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Shi L, Vedantham S, Karellas A, Zhu L. X-ray scatter correction for dedicated cone beam breast CT using a forward-projection model. Med Phys 2017; 44:2312-2320. [PMID: 28295375 DOI: 10.1002/mp.12213] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2016] [Revised: 01/25/2017] [Accepted: 03/07/2017] [Indexed: 12/25/2022] Open
Abstract
PURPOSE The quality of dedicated cone-beam breast CT (CBBCT) imaging is fundamentally limited by x-ray scatter contamination due to the large irradiation volume. In this paper, we propose a scatter correction method for CBBCT using a novel forward-projection model with high correction efficacy and reliability. METHOD We first coarsely segment the uncorrected, first-pass, reconstructed CBBCT images into binary-object maps and assign the segmented fibroglandular and adipose tissue with the correct attenuation coefficients based on the mean x-ray energy. The modified CBBCT are treated as the prior images toward scatter correction. Primary signals are first estimated via forward projection on the modified CBBCT. To avoid errors caused by inaccurate segmentation, only sparse samples of estimated primary are selected for scatter estimation. A Fourier-Transform based algorithm, herein referred to as local filtration hereafter, is developed to efficiently estimate the global scatter distribution on the detector. The scatter-corrected images are obtained by removing the estimated scatter distribution from measured projection data. RESULTS We evaluate the method performance on six patients with different breast sizes and shapes representing the general population. The results show that the proposed method effectively reduces the image spatial non-uniformity from 8.27 to 1.91% for coronal views and from 6.50 to 3.00% for sagittal views. The contrast-to-deviation ratio is improved by an average factor of 1.41. Comparisons on the image details reveal that the proposed scatter correction successfully preserves fine structures of fibroglandular tissues that are lost in the segmentation process. CONCLUSION We propose a highly practical and efficient scatter correction algorithm for CBBCT via a forward-projection model. The method is attractive in clinical CBBCT imaging as it is readily implementable on a clinical system without modifications in current imaging protocols or system hardware.
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Affiliation(s)
- Linxi Shi
- Nuclear and Radiological Engineering and Medical Physics Programs, The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Srinivasan Vedantham
- Department of Radiology, University of Massachusetts Medical School, Worcester, MA, 01655, USA
| | - Andrew Karellas
- Department of Radiology, University of Massachusetts Medical School, Worcester, MA, 01655, USA
| | - Lei Zhu
- Nuclear and Radiological Engineering and Medical Physics Programs, The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.,Department of Modern Physics, School of Physical Sciences, University of Science and Technology of China, Hefei, Anhui, 230026, China
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Rößler AC, Kalender W, Kolditz D, Steiding C, Ruth V, Preuss C, Peter SC, Brehm B, Hammon M, Schulz-Wendtland R, Wenkel E. Performance of Photon-Counting Breast Computed Tomography, Digital Mammography, and Digital Breast Tomosynthesis in Evaluating Breast Specimens. Acad Radiol 2017; 24:184-190. [PMID: 27888024 DOI: 10.1016/j.acra.2016.09.017] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Revised: 09/21/2016] [Accepted: 09/25/2016] [Indexed: 10/20/2022]
Abstract
RATIONALE AND OBJECTIVES This study compared a novel photon-counting breast computed tomography (pcBCT) system with digital mammography (DM) and digital breast tomosynthesis (DBT) systems. For this reason, surgical specimens were examined with all three techniques and rated by three observers. MATERIALS AND METHODS A total of 30 surgical specimens were investigated with DM, DBT, and pcBCT; the associated images were shown to three experienced radiologists. Findings (22 microcalcifications and 23 mass lesions) were recorded and compared to the results of the pathological examination. Sensitivity and specificity for detection of microcalcifications and lesions were calculated and displayed using receiver operating characteristic curves. RESULTS Sensitivity for microcalcifications was 82% for DM, 70% for DBT, and 85% for pcBCT. Specificity for microcalcifications was 71% for DM, 75% for DBT, and 83% for pcBCT. Sensitivity for lesions was 45% for DM, 62% for DBT, and 65% for pcBCT. Specificity for lesions was 76% for DM, 62% for DBT, and 76% for pcBCT. CONCLUSIONS pcBCT showed a comparable or superior performance compared to the clinically approved DM and DBT systems. Mass lesion detectability can be increased further by the use of contrast media.
