| Project/Area Number |
18K07694
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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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| Review Section |
Basic Section 52040:Radiological sciences-related
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| Research Institution | Fujita Health University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
外山 宏 藤田医科大学, 医学部, 教授 (90247643)
中原 一郎 藤田医科大学, 医学部, 教授 (80252451)
小田 淳平 藤田医科大学, 医学部, 講師 (30630040)
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2020: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2019: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2018: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
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| Keywords | 高精細CT / ディープラーニング / 被ばく低減 / CT血管造影 / 頭蓋内細動脈 / CT angiography / 高分解能CTA / 脳血管細動脈 |
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| Outline of Final Research Achievements |
The newly developed ultra-high resolution CT (UHR-CT), can visualizing small blood vessels more clearly compared with than conventional detector CT (C-CT). We determined if UHR-CTA produced superior images of the lenticulostriate arteries (LSA), compared to C-CTA. UHR-CT provides significantly higher-quality images, compared to the C-CT because of its improved spatial resolution and partial volume effect. UHR-CTA is a simple, noninvasive and easily accessible method to investigate the shape, number and length of lenticulostriate arteries.
In addition, we directly compare the capability for image quality improvements on brain contrast-enhanced CT angiography (CE-CTA) for UHR-CT in intracranial aneurysms patients among deep learning reconstruction (DLR) and hybrid-type iterative reconstruction (IR) and model-based IRs. DLR has a potential for image quality improvements than hybrid-type and model-based IRs on brain CE-CTA for UHR-CT.
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| Academic Significance and Societal Importance of the Research Achievements |
高精細CT装置は、従来型検出器CT装置と比較してより細かい構造の描出が可能である。従来型CTと比べ高精細CTで有意に細動脈の描出能が改善され,脳外科領域で臨床的に重要な細動脈及び静脈系における，高精細CTを用いた高分解能CT血管造影の有用性が示された。
高精細CTでは被ばく線量の増加が懸念されるため、被ばく低減技術の併用が重要となる。ディープラーニングを用いたノイズ成分とシグナル成分を識別し分解能を維持したままノイズを選択的に除去する新しい被ばく低減技術では，従来法と比べて，高精細CTを用いた頭部CTAにおける描出能の改善に寄与する可能性があることが示された。
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