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Vancoillie L, Cockmartin L, Lueck F, Marshall N, Keupers M, Nanke R, Kappler S, Van Ongeval C, Bosmans H. Optimized signal of calcifications in wide-angle digital breast tomosynthesis: a virtual imaging trial. Eur Radiol 2024; 34:6309-6319. [PMID: 38546790 DOI: 10.1007/s00330-024-10712-9] [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: 10/30/2023] [Revised: 02/01/2024] [Accepted: 02/24/2024] [Indexed: 09/15/2024]
Abstract
OBJECTIVES Evaluate microcalcification detectability in digital breast tomosynthesis (DBT) and synthetic 2D mammography (SM) for different acquisition setups using a virtual imaging trial (VIT) approach. MATERIALS AND METHODS Medio-lateral oblique (MLO) DBT acquisitions on eight patients were performed at twice the automatic exposure controlled (AEC) dose. The noise was added to the projections to simulate a given dose trajectory. Virtual microcalcification models were added to a given projection set using an in-house VIT framework. Three setups were evaluated: (1) standard acquisition with 25 projections at AEC dose, (2) 25 projections with a convex dose distribution, and (3) sparse setup with 13 projections, every second one over the angular range. The total scan dose and angular range remained constant. DBT volume reconstruction and synthetic mammography image generation were performed using a Siemens prototype algorithm. Lesion detectability was assessed through a Jackknife-alternative free-response receiver operating characteristic (JAFROC) study with six observers. RESULTS For DBT, the area under the curve (AUC) was 0.97 ± 0.01 for the standard, 0.95 ± 0.02 for the convex, and 0.89 ± 0.03 for the sparse setup. There was no significant difference between standard and convex dose distributions (p = 0.309). Sparse projections significantly reduced detectability (p = 0.001). Synthetic images had a higher AUC with the convex setup, though not significantly (p = 0.435). DBT required four times more reading time than synthetic mammography. DISCUSSION A convex setup did not significantly improve detectability in DBT compared to the standard setup. Synthetic images exhibited a non-significant increase in detectability with the convex setup. Sparse setup significantly reduced detectability in both DBT and synthetic mammography. CLINICAL RELEVANCE STATEMENT This virtual imaging trial study allowed the design and efficient testing of different dose distribution trajectories with real mammography images, using a dose-neutral protocol. KEY POINTS • In DBT, a convex dose distribution did not increase the detectability of microcalcifications compared to the current standard setup but increased detectability for the SM images. • A sparse setup decreased microcalcification detectability in both DBT and SM images compared to the convex and current clinical setups. • Optimal microcalcification cluster detection in the system studied was achieved using either the standard or convex dose setting, with the default number of projections.
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Affiliation(s)
- Liesbeth Vancoillie
- Department of Imaging and Pathology, Division of Medical Physics, KU Leuven, Herestraat 49, 3000, Leuven, Belgium.
- CVIT, Duke University, 2424 Erwin Road, Suite 302, Durham, NC, 27705, USA.
| | - Lesley Cockmartin
- Department of Radiology, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Ferdinand Lueck
- Siemens Healthcare GmbH, Siemensstraße 1, 91301, Forchheim, Germany
| | - Nicholas Marshall
- Department of Imaging and Pathology, Division of Medical Physics, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
- Department of Radiology, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Machteld Keupers
- Department of Radiology, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Ralf Nanke
- Siemens Healthcare GmbH, Siemensstraße 1, 91301, Forchheim, Germany
| | - Steffen Kappler
- Siemens Healthcare GmbH, Siemensstraße 1, 91301, Forchheim, Germany
| | - Chantal Van Ongeval
- Department of Imaging and Pathology, Division of Medical Physics, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
- Department of Radiology, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Hilde Bosmans
- Department of Imaging and Pathology, Division of Medical Physics, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
- Department of Radiology, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium
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Lyu SH, Abbey CK, Hernandez AM, Boone JM. Microcalcification detectability in breast CT images using CNN observers. Med Phys 2024; 51:933-945. [PMID: 38154070 PMCID: PMC10922367 DOI: 10.1002/mp.16922] [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: 08/25/2023] [Revised: 11/16/2023] [Accepted: 12/16/2023] [Indexed: 12/30/2023] Open
Abstract
BACKGROUND Breast computed tomography (CT) is an emerging breast imaging modality, and ongoing developments aim to improve breast CT's ability to detect microcalcifications. To understand the effects of different parameters on microcalcification detectability, a virtual clinical trial study was conducted using hybrid images and convolutional neural network (CNN)-based model observers. Mathematically generated microcalcifications were embedded into breast CT data sets acquired at our institution, and parameters related to calcification size, calcification contrast, cluster diameter, cluster density, and image display method (i.e., single slices, slice averaging, and maximum-intensity projections) were evaluated for their influence on microcalcification detectability. PURPOSE To investigate the individual effects and the interplay of parameters affecting microcalcification detectability in breast CT. METHODS Spherical microcalcifications of varying diameters (0.04, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40 mm) and native intensities were computer simulated to portray the partial volume effects of the imaging system. Calcifications were mathematically embedded into 109 patient breast CT volume data sets as individual calcifications or as clusters of calcifications. Six numbers of calcifications (1, 3, 5, 7, 10, 15) distributed within six cluster diameters (1, 3, 5, 6, 8, 10 mm) were simulated to study the effect of cluster density. To study the role of image display method, 2D regions of interest (ROIs) and 3D volumes of interest (VOIs) were generated using single slice extraction, slice averaging, and maximum-intensity projection (MIP). 