| Project/Area Number |
17H06819
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| Research Category |
Grant-in-Aid for Research Activity Start-up
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| Allocation Type | Single-year Grants |
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| Research Field |
Ophthalmology
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| Research Institution | Kyoto University |
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Principal Investigator |
Uji Akihito 京都大学, 医学研究科, 特定助教 (60534302)
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| Research Collaborator |
Ooto Sotaro
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| Project Period (FY) |
2017-08-25 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2017: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | 補償光学 / 網膜 / 網膜循環 / 光干渉断層系 / 黄斑疾患 / 眼科 |
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| Outline of Final Research Achievements |
Human retinal ganglion cells (RGCs) in healthy eyes were succesfully visualized and evaluated in vivo by using the prototype AO-OCT system.T he cells detected in the GCL were highly concordant with histological investigations of the human eye that have been previously reported. The cell density was negatively correlated with age.
The impact of deep learning reconstruction (DLR) method on quantitative measurements of retinal microvasculature and image quality of optical coherence tomography angiography (OCTA) has been investigated. We found that DLR image has much better image quality than averaged OCTA image in shorter time.
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| Academic Significance and Societal Importance of the Research Achievements |
補償光学を用いることで、従来可視化できなかった網膜の微細構造がＯＣＴでも可視化できることが示された。また人工知能を用いることでOCT imagingが飛躍的に良化することが示された。非侵襲的に病理組織並みの画像が得られることにより、黄斑疾患の早期発見、早期治療の実現、病態解明や創薬の領域において細胞レベルでのモニタリングにも貢献できると考えられる。
今回の研究で得られた知見は国内メーカー、研究所のハードウェア、ソフトウェア開発に大きな影響を与えると考えられ、それらの国際競争力を高め、網膜画像研究を加速させることが期待される。
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