Ramachandra Abhay B, Sankaran Sethuraman, Humphrey Jay D, Marsden Alison L
J Biomech Eng. 2015 Mar;137(3):0310091-03100910. doi: 10.1115/1.4029021. Epub 2015 Jan 29.
Vein maladaptation, leading to poor long-term patency, is a serious clinical problem in patients receiving coronary artery bypass grafts (CABGs) or undergoing related clinical procedures that subject veins to elevated blood flow and pressure. We propose a computational model of venous adaptation to altered pressure based on a constrained mixture theory of growth and remodeling (G&R). We identify constitutive parameters that optimally match biaxial data from a mouse vena cava, then numerically subject the vein to altered pressure conditions and quantify the extent of adaptation for a biologically reasonable set of bounds for G&R parameters. We identify conditions under which a vein graft can adapt optimally and explore physiological constraints that lead to maladaptation. Finally, we test the hypothesis that a gradual, rather than a step, change in pressure will reduce maladaptation. Optimization is used to accelerate parameter identification and numerically evaluate hypotheses of vein remodeling.
静脉适应不良会导致长期通畅性不佳,这是接受冠状动脉旁路移植术(CABG)或进行使静脉承受升高的血流和压力的相关临床手术的患者面临的一个严重临床问题。我们基于生长和重塑的约束混合理论(G&R)提出了一个静脉对压力变化的适应性计算模型。我们确定了能最佳匹配小鼠腔静脉双轴数据的本构参数,然后对静脉进行数值模拟,使其处于压力变化条件下,并针对G&R参数的一组生物学合理范围量化适应程度。我们确定了静脉移植物能实现最佳适应的条件,并探索导致适应不良的生理限制因素。最后,我们检验了压力逐渐变化而非突然变化会减少适应不良这一假设。优化方法用于加速参数识别并对静脉重塑假设进行数值评估。