2018 Fiscal Year Final Research Report
Fundamental study for the substance identified in photon counting mammography
| Project/Area Number |
16K09015
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Medical Physics and Radiological Technology
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| Research Institution | Kyoto College of Medical Science (2017-2018)
Nagoya University (2016) |
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Principal Investigator |
Kodera Yoshie 京都医療科学大学, 医療科学部, 研究員 (10124794)
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| Co-Investigator(Kenkyū-buntansha) |
小山 修司 名古屋大学, 脳とこころの研究センター, 准教授 (20242878)
西出 裕子 岐阜医療科学大学, 保健科学部, 准教授 (80635730)
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| Research Collaborator |
Mizutani Mitsuhiro
Watanabe Megumi
Yoshida Naoko
Yamamoto Shuichiro
Hashimoto Daisuke
Okada Masahiro
Nakajima Ai
Sasaki Mariko
Suzuki Reina
Kimura Hiroto
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| Project Period (FY) |
2016-10-21 – 2019-03-31
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| Keywords | フォトンカウンティング技術 / マンモグラフィ / 物質同定 / 実効原子番号 / コントラスト対雑音比 / 被曝低減 |
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| Outline of Final Research Achievements |
In analog systems, high contrast images are necessary to identify breast cancer. However, in the digital system, high CNR (contrast-to-noise ratio) is required. A novel energy-resolved photon-counting mammography (ERPCM) is being developed using a cadmium zinc telluride detector. The purpose of this study is to examine whether to obtain the higher CNR image using higher tube voltage, and is to create a novel fusion medical image of anatomy and physics, and explore the clinical meaning of this image. It was suggested that there is the usefulness of using high tube voltage for thicker and dense breast. On the scatterplots, it could discriminate the tumor values from normal tissue values for each case by a case. And on the fusion images, by coloring to around 20% from the top of the scatter points, the tumors on the images which the same part was diagnosed as a tumor were colored.
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| Free Research Field |
放射線画像工学
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| Academic Significance and Societal Importance of the Research Achievements |
連続スペクトルを持つX線のスペクトル情報の利用は、多くの医療関係者の望むところであり、現在種々の研究開発が行われているが、いまだその最終目的は達成されていない。本研究は、独自の解析方法を用いることで精度よく生体内の物質の同定に成功し、その可視化も実現している。今後、本手法を用いることで、これまでにはない新たな生体情報の取得が可能になり、画像診断の可能性の大きく広がることが期待できる。
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