安静時機能結合MRI  [in Japanese] Resting-state Functional Connectivity MRI  [in Japanese]

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Author(s)

    • 花川 隆 HANAKAWA Takashi
    • 国立研究開発法人国立精神・神経医療研究センター脳病態統合イメージングセンター先進脳画像研究部 National Center of Neurology and Psychiatry

Abstract

安静時機能結合MRI(resting-stage functional connectivity MRI)は,安静時に機能ネットワークに生じる自発脳活動の相関を指標とし,脳機能結合の状態を評価するMRI技術である.時間的に相関する安静時BOLD信号の変動を示す脳領域のセットは安静時機能結合ネットワークとよばれる.安静時機能結合ネットワークのうち,特に内側前頭前野,後部帯状回と楔前部,側頭頭頂結合部および海馬が構成するネットワークは,安静時にもっとも高い活動を示すデフォルトモードネットワーク(DMN)として知られる.アルツハイマー型認知症ではDMNに機能結合の異常があり,さらに認知症の前段階と考えられる各種病態でもDMNに異常があることが示されており,認知症の早期診断バイオマーカーの測定手法として,安静時機能結合MRIに対する期待が高まっている.

Resting-state functional connectivity MRI (rsfcMRI) is an emerging MRI technique that allows for assessment of functional connectivity between brain regions through the detection of intrinsic oscillations occurring in the resting-state networks. The default mode network (DMN) is one of the resting-state networks and consists of the medial prefrontal cortex, posterior cingulate cortex-precuneus, temporo-parietal junction and medial temporal cortex including the hippocampus. DMN is characterized as a set of brain regions that show higher brain activity during rest than during demanding cognitive tasks, and is suggested for roles in higher cognitive functions such as the self and awareness. Moreover, rsfcMRI studies have shown that DMN is abnormal in patients with senile dementia of Alzheimer type and mild cognitive impairment and also in cognitively normal elderly subjects with amyloid deposition. As such rsfcMRI is suitable as a tool for measuring biomarkers for the diagnosis and monitoring of neuro-psychiatric disorders including dementia. Many measurement and analytic methods are available for rsfcMRI. For the clinical application, however, it is important to develop standardized measurement and analytic techniques, which can be easily applicable to clinical settings.

Journal

  • Medical Imaging Technology

    Medical Imaging Technology 34(1), 13-17, 2016

    The Japanese Society of Medical Imaging Technology

Codes

  • NII Article ID (NAID)
    130005122383
  • Text Lang
    JPN
  • ISSN
    0288-450X
  • Data Source
    J-STAGE 
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