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Nishii T, Kobayashi T, Tanaka H, Kotoku A, Ohta Y, Morita Y, Umehara K, Ota J, Horinouchi H, Ishida T, Fukuda T. Deep Learning-based Post Hoc CT Denoising for Myocardial Delayed Enhancement. Radiology 2022; 305:82-91. [PMID: 35762889 DOI: 10.1148/radiol.220189] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background To improve myocardial delayed enhancement (MDE) CT, a deep learning (DL)-based post hoc denoising method supervised with averaged MDE CT data was developed. Purpose To assess the image quality of denoised MDE CT images and evaluate their diagnostic performance by using late gadolinium enhancement (LGE) MRI as a reference. Materials and methods MDE CT data obtained by averaging three acquisitions with a single breath hold 5 minutes after the contrast material injection in patients from July 2020 to October 2021 were retrospectively reviewed. Preaveraged images obtained in 100 patients as inputs and averaged images as ground truths were used to supervise a residual dense network (RDN). The original single-shot image, standard averaged image, RDN-denoised original (DLoriginal) image, and RDN-denoised averaged (DLave) image of holdout cases were compared. In 40 patients, the CT value and image noise in the left ventricular cavity and myocardium were assessed. The segmental presence of MDE in the remaining 40 patients who underwent reference LGE MRI was evaluated. The sensitivity, specificity, and accuracy of each type of CT image and the improvement in accuracy achieved with the RDN were assessed using odds ratios (ORs) estimated with the generalized estimation equation. Results Overall, 180 patients (median age, 66 years [IQR, 53-74 years]; 107 men) were included. The RDN reduced image noise to 28% of the original level while maintaining equivalence in the CT values (P < .001 for all). The sensitivity, specificity, and accuracy of the original images were 77.9%, 84.4%, and 82.3%, of the averaged images were 89.7%, 87.9%, and 88.5%, of the DLoriginal images were 93.1%, 87.5%, and 89.3%, and of the DLave images were 95.1%, 93.1%, and 93.8%, respectively. DLoriginal images showed improved accuracy compared with the original images (OR, 1.8 [95% CI: 1.2, 2.9]; P = .011) and DLave images showed improved accuracy compared with the averaged images (OR, 2.0 [95% CI: 1.2, 3.5]; P = .009). Conclusion The proposed denoising network supervised with averaged CT images reduced image noise and improved the diagnostic performance for myocardial delayed enhancement CT. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Vannier and Wang in this issue.
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Affiliation(s)
- Tatsuya Nishii
- From the Department of Radiology, National Cerebral and Cardiovascular Center, 6-1 Kishibe-shinmachi, Suita 564-8565, Japan (T.N., T.K., H.T., A.K., Y.O., Y.M., H.H., T.F.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Japan (T.K., K.U., J.O., T.I.); Medical Informatics Section, QST Hospital (K.U., J.O.), and Applied MRI Research, Department of Molecular Imaging and Theranostics, Institute for Quantum Medical Science (K.U., J.O.), National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Takuma Kobayashi
- From the Department of Radiology, National Cerebral and Cardiovascular Center, 6-1 Kishibe-shinmachi, Suita 564-8565, Japan (T.N., T.K., H.T., A.K., Y.O., Y.M., H.H., T.F.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Japan (T.K., K.U., J.O., T.I.); Medical Informatics Section, QST Hospital (K.U., J.O.), and Applied MRI Research, Department of Molecular Imaging and Theranostics, Institute for Quantum Medical Science (K.U., J.O.), National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Hironori Tanaka
- From the Department of Radiology, National Cerebral and Cardiovascular Center, 6-1 Kishibe-shinmachi, Suita 564-8565, Japan (T.N., T.K., H.T., A.K., Y.O., Y.M., H.H., T.F.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Japan (T.K., K.U., J.O., T.I.); Medical Informatics Section, QST Hospital (K.U., J.O.), and Applied MRI Research, Department of Molecular Imaging and Theranostics, Institute for Quantum Medical Science (K.U., J.O.), National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Akiyuki Kotoku