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Gossner J. Intramammary Findings on CT of the Chest - a Review of Normal Anatomy and Possible Findings. Pol J Radiol 2016; 81:415-421. [PMID: 28058068 PMCID: PMC5181571 DOI: 10.12659/pjr.896312] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Accepted: 01/31/2016] [Indexed: 01/10/2023] Open
Abstract
Computed tomography (CT) is a frequently performed examination in women of all ages. In all thoracic CT examinations of the chest at least parts of the breasts are included. Therefore incidental breast pathology may be observed. It has been suggested that one out of 250 women undergoing chest CT will show a malignant incidental breast lesion. Given the high number of performed chest CT examinations, this contributes to a significant number of malignancies. In this review, after a brief discussion of the value of computed tomography in breast imaging, normal and pathologic findings are discussed to create awareness of this potential “black box” on chest CT.
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Affiliation(s)
- Johannes Gossner
- Department of Clinical Radiology, Evangelisches Krankenhaus Göttingen-Weende, Göttingen, Germany
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Shi L, Vedantham S, Karellas A, Zhu L. Library based x-ray scatter correction for dedicated cone beam breast CT. Med Phys 2016; 43:4529. [PMID: 27487870 PMCID: PMC4947049 DOI: 10.1118/1.4955121] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2016] [Revised: 06/15/2016] [Accepted: 06/21/2016] [Indexed: 01/02/2023] Open
Abstract
PURPOSE The image quality of dedicated cone beam breast CT (CBBCT) is limited by substantial scatter contamination, resulting in cupping artifacts and contrast-loss in reconstructed images. Such effects obscure the visibility of soft-tissue lesions and calcifications, which hinders breast cancer detection and diagnosis. In this work, we propose a library-based software approach to suppress scatter on CBBCT images with high efficiency, accuracy, and reliability. METHODS The authors precompute a scatter library on simplified breast models with different sizes using the geant4-based Monte Carlo (MC) toolkit. The breast is approximated as a semiellipsoid with homogeneous glandular/adipose tissue mixture. For scatter correction on real clinical data, the authors estimate the breast size from a first-pass breast CT reconstruction and then select the corresponding scatter distribution from the library. The selected scatter distribution from simplified breast models is spatially translated to match the projection data from the clinical scan and is subtracted from the measured projection for effective scatter correction. The method performance was evaluated using 15 sets of patient data, with a wide range of breast sizes representing about 95% of general population. Spatial nonuniformity (SNU) and contrast to signal deviation ratio (CDR) were used as metrics for evaluation. RESULTS Since the time-consuming MC simulation for library generation is precomputed, the authors' method efficiently corrects for scatter with minimal processing time. Furthermore, the authors find that a scatter library on a simple breast model with only one input parameter, i.e., the breast diameter, sufficiently guarantees improvements in SNU and CDR. For the 15 clinical datasets, the authors' method reduces the average SNU from 7.14% to 2.47% in coronal views and from 10.14% to 3.02% in sagittal views. On average, the CDR is improved by a factor of 1.49 in coronal views and 2.12 in sagittal views. CONCLUSIONS The library-based scatter correction does not require increase in radiation dose or hardware modifications, and it improves over the existing methods on implementation simplicity and computational efficiency. As demonstrated through patient studies, the authors' approach is effective and stable, and is therefore clinically attractive for CBBCT imaging.
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Affiliation(s)
- Linxi Shi
- Nuclear and Radiological Engineering and Medical Physics Programs, The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332
| | - Srinivasan Vedantham
- Department of Radiology, University of Massachusetts Medical School, Worcester, Massachusetts 01655
| | - Andrew Karellas
- Department of Radiology, University of Massachusetts Medical School, Worcester, Massachusetts 01655
| | - Lei Zhu
- Nuclear and Radiological Engineering and Medical Physics Programs, The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332
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Longo R, Arfelli F, Bellazzini R, Bottigli U, Brez A, Brun F, Brunetti A, Delogu P, Di Lillo F, Dreossi D, Fanti V, Fedon C, Golosio B, Lanconelli N, Mettivier G, Minuti M, Oliva P, Pinchera M, Rigon L, Russo P, Sarno A, Spandre G, Tromba G, Zanconati F. Towards breast tomography with synchrotron radiation at Elettra: first images. Phys Med Biol 2016; 61:1634-49. [PMID: 26836274 DOI: 10.1088/0031-9155/61/4/1634] [Citation(s) in RCA: 70] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
The aim of the SYRMA-CT collaboration is to set-up the first clinical trial of phase-contrast breast CT with synchrotron radiation (SR). In order to combine high image quality and low delivered dose a number of innovative elements are merged: a CdTe single photon counting detector, state-of-the-art CT reconstruction and phase retrieval algorithms. To facilitate an accurate exam optimization, a Monte Carlo model was developed for dose calculation using GEANT4. In this study, high isotropic spatial resolution (120 μm)(3) CT scans of objects with dimensions and attenuation similar to a human breast were acquired, delivering mean glandular doses in the range of those delivered in clinical breast CT (5-25 mGy). Due to the spatial coherence of the SR beam and the long distance between sample and detector, the images contain, not only absorption, but also phase information from the samples. The application of a phase-retrieval procedure increases the contrast-to-noise ratio of the tomographic images, while the contrast remains almost constant. After applying the simultaneous algebraic reconstruction technique to low-dose phase-retrieved data sets (about 5 mGy) with a reduced number of projections, the spatial resolution was found to be equal to filtered back projection utilizing a four fold higher dose, while the contrast-to-noise ratio was reduced by 30%. These first results indicate the feasibility of clinical breast CT with SR.
