p = 0.78) while all the other differences were significant (p < 0.05). Separate analysis of microcalcification clusters presented the same results while for mass detection, the only significant difference came when comparing T1 to the other thickness groups. Comparing the scores of part 1 and part 2, results for the T3 group acquired with the new AEC setup and T3 group at standard AEC doses were significantly different (p = 0.0004), indicating improved detection. For this group a subanalysis for microcalcification detection gave the same results while no significant difference was found for mass detection. CONCLUSIONS These data using clinical images confirm results found in simple QA tests for many mammography systems that detectability falls as breast thickness increases. Results obtained with the AEC setup for constant detectability above 49 mm showed an increase in lesion detection with compressed breast thickness, bringing detectability of lesions to the same level.
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Affiliation(s)
- Elena Salvagnini
- Department of Imaging and Pathology, Radiology, KUL, Herestraat 49, Leuven B-3000, Belgium and SCK•CEN, Boeretang 200, Mol 2400, Belgium
| | - Hilde Bosmans
- Department of Imaging and Pathology, Radiology, KUL, Herestraat 49, Leuven B-3000, Belgium and Department of Radiology, Radiology, UZ Gasthuisberg, Herestraat 49, Leuven B-3000, Belgium
| | - Chantal Van Ongeval
- Department of Radiology, Radiology, UZ Gasthuisberg, Herestraat 49, Leuven B-3000, Belgium
| | - Andreas Van Steen
- Department of Radiology, Radiology, UZ Gasthuisberg, Herestraat 49, Leuven B-3000, Belgium
| | - Koen Michielsen
- Department of Imaging and Pathology, Nuclear Medicine and Molecular Imaging, KUL, Herestraat 49, Leuven B-3000, Belgium
| | - Lesley Cockmartin
- Department of Radiology, Radiology, UZ Gasthuisberg, Herestraat 49, Leuven B-3000, Belgium
| | | | - Nicholas W Marshall
- Department of Imaging and Pathology, Radiology, KUL, Herestraat 49, Leuven B-3000, Belgium and Department of Radiology, Radiology, UZ Gasthuisberg, Herestraat 49, Leuven B-3000, Belgium
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12
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Badano A. "How much realism is needed?" - the wrong question in silico imagers have been asking. Med Phys 2017; 44:1607-1609. [PMID: 28266047 DOI: 10.1002/mp.12187] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2016] [Revised: 02/07/2017] [Accepted: 02/22/2017] [Indexed: 01/31/2023] Open
Abstract
PURPOSE To discuss the use of realism as a first approximation for assessing computational imaging methods. METHODS Although in silico methods are increasingly becoming promising surrogates to physical experimentation for various stages of device development, their acceptance remains challenging. Realism is often considered as a first approximation for assessing computational imaging methods. However, realism is subjective and does not always ensure that key features of the methodologies reflect relevant aspects of devices of interest to imaging scientists, regulators, and medical practitioners. Moreover, in some cases (e.g., in computerized image analysis applications where human interpretation is not needed) how realistic in silico images are is irrelevant and perhaps misleading. RESULTS I emphasize a divergence from this methodology by providing a rationale for evaluating in silico imaging methods and tools in an objective and measurable manner. CONCLUSIONS Improved approaches for in silico imaging will lead to the rapid advancement and acceptance of computational techniques in medical imaging primarily but not limited to the regulatory evaluation of new imaging products.
