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2018 Fiscal Year Final Research Report

Noninvasive assessment of oxygen extraction fraction using high-field MRI

Research Project

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Project/Area Number 16K10798
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Neurosurgery
Research InstitutionIwate Medical University

Principal Investigator

Uwano Ikuko  岩手医科大学, 医歯薬総合研究所, 助教 (20468317)

Co-Investigator(Kenkyū-buntansha) 小笠原 邦昭  岩手医科大学, 医学部, 教授 (00305989)
佐々木 真理  岩手医科大学, 医歯薬総合研究所, 教授 (80205864)
Research Collaborator KUDO Kohsuke  
YAMASHITA Fumio  
Project Period (FY) 2016-04-01 – 2019-03-31
Keywords脳酸素摂取率 / 高磁場MRI / 血行力学的脳虚血 / 磁化率イメージング
Outline of Final Research Achievements

We investigated whether oxygen extraction fraction (OEF) maps generated by magnetic resonance quantitative susceptibility mapping (QSM) at high-field MRI enabled detection of OEF changes when compared with those obtained with PET. OEF ratios on QSM-OEF images at 7 Tesla and 3 Tesla MRI showed a good correlation with those on PET-OEF images in patients with unilateral steno-occlusive internal carotid artery/middle cerebral artery lesions, suggesting that noninvasive OEF measurement by MRI can be a substitute for PET. In addition, we found that preoperative QSM-OEF at 7 Tesla could identify patients at risk for cerebral hyperperfusion following carotid endarterectomy, and that the 7 Tesla QSM-OEF at 5 min after acetazolamide administration mostly correlates with hemodynamics in the patients with major cerebral arterial steno-occlusive disease. Moreover, correlations between QSM-OEF and PET-OEF in patients with chronic ischemia were improved when using high-resolution source images.

Free Research Field

MRIによる脳循環代謝解析

Academic Significance and Societal Importance of the Research Achievements

MRIを用いたOEF計測は、PETやSPECTに代わる第一選択の脳循環代謝検査となることが大いに期待される。また、ASL (arterial spin labeling)法による無侵襲脳血流計測と組み合わせることで、脳酸素代謝率の算出も可能となる。
本手法は無侵襲であり、日常検査としての繰り返し利用を実現し、脳梗塞の予防や治療方針の決定に大きく貢献することができる。また、脳虚血以外にも認知症など多くの脳神経疾患は酸素代謝に変化をもたらしていることから、本研究のOEF計測は多くの脳疾患の病態解明に役立つことが期待される。

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Published: 2020-03-30  

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