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Mettivier G, Sarno A, Varallo A, Russo P. Attenuation coefficient in the energy range 14–36 keV of 3D printing materials for physical breast phantoms. Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac8966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 08/12/2022] [Indexed: 11/11/2022]
Abstract
Abstract
Objective. To measure the monoenergetic x-ray linear attenuation coefficient, μ, of fused deposition modeling (FDM) colored 3D printing materials (ABS, PLAwhite, PLAorange, PET and NYLON), used as adipose, glandular or skin tissue substitutes for manufacturing physical breast phantoms. Approach. Attenuation data (at 14, 18, 20, 24, 28, 30 and 36 keV) were acquired at Elettra synchrotron radiation facility, with step-wedge objects, using the Lambert–Beer law and a CCD imaging detector. Test objects were 3D printed using the Ultimaker 3 FDM printer. PMMA, Nylon-6 and high-density polyethylene step objects were also investigated for the validation of the proposed methodology. Printing uniformity was assessed via monoenergetic and polyenergetic imaging (32 kV, W/Rh). Main results. Maximum absolute deviation of μ for PMMA, Nylon-6 and HD-PE was 5.0%, with reference to literature data. For ABS and NYLON, μ differed by less than 6.1% and 7.1% from that of adipose tissue, respectively; for PET and PLAorange the difference was less than 11.3% and 6.3% from glandular tissue, respectively. PLAorange is a good substitute of skin (differences from −9.4% to +1.2%). Hence, ABS and NYLON filaments are suitable adipose tissue substitutes, while PET and PLAorange mimick the glandular tissue. PLAwhite could be printed at less than 100% infill density for matching the attenuation of glandular tissue, using the measured density calibration curve. The printing mesh was observed for sample thicknesses less than 60 mm, imaged in the direction normal to the printing layers. Printing dimensional repeatability and reproducibility was less 1%. Significance. For the first time an experimental determination was provided of the linear attenuation coefficient of common 3D printing filament materials with estimates of μ at all energies in the range 14–36 keV, for their use in mammography, breast tomosynthesis and breast computed tomography investigations.
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Mettivier G, di Franco F, Sarno A, Castriconi R, Di Lillo F, Bliznakova K, Russo P. In-Line Phase Contrast Mammography, Phase Contrast Digital Breast Tomosynthesis, and Phase Contrast Breast Computed Tomography With a Dedicated CT Scanner and a Microfocus X-Ray Tube: Experimental Phantom Study. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2021. [DOI: 10.1109/trpms.2020.3003380] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Brombal L, Arana Peña LM, Arfelli F, Longo R, Brun F, Contillo A, Di Lillo F, Tromba G, Di Trapani V, Donato S, Menk RH, Rigon L. Motion artifacts assessment and correction using optical tracking in synchrotron radiation breast CT. Med Phys 2021; 48:5343-5355. [PMID: 34252212 PMCID: PMC9291820 DOI: 10.1002/mp.15084] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 05/12/2021] [Accepted: 06/21/2021] [Indexed: 11/23/2022] Open
Abstract
Purpose The SYRMA‐3D collaboration is setting up a breast computed tomography (bCT) clinical program at the Elettra synchrotron radiation facility in Trieste, Italy. Unlike the few dedicated scanners available at hospitals, synchrotron radiation bCT requires the patient's rotation, which in turn implies a long scan duration (from tens of seconds to few minutes). At the same time, it allows the achievement of high spatial resolution. These features make synchrotron radiation bCT prone to motion artifacts. This article aims at assessing and compensating for motion artifacts through an optical tracking approach. Methods In this study, patients’ movements due to breathing have been first assessed on seven volunteers and then simulated during the CT scans of a breast phantom and a surgical specimen, by adding a periodic oscillatory motion (constant speed, 1 mm amplitude, 12 cycles/minute). CT scans were carried out at 28 keV with a mean glandular dose of 5 mGy. Motion artifacts were evaluated and a correction algorithm based on the optical tracking of fiducial marks was introduced. A quantitative analysis based on the structural similarity (SSIM) index and the normalized mean square error (nMSE) was performed on the reconstructed CT images. Results CT images reconstructed through the optical tracking procedure were found to be as good as the motionless reference image. Moreover, the analysis of SSIM and nMSE demonstrated that an uncorrected motion of the order of the system's point spread function (around 0.1 mm in the present case) can be tolerated. Conclusions Results suggest that a motion correction procedure based on an optical tracking system would be beneficial in synchrotron radiation bCT.
