2017 Fiscal Year Final Research Report
Development of a new-generation medical imaging diagnosis system integrating artificial intelligence and risk models
| Project/Area Number |
15K09947
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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 |
Radiation science
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| Research Institution | Kanazawa University |
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Principal Investigator |
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| Co-Investigator(Renkei-kenkyūsha) |
Okuda Koichi 金沢医科大学, 一般教育機構, 講師 (60639938)
Matsuo Shinro 金沢大学附属病院, 講師 (30359773)
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Keywords | 人工ニューラルネットワーク / 虚血性心疾患 / 心不全 / 心筋血流イメージング / 心臓交感神経イメージング / リスクモデル / 心臓核医学 / 多施設研究 |
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| Outline of Final Research Achievements |
Clinical diagnosis of ischemic heart disease and heart failure is based on integrated assessment of clinical course, blood sampling, and imaging. The aim of this study was to create models by artificial intelligence or multivariable statistical analysis. Databases of patients with cardiac diseases were made by multicenter collaboration. With respect to myocardial perfusion imaging, using feature extractions and neural networks, diagnostic accuracy reached a level of expert interpretation. In patients with heart failure, multivariable risk model including 123I-metaiodobenzylguanidine successfully provided risk of cardiac death. Both algorithms were prepared as software for clinical uses.
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| Free Research Field |
核医学
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