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Arely detection of the brain atrophy with Sy-VBM using MRI

Research Project

Project/Area Number 20K08057
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 52040:Radiological sciences-related
Research InstitutionJuntendo University

Principal Investigator

Goto Masami  順天堂大学, 保健医療学部, 先任准教授 (30375844)

Project Period (FY) 2020-04-01 – 2024-03-31
Project Status Completed (Fiscal Year 2023)
Budget Amount *help
¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2023: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2022: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2021: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2020: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Keywords脳形態評価 / 磁気共鳴画像 / 脳萎縮 / 脳機能 / Synthetic MRI / VBM
Outline of Research at the Start

磁気共鳴(MR)画像をVoxel-based morphotometry(VBM)解析し脳容積評価を行う手法は、脳変性を伴う多数の疾患を対象とした解析に加え、老化による脳形態変化などを含めた広い領域で利用されている。本研究は、脳組織のMR定量値を算出することにより作成された画像をVBM解析に応用した新規脳容積評価法(Sy-VBM)を構築し、これまでのVBM解析より非常に高い感度で脳容積変化を捉え、脳萎縮が原因となる疾患の早期発見、高精度バイオマーカーの役割を果たすことを目的とする。

Outline of Final Research Achievements

Magnetic resonance (MR) imaging, combined with Voxel-based Morphometry (VBM) analysis, is widely used for assessing brain volume changes in various conditions, including neurodegenerative diseases. In this study, we developed a novel brain volume evaluation method called Sy-VBM by applying VBM analysis to MR images generated from quantitative measurements of brain tissue. Sy-VBM demonstrates significantly higher sensitivity in detecting brain volume changes compared to existing methods, making it a valuable tool for early detection of diseases associated with brain atrophy and serving as a high-precision biomarker. Additionally, we validated that the multi-contrast region extraction technique forming the foundation of Sy-VBM achieves superior accuracy in region segmentation compared to previous approaches.

Academic Significance and Societal Importance of the Research Achievements

パーキンソン病やアルツハイマー型認知症、統合失調症に罹患する人口は増加傾向にある。磁気共鳴(MR)画像をVoxel-based morphotometry(VBM)解析することによる脳容積評価法は、このような疾患に対する研究や臨床応用において数多く行われており、病態進行評価や疾患鑑別指標としての脳容積評価法の有用性は確立されている。この脳容積評価法に関連する技術を改善することは、疾患の早期発見や経過観察のためのバイオマーカの精度を向上させ、健康維持への貢献を果たすことができる。さらに、自身の脳萎縮状態を把握することは予防医学にも関連し、医療費削減にも貢献できる。

Report

(5 results)
  • 2023 Annual Research Report   Final Research Report ( PDF )
  • 2022 Research-status Report
  • 2021 Research-status Report
  • 2020 Research-status Report
  • Research Products

    (6 results)

All 2023 2022 2020

All Journal Article (3 results) (of which Peer Reviewed: 3 results) Presentation (3 results)

  • [Journal Article] Accuracy of skull stripping in a single-contrast convolutional neural network model using eight-contrast magnetic resonance images2023

    • Author(s)
      Goto M, Otsuka Y, Hagiwara A, et al.、
    • Journal Title

      Radiol Phys Technol

      Volume: 16 Issue: 3 Pages: 373-383

    • DOI

      10.1007/s12194-023-00728-z

    • Related Report
      2023 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Analysis of synthetic magnetic resonance images by multi-channel segmentation increases accuracy of volumetry in the putamen and decreases mis-segmentation in the dural sinuses.2023

    • Author(s)
      Goto M, Fukunaga I, Hagiwara A, Fujita S, Hori M, Kamagata K, Aoki S, Abe O, Sakamoto H, Sakano Y, Kyogoku S, Daida H.
    • Journal Title

      Acta Radiol.

      Volume: 64 Issue: 2 Pages: 741-750

    • DOI

      10.1177/02841851221089835

    • Related Report
      2022 Research-status Report 2021 Research-status Report
    • Peer Reviewed
  • [Journal Article] Using modulated and smoothed data improves detectability of volume difference in group comparison, but reduces accuracy with atlas-based volumetry using Statistical Parametric Mapping 12 software.2022

    • Author(s)
      Goto M, Murata S, Hori M, Nemoto K, Kamatgata K, Aoki S, Abe O, Sakamoto H, Sakano Y, Kyogoku S, Daida H.
    • Journal Title

      Acta Radiol.

      Volume: Online ahead of print Issue: 6 Pages: 0-0

    • DOI

      10.1177/02841851211032442

    • Related Report
      2021 Research-status Report
    • Peer Reviewed
  • [Presentation] ディープラーニングベースの脳区域抽出ソフトウェアの精度と再現性2023

    • Author(s)
      後藤政実 鎌形康司 高林海斗 他
    • Organizer
      第51回日本磁気共鳴医学会大会
    • Related Report
      2023 Annual Research Report
  • [Presentation] Accuracy of skull stripping in a single-contrast convolutional neural-network model on eight contrast magnetic resonance images.2022

    • Author(s)
      Goto M, Otsuka Y, Hagiwara A, Fujita S, Hori M, Kamagata K, Aoki S, Abe O, Sakamoto H, Sakano Y, Kyogoku S, Daida H.
    • Organizer
      The 22nd International Society of Radiographers and Radiological Technologists (ISRRT)
    • Related Report
      2022 Research-status Report
  • [Presentation] Decreased mis-segmentation in SPM 12: multi-channel analysis of synthetic magnetic resonance imaging2020

    • Author(s)
      Goto M, Fukunaga I, Hagiwara A, et al.
    • Organizer
      第22回日本ヒト脳機能マッピング学会
    • Related Report
      2020 Research-status Report

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Published: 2020-04-28   Modified: 2025-01-30  

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