- From the Department of Radiology, National Cerebral and Cardiovascular Center, 6-1 Kishibe-shinmachi, Suita 564-8565, Japan (T.N., T.K., H.T., A.K., Y.O., Y.M., H.H., T.F.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Japan (T.K., K.U., J.O., T.I.); Medical Informatics Section, QST Hospital (K.U., J.O.), and Applied MRI Research, Department of Molecular Imaging and Theranostics, Institute for Quantum Medical Science (K.U., J.O.), National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Yasutoshi Ohta
- From the Department of Radiology, National Cerebral and Cardiovascular Center, 6-1 Kishibe-shinmachi, Suita 564-8565, Japan (T.N., T.K., H.T., A.K., Y.O., Y.M., H.H., T.F.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Japan (T.K., K.U., J.O., T.I.); Medical Informatics Section, QST Hospital (K.U., J.O.), and Applied MRI Research, Department of Molecular Imaging and Theranostics, Institute for Quantum Medical Science (K.U., J.O.), National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Yoshiaki Morita
- From the Department of Radiology, National Cerebral and Cardiovascular Center, 6-1 Kishibe-shinmachi, Suita 564-8565, Japan (T.N., T.K., H.T., A.K., Y.O., Y.M., H.H., T.F.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Japan (T.K., K.U., J.O., T.I.); Medical Informatics Section, QST Hospital (K.U., J.O.), and Applied MRI Research, Department of Molecular Imaging and Theranostics, Institute for Quantum Medical Science (K.U., J.O.), National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Kensuke Umehara
- From the Department of Radiology, National Cerebral and Cardiovascular Center, 6-1 Kishibe-shinmachi, Suita 564-8565, Japan (T.N., T.K., H.T., A.K., Y.O., Y.M., H.H., T.F.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Japan (T.K., K.U., J.O., T.I.); Medical Informatics Section, QST Hospital (K.U., J.O.), and Applied MRI Research, Department of Molecular Imaging and Theranostics, Institute for Quantum Medical Science (K.U., J.O.), National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Junko Ota
- From the Department of Radiology, National Cerebral and Cardiovascular Center, 6-1 Kishibe-shinmachi, Suita 564-8565, Japan (T.N., T.K., H.T., A.K., Y.O., Y.M., H.H., T.F.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Japan (T.K., K.U., J.O., T.I.); Medical Informatics Section, QST Hospital (K.U., J.O.), and Applied MRI Research, Department of Molecular Imaging and Theranostics, Institute for Quantum Medical Science (K.U., J.O.), National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Hiroki Horinouchi
- From the Department of Radiology, National Cerebral and Cardiovascular Center, 6-1 Kishibe-shinmachi, Suita 564-8565, Japan (T.N., T.K., H.T., A.K., Y.O., Y.M., H.H., T.F.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Japan (T.K., K.U., J.O., T.I.); Medical Informatics Section, QST Hospital (K.U., J.O.), and Applied MRI Research, Department of Molecular Imaging and Theranostics, Institute for Quantum Medical Science (K.U., J.O.), National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Takayuki Ishida
- From the Department of Radiology, National Cerebral and Cardiovascular Center, 6-1 Kishibe-shinmachi, Suita 564-8565, Japan (T.N., T.K., H.T., A.K., Y.O., Y.M., H.H., T.F.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Japan (T.K., K.U., J.O., T.I.); Medical Informatics Section, QST Hospital (K.U., J.O.), and Applied MRI Research, Department of Molecular Imaging and Theranostics, Institute for Quantum Medical Science (K.U., J.O.), National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Tetsuya Fukuda
- From the Department of Radiology, National Cerebral and Cardiovascular Center, 6-1 Kishibe-shinmachi, Suita 564-8565, Japan (T.N., T.K., H.T., A.K., Y.O., Y.M., H.H., T.F.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Japan (T.K., K.U., J.O., T.I.); Medical Informatics Section, QST Hospital (K.U., J.O.), and Applied MRI Research, Department of Molecular Imaging and Theranostics, Institute for Quantum Medical Science (K.U., J.O.), National Institutes for Quantum Science and Technology, Chiba, Japan
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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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