Curriculum Vitaes
Profile Information
- Affiliation
- Professor (Professor and Chairman), School of Medicine, Faculty of Medicine, Fujita Health University
- Degree
- MD, PhD(Mar, 1998, Kobe University Graduate School of Medicine)
- Contact information
- yohno
fujita-hu.ac.jp - ORCID ID
https://orcid.org/0000-0002-4431-1084- J-GLOBAL ID
- 200901037501461104
- researchmap Member ID
- 1000372100
Research Interests
6Research Areas
2Research History
3-
Apr, 2019 - May, 2023
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Apr, 2012 - Mar, 2019
Education
1-
- Mar, 1998
Committee Memberships
28-
Oct, 2024 - Present
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Jun, 2024 - Present
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Sep, 2022 - Present
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Sep, 2020 - Present
Awards
42Papers
336-
Radiology: Cardiothoracic Imaging, Oct 1, 2025
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European Radiology, May 22, 2025
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European radiology, Feb 4, 2025OBJECTIVE: To directly compare coronary arterial stenosis evaluations by hybrid-type iterative reconstruction (IR), model-based IR (MBIR), deep learning reconstruction (DLR), and high-resolution deep learning reconstruction (HR-DLR) on coronary computed tomography angiography (CCTA) in both in vitro and in vivo studies. MATERIALS AND METHODS: For the in vitro study, a total of three-vessel tube phantoms with diameters of 3 mm, 4 mm, and 5 mm and with simulated non-calcified stepped stenosis plaques with degrees of 0%, 25%, 50%, and 75% stenosis were scanned with area-detector CT (ADCT) and ultra-high-resolution CT (UHR-CT). Then, ADCT data were reconstructed using all methods, although UHR-CT data were reconstructed with hybrid-type IR, MBIR, and DLR. For the in vivo study, patients who had undergone CCTA at ADCT were retrospectively selected, and each CCTA data set was reconstructed with all methods. To compare the image noise and measurement accuracy at each of the stenosis levels, image noise, and inner diameter were evaluated and statistically compared. To determine the effect of HR-DLR on CAD-RADS evaluation accuracy, the accuracy of CAD-RADS categorization of all CCTAs was compared by using McNemar's test. RESULTS: The image noise of HR-DLR was significantly lower than that of others on ADCT and UHR-CT (p < 0.0001). At a 50% and 75% stenosis level for each phantom, hybrid-type IR showed a significantly larger mean difference on ADCT than did others (p < 0.05). At in vivo study, 31 patients were included. Accuracy on HR-DLR was significantly higher than that on hybrid-type IR, MBIR, or DLR (p < 0.0001). CONCLUSION: HR-DLR is potentially superior for coronary arterial stenosis evaluations to hybrid-type IR, MBIR, or DLR shown on CCTA. KEY POINTS: Question How do coronary arterial stenosis evaluations by hybrid-type IR, MBIR, DLR, and HR-DLR compare to coronary CT angiography? Findings HR-DLR showed significantly lower image noise and more accurate coronary artery disease reporting and data system (CAD-RADS) evaluation than others. Clinical relevance HR-DLR is potentially superior to other reconstruction methods for coronary arterial stenosis evaluations, as demonstrated by coronary CT angiography results on ADCT and as shown in both in vitro and in vivo studies.
Misc.
621-
Radiology, 299(3) 524-538, Jun 1, 2021
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Radiology, 299(3) 508-523, Jun 1, 2021
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新医療, 47(4) 24-27, Apr, 2020
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THE LUNG-perspectives, 27(2) 113-119, May, 2019
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CT検診, 26(1) 47-47, Feb, 2019
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Journal of magnetic resonance imaging : JMRI, 47(6) 1437-1458, Jun, 2018 Peer-reviewedSince the clinical introduction of magnetic resonance imaging (MRI), the chest has been one of its most challenging applications, and many physicists and radiologists have tried since the 1980s to use MR for assessment of different lung diseases as well as mediastinal and pleural diseases. Since then, however, technical advances in sequencing, scanners, and coils, adaptation of parallel imaging techniques, utilization of contrast media, and development of postprocessing tools have been reported by many basic and clinical researchers. As a result, state-of-the-art thoracic MRI is now substituted for traditional imaging techniques and/or plays a complementary role in the management of patients with various chest diseases, and especially in the detection of pulmonary nodules and in thoracic oncology. In addition, MRI has continued to be developed to help overcome the limitations of computed tomography (CT) and nuclear medicine examinations. It can currently provide not only morphological, but also functional, physiological, pathophysiological, and molecular information at 1.5T with a gradual shift from 1.5T to 3T MR systems. In this review, we focus on these recent advances in MRI for pulmonary nodule detection and pulmonary nodule and mass evaluation by using noncontrast-enhanced and contrast-enhanced techniques as well as new molecular imaging methods such as chemical exchange saturation transfer imaging for a comparison with other modalities such as single or multidetector row CT, 18F-fluoro-2-deoxyglucose positron emission tomography (FDG-PET), and/or PET/CT. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1437-1458.
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CT検診, 25(1) 50-50, Feb, 2018
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Radiology, 284(1) 228-243, Jul, 2017 Peer-reviewed
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RADIOLOGY, 282(3) 923-923, Mar, 2017
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AJR. American journal of roentgenology, 208(3) 517-530, Mar, 2017 Peer-reviewed
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European journal of radiology, 86 313-319, Jan, 2017 Peer-reviewed
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European journal of radiology, 86 353-360, Jan, 2017 Peer-reviewed
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European journal of radiology, 86 297-307, Jan, 2017 Peer-reviewed
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European journal of radiology, 86 361-370, Jan, 2017 Peer-reviewed
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INNERVISION, 31(7) 76-78, Jun, 2016
Books and Other Publications
25Presentations
800-
The 6th International Congress on Magnetic Resonance Imaging (ICMRI 2018) and 23rd Scientific Meeting of KSMRM, Mar, 2018
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第25回日本CT検診学会学術集会, Feb, 2018, 日本CT検診学会 Invited
Teaching Experience
1-
イメージング (神戸大学)
Professional Memberships
18Research Projects
22-
Grants-in-Aid for Scientific Research, Japan Society for the Promotion of Science, Apr, 2025 - Mar, 2028
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Grants-in-Aid for Scientific Research, Japan Society for the Promotion of Science, Apr, 2025 - Mar, 2028
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科学研究費助成事業, 日本学術振興会, Apr, 2023 - Mar, 2026
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科学研究費助成事業, 日本学術振興会, Apr, 2022 - Mar, 2025
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科学研究費助成事業, 日本学術振興会, Apr, 2021 - Mar, 2024