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Ng KH, Lau S. Vision 20/20: Mammographic breast density and its clinical applications. Med Phys 2015; 42:7059-77. [PMID: 26632060 DOI: 10.1118/1.4935141] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Affiliation(s)
- Kwan-Hoong Ng
- Department of Biomedical Imaging and University of Malaya Research Imaging Centre, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia
| | - Susie Lau
- Department of Biomedical Imaging and University of Malaya Research Imaging Centre, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia
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Vedantham S, Shi L, Michaelsen KE, Krishnaswamy V, Pogue BW, Poplack SP, Karellas A, Paulsen KD. Digital Breast Tomosynthesis guided Near Infrared Spectroscopy: Volumetric estimates of fibroglandular fraction and breast density from tomosynthesis reconstructions. Biomed Phys Eng Express 2015; 1:045202. [PMID: 26941961 PMCID: PMC4771071 DOI: 10.1088/2057-1976/1/4/045202] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
A multimodality system combining a clinical prototype digital breast tomosynthesis with its imaging geometry modified to facilitate near-infrared spectroscopic imaging has been developed. The accuracy of parameters recovered from near-infrared spectroscopy is dependent on fibroglandular tissue content. Hence, in this study, volumetric estimates of fibroglandular tissue from tomosynthesis reconstructions were determined. A kernel-based fuzzy c-means algorithm was implemented to segment tomosynthesis reconstructed slices in order to estimate fibroglandular content and to provide anatomic priors for near-infrared spectroscopy. This algorithm was used to determine volumetric breast density (VBD), defined as the ratio of fibroglandular tissue volume to the total breast volume, expressed as percentage, from 62 tomosynthesis reconstructions of 34 study participants. For a subset of study participants who subsequently underwent mammography, VBD from mammography matched for subject, breast laterality and mammographic view was quantified using commercial software and statistically analyzed to determine if it differed from tomosynthesis. Summary statistics of the VBD from all study participants were compared with prior independent studies. The fibroglandular volume from tomosynthesis and mammography were not statistically different (p=0.211, paired t-test). After accounting for the compressed breast thickness, which were different between tomosynthesis and mammography, the VBD from tomosynthesis was correlated with (r =0.809, p<0.001), did not statistically differ from (p>0.99, paired t-test), and was linearly related to, the VBD from mammography. Summary statistics of the VBD from tomosynthesis were not statistically different from prior studies using high-resolution dedicated breast computed tomography. The observation of correlation and linear association in VBD between mammography and tomosynthesis suggests that breast density associated risk measures determined for mammography are translatable to tomosynthesis. Accounting for compressed breast thickness is important when it differs between the two modalities. The fibroglandular volume from tomosynthesis reconstructions is similar to mammography indicating suitability for use during near-infrared spectroscopy.
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Affiliation(s)
- Srinivasan Vedantham
- Department of Radiology, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Linxi Shi
- Department of Radiology, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | | | | | - Brian W. Pogue
- Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, USA
| | - Steven P. Poplack
- Department of Radiology, Dartmouth-Hitchcock Medical Center, Lebanon, NH 03756, USA
| | - Andrew Karellas
- Department of Radiology, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Keith D. Paulsen
- Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, USA
- Department of Radiology, Dartmouth-Hitchcock Medical Center, Lebanon, NH 03756, USA
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