2022 Fiscal Year Final Research Report
Computational modeling of patient-specific cardiovascular dynamics based on multimodality medical imaging
Project/Area Number |
21K18037
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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 90110:Biomedical engineering-related
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Research Institution | Osaka University |
Principal Investigator |
Otani Tomohiro 大阪大学, 大学院基礎工学研究科, 講師 (40778990)
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Project Period (FY) |
2021-04-01 – 2023-03-31
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Keywords | 血流動態 / 循環器 / 脳脊髄液 / 数値流体力学 / データ同化 / MRI |
Outline of Final Research Achievements |
This study developed clinical image-based computational frameworks of fluid dynamics simulator using high-performance computing, artifact removal algorithm from magnetic resonance imaging (MRI) of physiological flow, and flow data assimilation using MRI images. Computational simulation of the left atrium (LA) based on electrocardiography-gated computed tomography clarified the effect of lobectomy on LA hemodynamics. Next, subject-specific assessment and correction of the artifact in flow MRI data was developed and its efficacy was demonstrated using MRI images of cerebrospinal fluid flow in the brain ventricle system. Furthermore, a flow data assimilation based on MRI images was developed based on optimal boundary controls and numerical examples successfully demonstrated its capabilities to obtain fine and physically consistent profiles of physiological flow in living bodies.
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Free Research Field |
計算バイオメカニクス
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Academic Significance and Societal Importance of the Research Achievements |
本研究で構築した,大規模並列化を駆使した循環器血流の患者別解析や,生体流れのMRI計測におけるアーチファクト除去および流体データ同化手法は,数理・力学計算による生体流れ計測・理解の高度化をもたらすものであり,いずれも生体流れ解析の汎用的なツールとなり得る.特に,MRIによる流動計測は,血流場だけでなく脳脊髄液流れなど様々な応用および臨床診断への展開が期待されるが,時空間解像度の限界や複数種類のアーチファクトの問題を含んでおり,定量的妥当性の向上が望まれている.本研究で構築した技術群は,はこれらの問題の解決に向けた基幹技術と位置付けられる.
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