Mock circulatory loops used for testing cardiac assist devices: A review of computational and experimental models

灵活性(工程) 可控性 计算机科学 循环系统 医学 心脏病学 应用数学 数学 统计
作者
Femke Cappon,Tingting Wu,Theodore G. Papaioannou,Xinli Du,Po‐Lin Hsu,Ashraf W. Khir
出处
期刊:International Journal of Artificial Organs [SAGE Publishing]
卷期号:44 (11): 793-806 被引量:30
标识
DOI:10.1177/03913988211045405
摘要

Heart failure is a major health risk, and with limited availability of donor organs, there is an increasing need for developing cardiac assist devices (CADs). Mock circulatory loops (MCL) are an important in-vitro test platform for CAD’s performance assessment and optimisation. The MCL is a lumped parameter model constructed out of hydraulic and mechanical components aiming to simulate the native cardiovascular system (CVS) as closely as possible. Further development merged MCLs and numerical circulatory models to improve flexibility and accuracy of the system; commonly known as hybrid MCLs. A total of 128 MCLs were identified in a literature research until 25 September 2020. It was found that the complexity of the MCLs rose over the years, recent MCLs are not only capable of mimicking the healthy and pathological conditions, but also implemented cerebral, renal and coronary circulations and autoregulatory responses. Moreover, the development of anatomical models made flow visualisation studies possible. Mechanical MCLs showed excellent controllability and repeatability, however, often the CVS was overly simplified or lacked autoregulatory responses. In numerical MCLs the CVS is represented with a higher order of lumped parameters compared to mechanical test rigs, however, complex physiological aspects are often simplified. In hybrid MCLs complex physiological aspects are implemented in the hydraulic part of the system, whilst the numerical model represents parts of the CVS that are too difficult to represent by mechanical components per se. This review aims to describe the advances, limitations and future directions of the three types of MCLs.
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