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Affiliation(s)
- Aldo Badano
- Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA
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13
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Cockmartin L, Marshall NW, Zhang G, Lemmens K, Shaheen E, Van Ongeval C, Fredenberg E, Dance DR, Salvagnini E, Michielsen K, Bosmans H. Design and application of a structured phantom for detection performance comparison between breast tomosynthesis and digital mammography. Phys Med Biol 2017; 62:758-780. [PMID: 28072573 DOI: 10.1088/1361-6560/aa5407] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
This paper introduces and applies a structured phantom with inserted target objects for the comparison of detection performance of digital breast tomosynthesis (DBT) against 2D full field digital mammography (FFDM). The phantom consists of a 48 mm thick breast-shaped polymethyl methacrylate (PMMA) container filled with water and PMMA spheres of different diameters. Three-dimensionally (3D) printed spiculated masses (diameter range: 3.8-9.7 mm) and non-spiculated masses (1.6-6.2 mm) along with microcalcifications (90-250 µm) were inserted as targets. Reproducibility of the phantom application was studied on a single system using 30 acquisitions. Next, the phantom was evaluated on five different combined FFDM & DBT systems and target detection was compared for FFDM and DBT modes. Ten phantom images in both FFDM and DBT modes were acquired on these 5 systems using automatic exposure control. Five readers evaluated target detectability. Images were read with the four-alternative forced-choice (4-AFC) paradigm, with always one segment including a target and 3 normal background segments. The percentage of correct responses (PC) was assessed based on 10 trials of each reader for each object type, size and imaging modality. Additionally, detection threshold diameters at 62.5 PC were assessed via non-linear regression fitting of the psychometric curve. The reproducibility study showed no significant differences in PC values. Evaluation of target detection in FFDM showed that microcalcification detection thresholds ranged between 110 and 118 µm and were similar compared to the detection in DBT (range of 106-158 µm). In DBT, detection of both mass types increased significantly (p = 0.0001 and p = 0.0002 for non-spiculated and spiculated masses respectively) compared to FFDM, achieving almost 100% detection for all spiculated mass diameters. In conclusion, a structured phantom with inserted targets was able to show evidence for detectability differences between FFDM and DBT modes for five commercial systems. This phantom has potential for application in task-based assessment at acceptance and commissioning testing of DBT systems.
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Affiliation(s)
- L Cockmartin
- Department of Radiology, UZ Leuven, Herestraat 49, B-3000 Leuven, Belgium. Department of Imaging and Pathology, Division of Medical Physics and Quality Assessment, KU Leuven, Herestraat 49, B-3000 Leuven, Belgium
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14
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Erickson DW, Wells JR, Sturgeon GM, Samei E, Dobbins JT, Segars WP, Lo JY. Population of 224 realistic human subject-based computational breast phantoms. Med Phys 2016; 43:23. [PMID: 26745896 DOI: 10.1118/1.4937597] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
PURPOSE To create a database of highly realistic and anatomically variable 3D virtual breast phantoms based on dedicated breast computed tomography (bCT) data. METHODS A tissue classification and segmentation algorithm was used to create realistic and detailed 3D computational breast phantoms based on 230 + dedicated bCT datasets from normal human subjects. The breast volume was identified using a coarse three-class fuzzy C-means segmentation algorithm which accounted for and removed motion blur at the breast periphery. Noise in the bCT data was reduced through application of a postreconstruction 3D bilateral filter. A 3D adipose nonuniformity (bias field) correction was then applied followed by glandular segmentation using a 3D bias-corrected fuzzy C-means algorithm. Multiple tissue classes were defined including skin, adipose, and several fractional glandular densities. Following segmentation, a skin mask was produced which preserved the interdigitated skin, adipose, and glandular boundaries of the skin interior. Finally, surface modeling was used to produce digital phantoms with methods complementary to the XCAT suite of digital human phantoms. RESULTS After rejecting some datasets due to artifacts, 224 virtual breast phantoms were created which emulate the complex breast parenchyma of actual human subjects. The volume breast density (with skin) ranged from 5.5% to 66.3% with a mean value of 25.3% ± 13.2%. Breast volumes ranged from 25.0 to 2099.6 ml with a mean value of 716.3 ± 386.5 ml. Three breast phantoms were selected for imaging with digital compression (using finite element modeling) and simple ray-tracing, and the results show promise in their potential to produce realistic simulated mammograms. CONCLUSIONS This work provides a new population of 224 breast phantoms based on in vivo bCT data for imaging research. Compared to previous studies based on only a few prototype cases, this dataset provides a rich source of new cases spanning a wide range of breast types, volumes, densities, and parenchymal patterns.