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Affiliation(s)
- Luca Brombal
- Department of Physics, University of Trieste, Trieste, Italy.,Division of Trieste, Istituto Nazionale di Fisica Nucleare, Trieste, Italy
| | - Lucia Mariel Arana Peña
- Department of Physics, University of Trieste, Trieste, Italy.,Division of Trieste, Istituto Nazionale di Fisica Nucleare, Trieste, Italy
| | - Fulvia Arfelli
- Department of Physics, University of Trieste, Trieste, Italy.,Division of Trieste, Istituto Nazionale di Fisica Nucleare, Trieste, Italy
| | - Renata Longo
- Department of Physics, University of Trieste, Trieste, Italy.,Division of Trieste, Istituto Nazionale di Fisica Nucleare, Trieste, Italy
| | - Francesco Brun
- Division of Trieste, Istituto Nazionale di Fisica Nucleare, Trieste, Italy.,Department of Engineering and Architecture, University of Trieste, Trieste, Italy
| | | | | | | | - Vittorio Di Trapani
- Department of Physical sciences, Earth and environment, University of Siena, Siena, Italy.,Division of Pisa, Istituto Nazionale di Fisica Nucleare, Pisa, Italy
| | - Sandro Donato
- Department of Physics, University of Calabria, Arcavacata di Rende, Cosenza, Italy.,Division of Frascati, Istituto Nazionale di Fisca Nucleare, Frascati, Rome, Italy
| | - Ralf Hendrik Menk
- Division of Trieste, Istituto Nazionale di Fisica Nucleare, Trieste, Italy.,Elettra-Sincrotrone Trieste S.C.p.A., Trieste, Italy.,Department of Medical Imaging, University of Saskatchewan, Saskatoon, Canada
| | - Luigi Rigon
- Department of Physics, University of Trieste, Trieste, Italy.,Division of Trieste, Istituto Nazionale di Fisica Nucleare, Trieste, Italy
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Chen R, Zhao S, Wu W, Sun Z, Wang J, Wang H, Han G. A convolutional neural network algorithm for breast tumor detection with magnetic detection electrical impedance tomography. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2021; 92:064701. [PMID: 34243519 DOI: 10.1063/5.0041423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 05/11/2021] [Indexed: 06/13/2023]
Abstract
Breast cancer is a malignant tumor disease for which early detection, diagnosis, and treatment are of paramount significance in prolonging the life of patients. Magnetic Detection Electrical Impedance Tomography (MDEIT) based on the Convolutional Neural Network (CNN), which aims to realize non-invasive, high resolution detection of breast tumors, is proposed. First, the MDEIT forward problem of the coronal and horizontal planes of the breast was simulated and solved using the Finite Element Method to obtain sample datasets of different lesions. Then, the CNN was built and trained to predict the conductivity distribution in different orientations of the breast model. Finally, noise and phantom experiments were performed in order to assess the anti-noise performance of the CNN algorithm and its feasibility of detecting breast tumors in practical applications. The simulation results showed that the reconstruction relative error with the CNN algorithm can be reduced to 10%, in comparison with the truncated singular value decomposition algorithm and back propagation algorithm. The CNN algorithm had better stability in the anti-noise performance test. When the noise of 60 dB was added, the shape of the breast tumor could still be restored by the CNN algorithm. The phantom experimental results showed that through the CNN based reconstruction algorithm, the reconstruction conductivity distribution image was legible and the position of the breast tumor could be determined. It is reasonable to conclude that the MDEIT reconstruction method proposed in this study has practical importance for the early and non-invasive detection of breast tumors.