2D and 3D CNNs were trained on the ROIs and VOIs, and receiver operating characteristic (ROC) curve analysis was used to evaluate detection performance. The area under the ROC curve (AUC) was used as the primary performance metric. RESULTS Detection performance decreased with increasing section thickness, and peak detection performance occurred using the native section thickness (0.2 mm) and MIP display. The MIP display method, despite using a single slice, yielded comparable performance to the native section thickness, which employed 50 slices. Reduction in slices did not sacrifice detection accuracy and provided significant computational advantages over multi-slice image volumes. Larger cluster diameters resulted in reduced overall detectability, while smaller cluster diameters led to increased detectability. Additionally, we observed that the presence of more calcifications within a cluster improved the overall detectability, while fewer calcifications decreased it. CONCLUSIONS As breast CT is still a relatively new breast imaging modality, there is an ongoing need to identify optimal imaging protocols. This work demonstrated the utility of MIP presentation for displaying image volumes containing microcalcification clusters. It is likely that human observers may also benefit from viewing MIPs compared to individual slices. The results of this investigation begin to elucidate how model observers interact with microcalcification clusters in a 3D volume, and will be useful for future studies investigating a broader set of parameters related to breast CT.
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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
| | - Craig K. Abbey
- Department of Psychological and Brain Sciences, UC Santa Barbara, Santa Barbara, CA, 93106 USA
| | - Andrew M. Hernandez
- Department of Radiology, University of California Davis, Sacramento, CA, 95817, 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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Barufaldi B, Acciavatti RJ, Conant EF, Maidment ADA. Impact of super-resolution and image acquisition on the detection of calcifications in digital breast tomosynthesis. Eur Radiol 2024; 34:193-203. [PMID: 37572187 PMCID: PMC10898550 DOI: 10.1007/s00330-023-10103-6] [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: 02/23/2023] [Revised: 06/09/2023] [Accepted: 07/08/2023] [Indexed: 08/14/2023]
Abstract
OBJECTIVES A virtual clinical trial (VCT) method is proposed to determine the limit of calcification detection in tomosynthesis. METHODS Breast anatomy, focal findings, image acquisition, and interpretation (n = 14 readers) were simulated using screening data (n = 660 patients). Calcifications (0.2-0.4 mm3) were inserted into virtual breast phantoms. Digital breast tomosynthesis (DBT) acquisitions were simulated assuming various acquisition geometries: source motion (continuous and step-and-shoot), detector element size (140 and 70 µm), and reconstructed voxel size (35-140 µm). VCT results were estimated using multiple-reader multiple-case analyses and d' statistics. Signal-to-noise (SNR) analyses were also performed using BR3D phantoms. RESULTS Source motion and reconstructed voxel size demonstrated significant changes in the performance of imaging systems. Acquisition geometries that use 70 µm reconstruction voxel size and step-and-shoot motion significantly improved calcification detection. Comparing 70 with 100 µm reconstructed voxel size for step-and-shoot, the ΔAUC was 0.0558 (0.0647) and d' ratio was 1.27 (1.29) for 140 µm (70 µm) detector element size. Comparing step-and-shoot with a continuous motion for a 70 µm reconstructed voxel size, the ΔAUC was 0.0863 (0.0434) and the d' ratio was 1.40 (1.19) for 140 µm (70 µm) detector element. Small detector element sizes (e.g., 70 µm) did not significantly improve detection. The SNR results with the BR3D phantom show that calcification detection is dependent upon reconstructed voxel size and detector element size, supporting VCT results with comparable agreement (ratios: d' = 1.16 ± 0.11, SNR = 1.34 ± 0.13). CONCLUSION DBT acquisition geometries that use super-resolution (smaller reconstructed voxels than the detector element size) combined with step-and-shoot motion have the potential to improve the detection of calcifications. CLINICAL RELEVANCE Calcifications may not always be discernable in tomosynthesis because of differences in acquisition and reconstruction methods. VCTs can identify strategies to optimize acquisition and reconstruction parameters for calcification detection in tomosynthesis, most notably through super-resolution in the reconstruction. KEY POINTS • Super-resolution improves calcification detection and SNR in tomosynthesis; specifically, with the use of smaller reconstruction voxels. • Calcification detection using step-and-shoot motion is superior to that using continuous tube motion. • A detector element size of 70 µm does not provide better detection than 140 µm for small calcifications at the threshold of detectability.
