The impact of different aortic valve calcification patterns on the outcome of transcatheter aortic valve implantation: A numerical simulation study
10.16156/j.1004-7220.2017.06.004
- VernacularTitle:不同钙化模式对经导管主动脉瓣膜植入效果影响的数值模拟研究
- Author:
Rong-Hui LIU
1
;
Chang JIN
;
Wen-Tao FENG
;
Ze-Bin WU
;
Sheng-Ping ZHONG
;
Li-Zhen WANG
;
Yu-Bo FAN
Author Information
1. 北京航空航天大学生物与医学工程学院
- Keywords:
Transcatheter aortic valve implantation (TAVI);
Finite element analysis;
Calcification;
Paravalvular regurgitation
- From:
Journal of Medical Biomechanics
2017;32(6):506-512
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the effect of different calcification patterns on the outcome of transcatheter aortic valve implantation (TAVI) by the finite element method.Methods Three calcified human aortic root models (coaptation line calcification model,attachment line calcification model and circular calcification model) were developed according to the location of calcified plaques on the aortic valve leaflets.The processes of self-expanding transcatheter aortic valve implanted into the 3 calcified models were simulated by ABAQUS software.The effects of different calcification patterns on the aortic root stresses,valve frame distortions and paravalvular gaps were analyzed.Results Circular calcification model had the largest maximum principal stress on calcified plaques (18.42 MPa),which might result in a higher risk of stroke after implantation;the circular calcification model also had the greatest distortion of the valve frame,which might lead to worse prosthetic durability;the paravalvular gaps area of the attachment line calcification model was 37.2 mm2,which was more than twice that of the other 2 models,causing more serious paravalvular regurgitation.Cenclusiens Different aortic valve calcification patterns are related to aortic root stresses,valve frame distortions and paravalvular gaps after TAVI,which will have an impact on postoperative complications and prothesis durability.The research findings provide references for the prediction of clinical outcome after TAVI.
