| Project/Area Number |
20K09341
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 56010:Neurosurgery-related
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| Research Institution | Tokyo Medical and Dental University |
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Principal Investigator |
Inaji Motoki 東京医科歯科大学, 医学部附属病院, 講師 (00422486)
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| Project Period (FY) |
2020-04-01 – 2023-03-31
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| Project Status |
Completed (Fiscal Year 2022)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2022: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2021: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2020: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | epilepsy / HFO / ECoG / cardiac repolarization / adenosine / HRV |
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| Outline of Research at the Start |
アデノシンはてんかん発作及び心拍変動の両者に関与しうる伝達物質であるこのことから、本研究はてんかん患者において、アデノシンA1受容体を可視化する[11C]MPDX PETを用いて、心臓自律神経調整に関与するといわれる島皮質、前頭前野、帯状回、扁桃体、脳幹の受容体変化を測定し、発作時長時間VIDEO-EEGにて測定した発作前後の心拍変動結果との相関を明らかにして、てんかん発作が心拍に影響するメカニズムに迫る
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| Outline of Final Research Achievements |
We clarified the correlation between the results of intracranial electroencephalography using SEEG and electrocardiogram changes. We also examined the correlation between intraoperative ECoG findings and HFO, and demonstrated the validity of the evaluation of hippocampal epileptogenicity via the parahippocampal gyrus ECoG, as well as the validity of HFO analysis. We also clarified the effects of sevoflurane anesthetics on intraoperative EEG (Orihara, Inaji Epilepsy Res. 2022).We are also considering introducing machine learning into EEG analysis methods, and created a diagnostic algorithm based on machine learning using trauma patients. (Abe, Inaji et.al Netw Open 2022) In a three-year research period, we were able to demonstrate the application of epilepsy and electrocardiogram changes to seizure prediction and the effects on electrocardiogram abnormalities.
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| Academic Significance and Societal Importance of the Research Achievements |
てんかん発作と心電図の関係を明らかにすることは、心電図を用いた発作予知の実用化につながる他、SUDEPの解明につながると考えられる。このために皮質脳波におけるHFOや麻酔薬の影響を明らかにする必要があった。また機械学習の方法論はてんかん以外の脳外科疾患にも実用が可能であり、我々は頭部外傷の予後予測アルゴリズムなどに適応することを示した。
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