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Next-generation computer-aided diagnosis for early detection of dementia using person's genotype and radiomic features

Research Project

Project/Area Number 17K09067
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Medical Physics and Radiological Technology
Research InstitutionKumamoto University

Principal Investigator

Yoshikazu Uchiyama  熊本大学, 大学院生命科学研究部(保), 准教授 (50325172)

Project Period (FY) 2017-04-01 – 2020-03-31
Project Status Completed (Fiscal Year 2019)
Budget Amount *help
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2019: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2017: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Keywordsアルツハイマー型認知症 / 遺伝子 / MR画像 / コンピュータ支援診断 / Radiogenomics / 認知症
Outline of Final Research Achievements

We constructed next-generation computer-aided diagnosis by the integration analysis of genetic and image tests. We found that the process of disease formation is different in mild cognitive impairment and Alzheimer’s diseases (AD) according to the APOE genotype. Therefore, the early detection of AD would be possible by the image interpretation considering patient’s genotype. We also developed a method for distinguishing normal patients from ADs on the eigenspace by creating an eigenspace from normal MR images of 60, 70 and 80 ages. The proposed method made it possible to quantitatively evaluate the degree of cerebral atrophy considering the effects of normal aging. Since this method represents cerebral atrophy in a low-dimensional eigenspace, it has the advantage of avoiding the multiple test problem without setting a region of interest at a specific part of the brain.

Academic Significance and Societal Importance of the Research Achievements

遺伝子検査と画像検査の統合解析による次世代型のコンピュータ支援診断の新しい概念の研究を構築した点で学術的意義は大きい.この新しい概念は,認知症以外の他疾患にも適用可能であり,関連分野の進展に貢献できる.遺伝学的検査によって個人の遺伝型が特定できれば,認知症になりやすい患者群を特定することができる.そのような患者群は,発症を早期に発見するために,定期的な検査が行われるであろう.定期検査の際に,その患者の遺伝型に関係する画像特徴の変化(脳萎縮)が特定できれば,その変化に注目して読影を行うことができるため,現在よりも早期に病気を検出できる可能性が高く,社会的意義も大きい.

Report

(4 results)
  • 2019 Annual Research Report   Final Research Report ( PDF )
  • 2018 Research-status Report
  • 2017 Research-status Report
  • Research Products

    (15 results)

All 2020 2019 2018 2017

All Journal Article (4 results) (of which Peer Reviewed: 2 results) Presentation (10 results) (of which Invited: 4 results) Book (1 results)

  • [Journal Article] 脳疾患におけるレディオゲノミクス2020

    • Author(s)
      内山良一
    • Journal Title

      Medical Imaging Technology

      Volume: 38 Pages: 15-20

    • NAID

      130007796410

    • Related Report
      2019 Annual Research Report
  • [Journal Article] Radiomicsによる分子分類と治療戦略2020

    • Author(s)
      内山良一
    • Journal Title

      医学物理

      Volume: 40 Pages: 19-22

    • NAID

      130007823202

    • Related Report
      2019 Annual Research Report
  • [Journal Article] Computer-aided diagnosis with radiogenomics: Analysis of the relationship between genotype and morphological changes of the brain magnetic resonance images2018

    • Author(s)
      C.Kai, Y.Uchiyama, J.Shiraishi, H.Fujita, K.Doi
    • Journal Title

      Radiological physics and technology

      Volume: 11 Issue: 3 Pages: 265-273

    • DOI

      10.1007/s12194-018-0462-5

    • NAID

      130007739858

    • Related Report
      2018 Research-status Report
    • Peer Reviewed
  • [Journal Article] Quantitation of Cerebral Atrophy due to Normal Aging: Principal Component Analysis with MR Images in Patients’ Age Groups2018

    • Author(s)
      甲斐千遥, 内山良一, 白石順二, 藤田広志
    • Journal Title

      Japanese Journal of Radiological Technology

      Volume: 74 Issue: 12 Pages: 1389-1395

    • DOI

      10.6009/jjrt.2018_JSRT_74.12.1389

    • NAID

      130007535715

    • ISSN
      0369-4305, 1881-4883
    • Related Report
      2018 Research-status Report
    • Peer Reviewed
  • [Presentation] 合同シンポジウム Radiomicsによる鑑別診断と予後予測2019

    • Author(s)
      内山良一
    • Organizer
      本放射線技術学会第75回総会学術大会
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] 基調講演 AI・Deep Learning・Radiomicsの基礎と現状2019

    • Author(s)
      内山良一
    • Organizer
      第5回福岡県診療放射線技師会学術大会
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] RadiogenomicsにおけるSystems Biology2019

    • Author(s)
      内山良一
    • Organizer
      医用画像情報学会春季大会
    • Related Report
      2018 Research-status Report
  • [Presentation] 病変の表現型と遺伝子型の関係を探索する画像データマイニング2018

    • Author(s)
      甲斐千遥,内山良一,白石順二,藤田広志
    • Organizer
      医用画像情報学会秋季大会
    • Related Report
      2018 Research-status Report
  • [Presentation] RadiomicsによるCAD・CATSシステムの開発2018

    • Author(s)
      内山良一,甲斐千遥,吉岡拓弥,石丸真子,金子沙世
    • Organizer
      第180回医用画像情報学会大会
    • Related Report
      2017 Research-status Report
  • [Presentation] 遺伝子型と画像特徴を用いたコンピュータ支援診断:軽度認知障害とアルツハイマー型認知症の脳萎縮の定量評価2017

    • Author(s)
      甲斐千遥,内山良一,白石順二,藤田広志
    • Organizer
      第36回日本医用画像工学会大会
    • Related Report
      2017 Research-status Report
  • [Presentation] Radiogenomicsによる診断支援と予後予測2017

    • Author(s)
      内山良一
    • Organizer
      日本放射線技術学会第73回総会学術大会
    • Related Report
      2017 Research-status Report
    • Invited
  • [Presentation] Computer-Aided Diagnosis and Prognostic Prediction Based on Radiogenomics2017

    • Author(s)
      Y.Uchiyama
    • Organizer
      計測自動制御学会ライフエンジニアリング部門シンポジウム
    • Related Report
      2017 Research-status Report
    • Invited
  • [Presentation] Computer-Aided Diagnosis Scheme Based on Radiogenomics for the Detection of Alzheimer's Diseases2017

    • Author(s)
      C.Kai, Y.Uchiyama
    • Organizer
      第6回生命医薬情報学連合大会
    • Related Report
      2017 Research-status Report
  • [Presentation] 正常老化による脳萎縮の推移を分析するための時空間統計モデル2017

    • Author(s)
      甲斐千遥,内山良一,白石順二,藤田広志
    • Organizer
      第45回日本放射線技術学会秋季大会
    • Related Report
      2017 Research-status Report
  • [Book] 新医用放射線科学講座 医用画像情報工学2018

    • Author(s)
      内山良一(分担執筆)
    • Total Pages
      13
    • Publisher
      医歯薬出版株式会社
    • Related Report
      2018 Research-status Report

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Published: 2017-04-28   Modified: 2021-02-19  

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