用于模拟肿瘤生长引起的脑组织粘弹性力学行为的位置和时间相关的压力分布。
A position- and time-dependent pressure profile to model viscoelastic mechanical behavior of the brain tissue due to tumor growth.
机构信息
Faculty of Mechanical Engineering, Semnan University, Semnan, Iran.
Department of Ophthalmology and Visual Sciences, University of Alabama at Birmingham, Birmingham, AL, USA.
出版信息
Comput Methods Biomech Biomed Engin. 2023 May;26(6):660-672. doi: 10.1080/10255842.2022.2082245. Epub 2022 May 31.
This study proposed a computational framework to calculate the resultant position- and time-dependent pressure profile on the brain tissue due to tumor growth. A finite element (FE) patch of the brain tissue was constructed and an inverse dynamic FE-optimization algorithm was used to calculate its viscoelastic mechanical properties under compressive uniaxial loading. Two patient-specific post-tumor resection FE models were input to the FE-optimization algorithm to calculate the optimized 3-order position-dependent and normal distribution time-dependent pressure profile parameters. The optimized viscoelastic material properties, the most suitable simulation time, and the optimized 3-order position- and -time-dependent pressure profiles were calculated.
本研究提出了一种计算由于肿瘤生长引起的脑组织位置和时间相关压力分布的计算框架。构建了脑组织的有限元（FE）贴片，并使用反向动力学 FE 优化算法在压缩单轴加载下计算其黏弹性力学特性。将两个特定于患者的肿瘤切除后 FE 模型输入到 FE 优化算法中，以计算优化的三阶位置相关和正态分布时间相关压力分布参数。计算了优化的黏弹性材料特性、最合适的模拟时间以及优化的三阶位置和时间相关压力分布。
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