Comparison of 3D constructed CT images and pathological findings of interstitial pneumonia
| Project/Area Number |
15K09184
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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 |
Respiratory organ internal medicine
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| Research Institution | Nagoya City University |
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Principal Investigator |
Ohkubo Hirotsugu 名古屋市立大学, 大学院医学研究科, 講師 (70408144)
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| Co-Investigator(Kenkyū-buntansha) |
新實 彰男 名古屋市立大学, 大学院医学研究科, 教授 (30252513)
難波 大夫 名古屋市立大学, 大学院医学研究科, 講師 (40381793)
森山 悟 名古屋市立大学, 大学院医学研究科, 研究員 (50551264)
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| Project Period (FY) |
2015-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2018: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2017: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2016: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2015: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | 間質性肺炎 / ３次元構築画像 / ボリュームレンダリング / 人工知能 / ディープラーニング / ボリュームレンダリング法 / 線維化性間質性肺炎 / CT / 画像解析 / 機械学習 |
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| Outline of Final Research Achievements |
Our 3D constructed CT images using volume rendering method showed similar findings of the pathology (loupe findings) of interstitial lung disease. Heterogenicity was discovered in the 3D constructed CT images using volume rendering method, that was typical for usual interstitial pneumonia (UIP). Furthermore, honeycomb lung was found to be a funicular structure that was vertical from pleura. We found traction bronchiectasis surrounded by ground glass opacity was an important finding in UIP. In non-specific interstitial pneumonia, heterogeneity was not found in the 3D constructed CT images. We recruited larger cohort by multi-center study. The trial using deep learning method was ongoing for the diagnose of interstitial pneumonia.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究では、CT画像での判別が難解である間質性肺炎のCT画像から３次元画像を構築することで、将来の新しい間質性肺炎の診断方法に貢献したといえる。CTからの情報を病理所見と照らし合わせてその正確性を追求した。得られた結果は、予後不良である間質性肺炎のより優れた診断法につながり、治療選択においても意義のあるものへとつながっていくと考える。また、近年脚光を浴びている人工知能（AI）の研究へと発展させ、近未来の間質性肺炎診断にむけての研究を展開している。
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Report
(5 results)
Research Products
(21 results)
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[Journal Article] Remarkable Improvement in a Patient with Idiopathic Pulmonary Fibrosis after Treatment with Nintedanib2019
Author(s)
Nakano A, Ohkubo H, Fukumitsu K, Fukuda S, Kanemitsu Y, Takemura M, Maeno K, Ito Y, Oguri T, Niimi A.
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Journal Title
Internal Medicine
Volume: 58
Issue: 8
Pages: 1141-1144
DOI
NAID
ISSN
0918-2918, 1349-7235
Year and Date
2019-04-15
Related Report
Peer Reviewed / Open Access
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[Journal Article] Normal Lung Quantification in Usual Interstitial Pneumonia Pattern: The Impact of Threshold-based Volumetric CT Analysis for the Staging of Idiopathic Pulmonary Fibrosis.2016
Author(s)
Ohkubo H, Kanemitsu Y, Uemura T, Takakuwa O, Takemura M, Maeno K, Ito Y, Oguri T, Kazawa N, Mikami R, Niimi A.
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Journal Title
PLoS One
Volume: 11
Issue: 3
Pages: e0152505-e0152505
DOI
Related Report
Peer Reviewed / Open Access
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[Book] 日本医事新報2016
Author(s)
大久保 仁嗣、新実 彰男
Total Pages
1
Publisher
（株）日本医事新報社
Related Report
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