Development of a prediction model of cerebral infarction during TAVI with dynamic analysis

2020 Fiscal Year Final Research Report

• Project/Area Number: 18K08739
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 55030:Cardiovascular surgery-related
• Research Institution: Kyushu University
• Principal Investigator: Sonoda Hiromichi 九州大学, 大学病院, 講師 (50596830)
• Co-Investigator(Kenkyū-buntansha): 木村 聡 九州大学, 医学研究院, 助教 (50467916) ; 山下 慶之 九州大学, 大学病院, 助教 (60644705)
• Project Period (FY): 2018-04-01 – 2021-03-31
• Keywords: TAVI / 脳塞栓症 / 有限要素法

Outline of Final Research Achievements

We analyzed the capacity and the distribution of calcified tissue in preoperative CT data with using three-dimensional image analysis software. It was suggested that there is much onset of the cerebral embolism in patients with large calcified capacity and in patients with unequal calcified distribution of the three leaflets.
We performed dynamic analysis using a finite element method. We were able to show the dynamic characteristic of one part of calcification. But it was difficult to predict dynamic characteristic of all parts of calcification on the aortic valve. It was also difficult to analyze heterogeneous calcification with finite element method, because there was too large data to digitize. It is necessary to simplify data when we actually use the data in practice.

Free Research Field

心臓血管外科

Academic Significance and Societal Importance of the Research Achievements

経カテーテル的大動脈弁置換術（TAVI: Transcatheter aortic valve implantation）は、重度大動脈弁狭窄症に対する比較的新しい治療法であり、従来の外科的大動脈弁置換術と比べて低侵襲である。しかしTAVIの合併症として脳塞栓症があり、高度に石灰化した自己弁を押し広げて人工弁を留置するため、破砕された石灰化病変の塞栓子が脳塞栓症の原因となる。症候性脳梗塞に限らず、無症候性脳梗塞でも認知機能に悪影響を及ぼすことが報告されており、TAVI手術時の脳塞栓症回避は重要な課題である。今回の研究成果は、TAVIの手術リスクを術前に予測する方法になりうるものと考える。