| Project/Area Number |
17K15804
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Medical Physics and Radiological Technology
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| Research Institution | Kumamoto University |
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Principal Investigator |
Oda Seitaro 熊本大学, 大学院生命科学研究部(医), 特任講師 (80571041)
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2019: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2018: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2017: ¥2,990,000 (Direct Cost: ¥2,300,000、Indirect Cost: ¥690,000)
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| Keywords | 多層検出器CT / 冠動脈プラーク / multi-energy解析 / 冠動脈脆弱性プラーク |
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| Outline of Final Research Achievements |
In this study, coronary vulnerable plaques could be classified with high accuracy by comprehensively evaluating the histogram features extracted from multi-energy data by multi-layer detector CT using a machine learning (random forest) models. This had significantly higher diagnostic performance than standard CT images had. Moreover, the diagnostic ability was significantly higher than that of the conventional analysis method using mean CT value. By using this new method, accurate characterization of coronary plaque can be possible, and it may contribute to the decision of an appropriate therapeutic strategy.
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| Academic Significance and Societal Importance of the Research Achievements |
多層検出器CT によるmulti-energy dataを使用することにより、これまでよりも正確な冠動脈プラーク評価が可能となり、より適切な診療マネージメントが可能になると考えられる。このことは、急性冠症候群の発症抑制に寄与し、臨床診療の側面だけでなく、医療経済的にも意義が大きいと考える。
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