Prediction of device-related complications after continuous-flow left ventricular assist device implantation using artificial intelligence trained on acoustic spectra
Project/Area Number |
18K16388
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Research Category |
Grant-in-Aid for Early-Career Scientists
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Allocation Type | Multi-year Fund |
Review Section |
Basic Section 55030:Cardiovascular surgery-related
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Research Institution | Osaka University |
Principal Investigator |
Misumi Yusuke 大阪大学, 医学部附属病院, 医員 (20631477)
|
Project Period (FY) |
2018-04-01 – 2020-03-31
|
Project Status |
Completed (Fiscal Year 2019)
|
Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2019: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2018: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
|
Keywords | 補助人工心臓 / 在宅管理 / 合併症 / 音響解析 / 人工知能 / 機械学習による予測モデルの作成 / 植込み型左室補助人工心臓 / 駆動音解析 |
Outline of Final Research Achievements |
Left ventricular assist devises (LVADs) has become an important treatment of choice for patients with end-stage heart failure. As the growing number of patients receiving implantable LVAD therapy, there is an increasing clinical need to sensitively detect LVAD malfunction in daily lives of patients at home as in the case of tele-monitoring medical care system in the near future. In patients receiving implantable LVAD therapy, diagnosing modalities for major device-related complications require hospital visits and not suitable for a long-term tele-monitoring at home. LVAD acoustic signals are easily obtainable with an electronic stethoscope from the chest wall and could be potentially a suitable modality for tele-monitoring care of LVAD patients at home. In this study, we investigated the relationships between the changes in LVAD sound and relevant clinical outcomes such as pump thrombosis or malfunction.
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Academic Significance and Societal Importance of the Research Achievements |
本研究成果を元に、LVAD駆動音の音響解析を用いた早期異常検出システムの技術的基盤を構築し、LVAD在宅管理における遠隔診断への応用の足がかりとしたい。駆動音の音響解析によりLVAD駆動異常の早期診断や循環動態の把握が可能となれば、LVAD装着患者が在宅にて手軽に自身のLVAD駆動状況を把握可能なシステムに応用できると考えられる。重篤な合併症の兆候を早期に検出し治療へ繋げることで、今後増加すると見込まれる在宅LVAD植込み患者の生活の質を維持すると共に、医療機関の救急・外来対応の負担を軽減させることが見込まれるものである。
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Report
(3 results)
Research Products
(3 results)
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[Presentation] Predicting Cerebrovascular Accident in Patients with Implantable Ventricular Assist Device Using Artificial Intelligence Trained on Acoustic Spectra2019
Author(s)
Yusuke Misumi, Hidetsugu Asanoi, Shigeru Miyagawa, Yasushi Yoshikawa, Hiroki Hata, Daisuke Yoshioka, Satoshi Kainuma, Takuji Kawamura,Ai Kawamura, Yuichi Maruyama, Koichi Toda, and Yoshiki Sawa
Organizer
American Heart Association Scientific Sessions 2019
Related Report
Int'l Joint Research
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[Presentation] Prediction of Aortic Valve Insufficiency after Continuous-flow Left Ventricular Assist Device Implantation Using Artificial Intelligence Trained on Acoustic Spectra2019
Author(s)
Yusuke Misumi, Hidetsugu Asanoi, Shigeru Miyagawa, Yasushi Yoshikawa, Hiroki Hata, Daisuke Yoshioka, Satoshi Kainuma, Shohei Yoshida, Yuichi Maruyama, Koichi Toda, and Yoshiki Sawa
Organizer
日本循環器学会
Related Report
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[Presentation] Prediction of Aortic Valve Insufficiency after Continuous-flow Left Ventricular Assist Device Implantation Using Artificial Intelligence Trained on Acoustic Spectra2018
Author(s)
Yusuke Misumi, Hidetsugu Asanoi, Shigeru Miyagawa, Yasushi Yoshikawa, Hiroki Hata, Daisuke Yoshioka, Satoshi Kainuma, Shohei Yoshida, Yuichi Maruyama, Koichi Toda, and Yoshiki Sawa
Organizer
American Heart Association Scientific Sessions 2018
Related Report
Int'l Joint Research