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Affiliation(s)
- Ruijuan Chen
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Songsong Zhao
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Weiwei Wu
- School of Electronics and Information Engineering, Tiangong University, Tianjin 300387, China
| | - Zhihui Sun
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Jinhai Wang
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Huiquan Wang
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Guang Han
- School of Life Sciences, Tiangong University, Tianjin 300387, China
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Tseng HW, Karellas A, Vedantham S. Radiation dosimetry of a clinical prototype dedicated cone-beam breast CT system with offset detector. Med Phys 2021; 48:1079-1088. [PMID: 33501686 DOI: 10.1002/mp.14688] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 12/15/2020] [Accepted: 12/17/2020] [Indexed: 12/27/2022] Open
Abstract
PURPOSE A clinical-prototype, dedicated, cone-beam breast computed tomography (CBBCT) system with offset detector is undergoing clinical evaluation at our institution. This study is to estimate the normalized glandular dose coefficients ( DgN CT ) that provide air kerma-to-mean glandular dose conversion factors using Monte Carlo simulations. MATERIALS AND METHODS The clinical prototype CBBCT system uses 49 kV x-ray spectrum with 1.39 mm 1st half-value layer thickness. Monte Carlo simulations (GATE, version 8) were performed with semi-ellipsoidal, homogeneous breasts of various fibroglandular weight fractions ( f g = 0.01 , 0.15 , 0.5 , 1 ) , chest wall diameters ( d = 8 , 10 , 14 , 18 , 20 cm), and chest wall to nipple length ( l = 0.75 d ), aligned with the axis of rotation (AOR) located at 65 cm from the focal spot to determine the DgN CT . Three geometries were considered - 40 × 30 -cm detector with no offset that served as reference and corresponds to a clinical CBBCT system, 30 × 30 -cm detector with 5 cm offset, and a 30 × 30 -cm detector with 10 cm offset. RESULTS For 5 cm lateral offset, the DgN CT ranged 0.177 - 0.574 mGy/mGy and reduction in DgN CT with respect to reference geometry was observed only for 18 cm ( 6.4 % ± 0.23 % ) and 20 cm ( 9.6 % ± 0.22 % ) diameter breasts. For the 10 cm lateral offset, the DgN CT ranged 0.221 - 0.581 mGy/mGy and reduction in DgN CT was observed for all breast diameters. The reduction in DgN CT was 1.4 % ± 0.48 % , 7.1 % ± 0.13 % , 17.5 % ± 0.19 % , 25.1 % ± 0.15 % , and 27.7 % ± 0.08 % for 8, 10, 14, 18, and 20 cm diameter breasts, respectively. For a given breast diameter, the reduction in DgN CT with offset-detector geometries was not dependent on f g . Numerical fits of DgN CT d , l , f g were generated for each geometry. CONCLUSION The DgN CT and the numerical fit, D g N CT d , l , f g would be of benefit for current CBBCT systems using the reference geometry and for future generations using offset-detector geometry. There exists a potential for radiation dose reduction with offset-detector geometry, provided the same technique factors as the reference geometry are used, and the image quality is clinically acceptable.
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Affiliation(s)
- Hsin Wu Tseng
- Department of Medical Imaging, The University of Arizona, Tucson, AZ, USA
| | - Andrew Karellas
- Department of Medical Imaging, The University of Arizona, Tucson, AZ, USA
| | - Srinivasan Vedantham
- Department of Medical Imaging, The University of Arizona, Tucson, AZ, USA.,Department of Biomedical Engineering, The University of Arizona, Tucson, AZ, USA
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