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Affiliation(s)
- Bruno Barufaldi
- Department of Radiology, Hospital of University of Pennsylvania, 3400 Spruce Street 1 Silverstein, Philadelphia, PA, 19103, USA.
| | - Raymond J Acciavatti
- Department of Radiology, Hospital of University of Pennsylvania, 3400 Spruce Street 1 Silverstein, Philadelphia, PA, 19103, USA
| | - Emily F Conant
- Department of Radiology, Hospital of University of Pennsylvania, 3400 Spruce Street 1 Silverstein, Philadelphia, PA, 19103, USA
| | - Andrew D A Maidment
- Department of Radiology, Hospital of University of Pennsylvania, 3400 Spruce Street 1 Silverstein, Philadelphia, PA, 19103, USA
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Barufaldi B, da Nobrega YNG, Carvalhal G, Teixeira JPV, Silva Filho TM, do Rego TG, Malheiros Y, Acciavatti RJ, Maidment ADA. Multiclass Segmentation of Breast Tissue and Suspicious Findings: A Simulation-Based Study for the Development of Self-Steering Tomosynthesis. Tomography 2023; 9:1120-1132. [PMID: 37368544 PMCID: PMC10303463 DOI: 10.3390/tomography9030092] [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: 04/26/2023] [Revised: 06/05/2023] [Accepted: 06/08/2023] [Indexed: 06/29/2023] Open
Abstract
In breast tomosynthesis, multiple low-dose projections are acquired in a single scanning direction over a limited angular range to produce cross-sectional planes through the breast for three-dimensional imaging interpretation. We built a next-generation tomosynthesis system capable of multidirectional source motion with the intent to customize scanning motions around "suspicious findings". Customized acquisitions can improve the image quality in areas that require increased scrutiny, such as breast cancers, architectural distortions, and dense clusters. In this paper, virtual clinical trial techniques were used to analyze whether a finding or area at high risk of masking cancers can be detected in a single low-dose projection and thus be used for motion planning. This represents a step towards customizing the subsequent low-dose projection acquisitions autonomously, guided by the first low-dose projection; we call this technique "self-steering tomosynthesis." A U-Net was used to classify the low-dose projections into "risk classes" in simulated breasts with soft-tissue lesions; class probabilities were modified using post hoc Dirichlet calibration (DC). DC improved the multiclass segmentation (Dice = 0.43 vs. 0.28 before DC) and significantly reduced false positives (FPs) from the class of the highest risk of masking (sensitivity = 81.3% at 2 FPs per image vs. 76.0%). This simulation-based study demonstrated the feasibility of identifying suspicious areas using a single low-dose projection for self-steering tomosynthesis.
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Affiliation(s)
- Bruno Barufaldi
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA; (R.J.A.); (A.D.A.M.)
| | - Yann N. G. da Nobrega
- Center of Informatics, Federal University of Paraiba, Joao Pessoa 58051-900, PB, Brazil; (Y.N.G.d.N.); (G.C.); (J.P.V.T.); (T.G.d.R.); (Y.M.)
| | - Giulia Carvalhal
- Center of Informatics, Federal University of Paraiba, Joao Pessoa 58051-900, PB, Brazil; (Y.N.G.d.N.); (G.C.); (J.P.V.T.); (T.G.d.R.); (Y.M.)
| | - Joao P. V. Teixeira
- Center of Informatics, Federal University of Paraiba, Joao Pessoa 58051-900, PB, Brazil; (Y.N.G.d.N.); (G.C.); (J.P.V.T.); (T.G.d.R.); (Y.M.)
| | - Telmo M. Silva Filho
- Department of Engineering Mathematics, University of Bristol, Bristol BS8 1QU, UK;
| | - Thais G. do Rego
- Center of Informatics, Federal University of Paraiba, Joao Pessoa 58051-900, PB, Brazil; (Y.N.G.d.N.); (G.C.); (J.P.V.T.); (T.G.d.R.); (Y.M.)
| | - Yuri Malheiros
- Center of Informatics, Federal University of Paraiba, Joao Pessoa 58051-900, PB, Brazil; (Y.N.G.d.N.); (G.C.); (J.P.V.T.); (T.G.d.R.); (Y.M.)
| | - Raymond J. Acciavatti
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA; (R.J.A.); (A.D.A.M.)
| | - Andrew D. A. Maidment
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA; (R.J.A.); (A.D.A.M.)
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Barufaldi B, Vent TL, Bakic PR, Maidment ADA. In reply to Glick. Med Phys 2022; 49:7371-7372. [PMID: 36468247 DOI: 10.1002/mp.15950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 08/04/2022] [Indexed: 12/11/2022] Open
Affiliation(s)
- Bruno Barufaldi
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Trevor L Vent
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Predrag R Bakic
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Translational Medicine, Lund University, Malmö, Sweden
| | - Andrew D A Maidment
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Glick SJ. In Regards to Barufaldi et al. Med Phys 49(4), 2220-2232. Med Phys 2022; 49:7369-7370. [PMID: 36468268 DOI: 10.1002/mp.15771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 05/05/2022] [Accepted: 05/11/2022] [Indexed: 12/07/2022] Open
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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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