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Affiliation(s)
- David W Erickson
- Carl E. Ravin Advanced Imaging Laboratories, Duke University Medical Center, Durham, North Carolina 27705 and Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705
| | - Jered R Wells
- Clinical Imaging Physics Group and Carl E. Ravin Advanced Imaging Laboratories, Duke University Medical Center, Durham, North Carolina 27705 and Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705
| | - Gregory M Sturgeon
- Carl E. Ravin Advanced Imaging Laboratories, Duke University Medical Center, Durham, North Carolina 27705
| | - Ehsan Samei
- Department of Radiology and Carl E. Ravin Advanced Imaging Laboratories, Duke University Medical Center, Durham, North Carolina 27705 and Departments of Physics, Electrical and Computer Engineering, and Biomedical Engineering, and Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705
| | - James T Dobbins
- Department of Radiology and Carl E. Ravin Advanced Imaging Laboratories, Duke University Medical Center, Durham, North Carolina 27705 and Departments of Physics and Biomedical Engineering and Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705
| | - W Paul Segars
- Department of Radiology and Carl E. Ravin Advanced Imaging Laboratories, Duke University Medical Center, Durham, North Carolina 27705 and Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705
| | - Joseph Y Lo
- Department of Radiology and Carl E. Ravin Advanced Imaging Laboratories, Duke University Medical Center, Durham, North Carolina 27705 and Departments of Electrical and Computer Engineering and Biomedical Engineering and Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705
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15
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Kiarashi N, Nolte AC, Sturgeon GM, Segars WP, Ghate SV, Nolte LW, Samei E, Lo JY. Development of realistic physical breast phantoms matched to virtual breast phantoms based on human subject data. Med Phys 2015; 42:4116-26. [PMID: 26133612 DOI: 10.1118/1.4919771] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Affiliation(s)
- Nooshin Kiarashi
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27710 and Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina 27708
| | - Adam C Nolte
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27710 and Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708
| | - Gregory M Sturgeon
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27710
| | - William P Segars
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27710 and Medical Physics Graduate Program, Duke University, Durham, North Carolina 27708
| | - Sujata V Ghate
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27710
| | - Loren W Nolte
- Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina 27708 and Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708
| | - Ehsan Samei
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27710; Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina 27708; Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708; Medical Physics Graduate Program, Duke University, Durham, North Carolina 27708; and Department of Physics, Duke University, Durham, North Carolina 27708
| | - Joseph Y Lo
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27710; Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina 27708; Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708; and Medical Physics Graduate Program, Duke University, Durham, North Carolina 27708
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16
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Cockmartin L, Marshall NW, Van Ongeval C, Aerts G, Stalmans D, Zanca F, Shaheen E, De Keyzer F, Dance DR, Young KC, Bosmans H. Comparison of digital breast tomosynthesis and 2D digital mammography using a hybrid performance test. Phys Med Biol 2015; 60:3939-58. [PMID: 25909596 DOI: 10.1088/0031-9155/60/10/3939] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
This paper introduces a hybrid method for performing detection studies in projection image based modalities, based on image acquisitions of target objects and patients. The method was used to compare 2D mammography and digital breast tomosynthesis (DBT) in terms of the detection performance of spherical densities and microcalcifications. The method starts with the acquisition of spheres of different glandular equivalent densities and microcalcifications of different sizes immersed in a homogeneous breast tissue simulating medium. These target objects are then segmented and the subsequent templates are fused in projection images of patients and processed or reconstructed. This results in hybrid images with true mammographic anatomy and clinically relevant target objects, ready for use in observer studies. The detection study of spherical densities used 108 normal and 178 hybrid 2D and DBT images; 156 normal and 321 hybrid images were used for the microcalcifications. Seven observers scored the presence/absence of the spheres/microcalcifications in a square region via a 5-point confidence rating scale. Detection performance in 2D and DBT was compared via ROC analysis with sub-analyses for the density of the spheres, microcalcification size, breast thickness and z-position. The study was performed on a Siemens Inspiration tomosynthesis system using patient acquisitions with an average age of 58 years and an average breast thickness of 53 mm providing mean glandular doses of 1.06 mGy (2D) and 2.39 mGy (DBT). Study results showed that breast tomosynthesis (AUC = 0.973) outperformed 2D (AUC = 0.831) for the detection of spheres (p < 0.0001) and this applied for all spherical densities and breast thicknesses. By way of contrast, DBT was worse than 2D for microcalcification detection (AUC2D = 0.974, AUCDBT = 0.838, p < 0.0001), with significant differences found for all sizes (150-354 µm), for breast thicknesses above 40 mm and for heights above the detector of 20 mm and above. In conclusion, the hybrid method was successfully used to produce images for a detection study; results showed breast tomosynthesis outperformed 2D for spherical densities while further optimization of DBT for microcalcifications is suggested.
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Affiliation(s)
- Lesley Cockmartin
- Department of Imaging and Pathology, Division of Medical Physics & Quality Assessment, KU Leuven, Herestraat 49 Box 7003, 3000 Leuven, Belgium. Department of Radiology, University Hospitals Leuven, Herestraat 49, 3000 Leuven, Belgium
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