| Project/Area Number |
18K08575
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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 55010:General surgery and pediatric surgery-related
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| Research Institution | Kochi University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
星野 絵里 立命館大学, 総合科学技術研究機構, 准教授 (50598521)
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| Project Period (FY) |
2018-04-01 – 2023-03-31
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| Project Status |
Completed (Fiscal Year 2022)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2022: ¥260,000 (Direct Cost: ¥200,000、Indirect Cost: ¥60,000)
Fiscal Year 2021: ¥260,000 (Direct Cost: ¥200,000、Indirect Cost: ¥60,000)
Fiscal Year 2020: ¥130,000 (Direct Cost: ¥100,000、Indirect Cost: ¥30,000)
Fiscal Year 2019: ¥260,000 (Direct Cost: ¥200,000、Indirect Cost: ¥60,000)
Fiscal Year 2018: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
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| Keywords | 人工知能 / 便色 / 早期発見 / 胆道閉鎖症 / 胆汁うっ滞性肝疾患 / アプリケーション / AI（人工知能） / 胆道閉鎖所 / AI / スクリーニング / 画像診断 / 胆汁鬱滞性肝疾患 / 新生児乳児検診 |
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| Outline of Final Research Achievements |
The number of cases (mean birth weight, mean weeks of gestation) at the four facilities participating in this study was 2463, including facility A: 767 cases (2931 g, 38 weeks 6 days), facility B: 289 cases (3013 g, 39 weeks 1 day), facility C: 596 cases (2881 g, 38 weeks 2 days), and facility D: 811 cases (3066 g, 39 weeks 4 days). This corresponded to 71.5% of all births during the study period. The results were 96.59% "no abnormality", 0.14% "necessary observation,", and 3.29% "be careful". Surgical treatment was performed in 2 of the 84 cases judged to be "necessary observation" and "be careful", and the sensitivity and specificity for detecting liver disease requiring surgical treatment were 100% and 96.7%, respectively. This study was considered useful as a method for early detection of biliary atresia and biliary congestive disease.
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| Academic Significance and Societal Importance of the Research Achievements |
胆道閉鎖症および胆汁うっ滞性肝疾患の早期発見のため母子手帳に添付されている便色カラーカードは簡便で安価なスクリーニング法であり、海外での使用も報告されている。しかし肉眼で児の便色と比較するため主観的判断による見逃しや診断遅れなどが問題となっている。本研究のAIによる判定は人間の目で認識・判断する必要が無く、プログラムが微細な色調変化を的確に診断することでより早期の疾患の発見が可能となり、便色カラーカードに替わる方法として期待される。
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