当前位置: X-MOL 学术Cardiovasc. Eng. Technol. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
A Proof of Concept of a Non-Invasive Image-Based Material Characterization Method for Enhanced Patient-Specific Computational Modeling.
Cardiovascular Engineering and Technology ( IF 1.8 ) Pub Date : 2020-08-03 , DOI: 10.1007/s13239-020-00479-7
B M Fanni 1, 2 , E Sauvage 3, 4 , S Celi 1 , W Norman 3, 4 , E Vignali 1, 2 , L Landini 1, 2 , S Schievano 3, 4 , V Positano 1 , C Capelli 3, 4
Affiliation  

Purpose

Computational models of cardiovascular structures rely on their accurate mechanical characterization. A validated method able to infer the material properties of patient-specific large vessels is currently lacking. The aim of the present study is to present a technique starting from the flow-area (QA) method to retrieve basic material properties from magnetic resonance (MR) imaging.

Methods

The proposed method was developed and tested, first, in silico and then in vitro. In silico, fluid-structure interaction (FSI) simulations of flow within a deformable pipe were run with varying elastic modules (E) between 0.5 and 32 MPa. The proposed QA-based formulation was assessed and modified based on the FSI results to retrieve E values. In vitro, a compliant phantom connected to a mock circulatory system was tested within MR scanning. Images of the phantom were acquired and post-processed according to the modified formulation to infer E of the phantom. Results of in vitro imaging assessment were verified against standard tensile test.

Results

In silico results from FSI simulations were used to derive the correction factor to the original formulation based on the geometrical and material characteristics. In vitro, the modified QA-based equation estimated an average E = 0.51 MPa, 2% different from the E derived from tensile tests (i.e. E = 0.50 MPa).

Conclusion

This study presented promising results of an indirect and non-invasive method to establish elastic properties from solely MR images data, suggesting a potential image-based mechanical characterization of large blood vessels.



中文翻译:

用于增强患者特定计算建模的非侵入性基于图像的材料表征方法的概念证明。

目的

心血管结构的计算模型依赖于其准确的机械特性。目前缺乏能够推断患者特定大血管材料特性的经过验证的方法。本研究的目的是提出一种从流动面积 (QA) 方法开始的技术,以从磁共振 (MR) 成像中检索基本材料特性。

方法

所提出的方法首先在计算机中进行了开发和测试,然后体外进行了测试。在 silico中,可变形管道内的流固耦合 (FSI) 模拟在 0.5 和 32 MPa 之间的不同弹性模量 ( E ) 下运行。基于 FSI 结果评估和修改建议的基于 QA 的公式,以检索E值。在体外,在 MR 扫描中测试了连接到模拟循环系统的顺应体模。根据修改后的公式获取和后处理模型的图像,以推断模型的E。体外结果成像评估根据标准拉伸试验进行了验证。

结果

FSI 模拟的计算机结果用于根据几何和材料特性推导出原始配方的校正因子。在体外,基于 QA 的修正方程估计平均E = 0.51 MPa,与拉伸试验得出的E (即E = 0.50 MPa)有 2% 的差异。

结论

这项研究展示了一种间接和非侵入性方法的有希望的结果,该方法仅从 MR 图像数据中建立弹性特性,表明大血管的潜在基于图像的机械表征。

更新日期:2020-08-04
down
wechat
bug