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2018 Fiscal Year Final Research Report

Disease- and Deep Brain Stimulation-Related Metabolic Networks using FDG-PET in Movement disorders

Research Project

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Project/Area Number 16K10788
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Neurosurgery
Research InstitutionThe University of Tokushima

Principal Investigator

MURE HIDEO  徳島大学, 病院, 講師 (00624355)

Co-Investigator(Kenkyū-buntansha) 梶 龍兒  徳島大学, 大学院医歯薬学研究部(医学域), 特命教授 (00214304)
森垣 龍馬  徳島大学, 病院, 助教 (70710565)
大北 真哉  徳島大学, 病院, 特任助教 (20748694)
岡崎 敏之  徳島大学, 大学院医歯薬学研究部(医学域), 助教 (20804389)
Research Collaborator GOTO satoshi  
KAJI ryuji  
Project Period (FY) 2016-04-01 – 2019-03-31
Keywordsジストニア / 画像診断 / FDG-PET
Outline of Final Research Achievements

he effect of deep brain stimulation (DBS) on brain networks has remained unclear in dystonia. We searched for glucose metabolism network patterns that relate to disease and DBS in patients with dystonia.Six patients with dystonia who underwent DBS surgery and 8 healthy volunteers were enrolled in this study. images were obtained pre- and post-DBS surgery in the patients. We detected a dystonia-related network pattern. This pattern comprised relative increase in the superior parietal lobule, postcentral gyrus, precentral gyrus, cingulate gyrus, and angular gyrus. Pattern expression scores were significantly higher in dystonia patients than healthy volunteers. Second pattern suggested relative increase in the postcentral gyrus in post-DBS scans, although the difference was not significant. Our results suggest that networkwide glucose metabolism in the cortical sensorimotor regions are associated with disease and effect of DBS in human dystonia.

Free Research Field

脳神経外科

Academic Significance and Societal Importance of the Research Achievements

ジストニアは国の指定難病であるがパーキンソン病に比べると病態解明や診断法の開発は進んでおらず、その客観的診断法も確立されていない。当施設ではジストニアに対してこれまでに約100例のDBS施行例がありこれは国内有数の治療実績である。治療の標準化および治療効果向上のために、FDG-PETを中心とした脳機能イメージングによる解析を行い、客観的な指標で病態の個体差を明らかにするため 本研究でジストニア患者PET画像データを解析し全脳ネットワークレベルで検出する基盤を確立できた。ジストニアにも特異的神経ネットワークパターンが存在しDBSの予後などの客観的マーカーにすることが可能であると考える。

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Published: 2020-03-30  

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